Department of Statistics Academic Program Review Spring 2015

Home , Alyson Wilson, Andrea Ferris, Howell Tong, Vitamer

Department of Statistics • Texas A&M University • 3143 TAMU • College Station, TX 77843-3143 (979) 845-3141 • www.stat.tamu.edu

Table of Contents

I. Introduction Brief History of the Department……………………………………………………. 4 Mission and Goals………………………………………………………………….. 8 Administrative Structure of the Department………………………………………... 11 Resources…………………………………………………………………………... 13 Analysis……………………………………………………………………………. 14 Undergraduate Program……………………………………………………………. 15 Graduate Program………………………………………………………………….. 16 Professional Education……………………………………………………………... 19 Challenges and Opportunities……………………………………………………… 20 Assessment………………………………………………………………………… 22 II. Student Report Graduate Program in Statistics……………………………………………………… 28 Master of Science Program…………………………………………………………. 29 Doctor of Philosophy Program……………………………………………………... 32 Internship Program…………………………………………………………………. 35 Undergraduate Course Offerings…………………………………………………… 36 Graduate Course Offerings………………………………………………………… 37 Scheduling Coursework…………………………………………………………….. 42 Graduate Program Admissions Criteria……………………………………………... 43 GRE Scores for First Time Students………………………………………………... 44 Graduate Students Applied, Admitted, and Enrolled ………………………………. 45 Students by GPR Range……………………………………………………………. 48 Institutional Support for Full Time Students……………………………………….. 50 Honors & Awards Received by Students…………………………………………… 51 Statistics Graduate Student Association…………………………………………….. 54 Student Publications………………………………………………………………... 55 Professional Development Opportunities for Students……………………………... 56 Average Year to Degree, By Degree Program………………………………………. 57 Masters Graduation and Retention Report…………………………………………. 58 Doctoral Graduation and Retention Report………………………………………... 59 Master’s Degrees Awarded…………………………………………………………. 60 Ph.D. Degrees Awarded……………………………………………………………. 65 Ph.D. Graduate Employers………………………………………………………… 69 III. Faculty Information Department of Statistics Faculty……………………………………………………. 73 Average FTE for Faculty Rank……………………………………………………... 76 Faculty Rank by Ethnicity………………………………………………………….. 77 Headcount by Faculty Rank………………………………………………………... 78 Demographics by Faculty Rank…………………………………………………….. 79 Honors and Awards Received by Faculty…………………………………………... 80 Committee Assignments……………………………………………………………. 81 Faculty Editorial Service……………………………………………………………. 82

Primary Investigator Awards……………………………………………………….. 85 Co-Principal and Collaborating Investigator Awards……………………………….. 88 Faculty Collaborations within Texas A&M…………………………………………. 90 SCH per FTE and Student/Faculty Ratio………………………………………….. 93 Faculty Summary…………………………………………………………………… 94 Weighted Average Faculty Salary Comparisons……………………………………... 95 Goldplate Funding………………………………………………………………….. 96 Semester Credit Hours Taught by Faculty Rank…………………………………….. 97 History of Courses Taught………………………………………………………….. 102 IV. Appendix A. MS Statistics and Online Programs…………………………………………. 105 B. MS Analytics Overview……………………………………………………... 111 C. Proposal for an Undergraduate Major in Statistics………………………….. 115 D. Postdoctoral Training Program in Biostatistics, Bioinformatics and the Biological Basis of Nutrition and Cancer…………………………… 122 E. Institute for Applied Mathematics and Computational Science……………... 124 F. Center for Statistical Bioinformatics………………………………………... 128 G. Statistics Gifts and Endowments…………………………………………… 129 H. Colloquium and Seminar Speakers………………………………………….. 130 I. Department of Statistics Alumni Advisory Board…………………………… 142 J. Faculty Postdoctoral Researchers…………………………………………… 200 K. Department Bylaws………………………………………………………… 202 L. Faculty Biographical Sketches………………………………………………. 217

I. INTRODUCTION

Brief History of the Department The Department of Statistics was formed in 1962 as the Graduate Institute of Statistics with the mandate of providing statistical research, consulting, and instruction for Texas A&M University. The Department was authorized from its inception to grant MS and PhD degrees. Prior to 1962, a number of different departments provided the few statistics courses taught at the undergraduate and graduate level. H.O. Hartley was the Institute's first Director and by the fall of 1964 the Department consisted of a faculty of five with twelve graduate students. The Department resided in several locations prior to its moving to the Olin E. Teague Building in 1966. The construction of this building was greatly assisted by an NSF Center for Excellence grant obtained by Professor Hartley and others. The university’s computing center also resided in the Teague Building. The rapid expansion of the university during the 1970s and subsequent demands for space by the computing center resulted in the Institute moving to its current location on the fourth floor of the John R. Blocker Building in 1981. In the fall of 2004, the Department acquired additional office space on the fifth floor of the Blocker Building. The Graduate Institute of Statistics was included in 1966 as a member of the newly formed College of Science and in 1984 acquired its current name, the Department of Statistics. In 1977, Dr. Hartley retired and was succeeded by Dr. William B. Smith. By the early 1980s the Department had grown to 18 faculty members with 40-50 graduate students. The next two department heads were Dr. Raymond J. Carroll, appointed in 1986, and Dr. H. Joseph Newton in 1990. The faculty by this time had grown to 25 members with 60-65 graduate students. Along with this increase in the size of the faculty and graduate student population was a concurrent increase in research productivity and funded research. Another indicator of the university's high regard for the Department was the designation of Drs. Manny Parzen and Raymond J. Carroll as Distinguished Professors. At the time, there were only 46 faculty members currently holding the title of Distinguished Professor at Texas A&M University. In 1998, Dr. James Calvin was appointed to head the Department, which, at that time, consisted of 26 faculty members with 60-65 graduate students. Dr. Calvin served as Department Head for 6 years. With the appointment of Dr. Simon Sheather in March 2005 as Department Head, the department embarked on two major initiatives in the area of online teaching. In 2006, the Texas A&M University System Board of Regents approved the introduction of the Master of Science degree in Statistics for distance delivery. The first cohort of 20 students started the program in Fall 2007. By the Spring 2014 semester there were over 400 students enrolled in on-line statistics graduate courses, with 292 seeking an M.S. degree. Over 100

students have completed the program and received their M.S. degree in Statistics. The distance master’s is a key source of revenue for the Department, and arguably the most successful statistics distance-learning program in the nation. Further details regarding the distance learning masters program is provided in Appendix A. In 2012, a second distance-learning program was initiated when an agreement was reached with the Mays Business School to offer a joint MS Analytics program; this program began in Fall 2013. The Analytics program has experienced great initial success, and in the Fall of 2014 28 students enrolled in the program. The first cohort of students is expected to graduate in May 2015. Further details regarding the MS Analytics program is provided in Appendix B. In addition to the distance M.S. programs in Statistics and Analytics, a “fast track” PhD program was introduced in 2008, and a Certificate of Applied Statistics was approved. In 2009, a joint TAMU/SAS certificate was introduced and the number of supported on-campus graduate students was expanded with the introduction of Technology Teaching Assistants. The Department also added two more Distinguished Professors, Drs. Clifford Spiegelman and Bani Mallick. A history of the Department was published on its 50th anniversary in 2012,1 and the anniversary was celebrated the following year in March. A short video prepared for this gathering is available on line at https://www.youtube.com/watch?v=A9v2dZ5C5Ei. In March of 2014, Dr. Valen Johnson was appointed as Department Head. Dr. Johnson was recruited to the Department in 2012 as one of three faculty hires supported by the Applied Mathematical, Statistical and Computational Sciences (AMSCS) white paper, which had been selected as a research landmark area in 2009. From its inception, the Department has been substantially involved in collaborative research. Dr. Hartley and the faculty had research grants and contracts from ONR, NASA, Army Research Office, and National Center for Toxicological Research. For over twenty years, the Texas Agricultural Experiment Station provided funding for statistical consulting. The Department was actively involved in the development of the Center for Environmental and Rural Health, an NIEHS funded research center. Also, several faculty members greatly assisted in obtaining the competitive renewal of Texas A&M University's EPA funded Superfund Basic Research Program. In 2001, Professor Carroll received a grant from NCI to establish a two-year training program in Bioinformatics. The success of this program has resulted in the grant being renewed through 2016. A number of faculty have also been appointed as adjunct faculty at M.D. Anderson Cancer Center (MDACC),

1 S. Sheather and J. South, Texas A&M Department of Statistics, Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., eds A. Agresti and X.-L. Meng, Springer, New York (2012). 5

and several students and post-doctoral researchers are currently jointly supported by MDACC and Departmental faculty. The Department has established four major lecture and award series. The H. O. Hartley Memorial Lecture series was established in 1988 to honor the memory of Herman Otto Hartley. Past speakers include Peter J. Diggle, Bradley Efron, E.J. Hannan, Sir David R. Cox, Wayne Fuller, Adrian Raftery, Peter Hall, Terry Speed, James Berger, Edward George, Regina Liu, and David Dunson. The Parzen Prize for Statistical Innovation was established in 1994. Past awardees include Grace Wahba, Donald P. Rubin, Bradley Efron, C. R. Rao, David R. Brillinger, Jerome H. Friedman, Alan E. Gelfand, Nancy Reid, Marvin Zelen, Roger Koenker, Adrian Raftery, and Trevor Hastie. The Department established the third lectureship, the Ronald R. Hocking Lecture Series, in 2002 to recognize exceptional contributions to the field of linear models and their generalizations. Past speakers include Ronald Hocking, David Harville, Dallas Johnson, Ramon Littell, Michael Kutner, Tim Hesterberg, Brian Marx, Oliver Schabenberger, John Sall, Garrett Fitzmaurice, and Goutam Chakraborty. In 2009 the fourth award and lecture series, the Raymond J. Carroll Young Investigator Award, was inaugurated. This award is bestowed in alternate years on a junior investigator who has made outstanding contributions in the area of statistics. Past recipients include Samuel Kou, Marc Suchard, and Tyler J. VanderWeele. All four of these lecture/award series have provided the Department’s graduate students with the opportunity to interact with pioneers in the statistics profession. The Department also presents several prestigious internal awards to outstanding former and current students. Among these is the Margaret Sheather Memorial Award in Statistics, which was awarded from 2010-2014 and was presented annually to the student(s) with the most outstanding master’s project(s). In 2015 this award was re-established as the Margaret Sheather Memorial Award in Analytics and in the future it will be awarded to the MS Analytics student(s) with the most outstanding capstone project(s). The Hartley Award is presented annually to a former student for distinguished service to the discipline of statistics. The William S. Connor Award is presented annually to the student whom the faculty deems most outstanding amongst those students passing the preliminary examination during the current year. A description of funds raised to support these awards, as well as the lecture series above, is provided in Appendix G. The Department’s students frequently also attract external awards. Notable among these are the success of our graduate students in recent Capital One Statistical Modeling Competitions. The Department fielded the winning team and a finalist team in 2012, another finalist team in 2013, and the winning and a finalist team in 2014. A list of these awards and other student honors appears on page 51. The Department does not currently offer an undergraduate degree in statistics. However, undergraduates can obtain a concentration in statistics, and the Department developed, in conjunction with

the Mathematics Department, a statistics option within the BS degree in Applied Mathematical Sciences. The Department also offers a minor in statistics. The Department's undergraduate course offering has grown to over ten courses with approximately 5,700 undergraduates enrolled per academic year. Besides the courses offered to its MS and PhD students, the graduate service courses have an enrollment of over 1,500 students per academic year. For many years, the Department hosted a Statistics Advanced Placement Summer Institute on-campus for high school mathematics teachers, and, thanks to the dedication of our Emeritus Professor James Matis, will begin doing so again this summer. This institute provides an opportunity for the Department to interact with AP statistics teachers, and it is our hope that this interaction will serve as a mechanism for advertising the Department’s role in undergraduate statistics education to high school students across the state. In 2012, members of the Department formed Texas A&M Statistical Services, LP, an external consulting center that provides 99% of its profit to Texas A&M University. Drs. Simon Sheather and Edward Jones serve as President and Executive Vice President of this limited partnership. After a period of sustained growth in the number of faculty, from 5 full-time tenure-track faculty members in 1964 to 26 tenure-track faculty members in 2000, the growth in the number of tenure-track faculty has ebbed and flowed since the turn of the century, this despite the dramatic increase in the number of students taking, or wanting to take, statistics courses. The problem has been partially offset by the addition of a highly qualified group of senior lecturers, which is supported from soft money resources. This problem is discussed further in the Challenges and Opportunities Section below, but it is clear that the Department has a pressing need to expand its course offerings to meet the increasing demand for statistics courses in the era of “Big Data.” This need can only be satisfied with an increase in the size of its faculty.

Mission and Goals Statistical science is a broad discipline that encompasses activities from data acquisition and processing, exploratory data analysis, complex modeling of stochastic processes, inference, hypothesis testing, parameter estimation, uncertainty quantification, casual inference, and decision making under uncertainty. The Department’s mission is to function as a leading international center for statistical research, education and service. Faculty members in the Department contribute to a broad spectrum of research in statistical methodology and application, and faculty in the department have received numerous national and international awards for their contributions to statistics. Faculty members in the Department have received the COPPS Award (Carroll), Noether Senior Scholar Award and Lecture (Carroll, Spiegelman), and the Wilcoxon Prize (Carroll). (A more complete listing of faculty awards is provided in on page 80). Current strengths of Department include spatial statistics, Bayesian methodology, functional data analysis, modeling of measurement error, non-parametric methods, and analysis of high and ultra-high dimensional data. Further discussion of the faculty’s research productivity is provided in the Analysis section below. As part of a land-grant university, the Department takes its responsibility for statistical education very seriously. The Department teaches approximately 5,700 undergraduate students each year. A vast majority of these students enroll in service courses designed to provide a rudimentary understanding of statistics that will allow them to interpret scientific findings in their fields of study, as well as to interpret statistical analysis reported in popular media, government studies and business reports. The more advanced of these courses also provide students with background in experimental design, the statistical analysis of simple experiments and observational studies, and regression analysis. In addition to undergraduate service courses, the Department also teaches approximately 1,500 graduate-level students from other departments. Many of these students come from the College of Engineering, but it is common for graduate students from across the university to enroll in the Department’s graduate course offerings to satisfy requirements in their degree programs. A major extension of the Department’s educational mission has been to provide Texas (as well as other U.S. and foreign) students with an opportunity to obtain graduate training remotely through our distance learning program in statistics. The TAMU distance master’s program is one of the largest programs in the nation, having conferred over 100 master’s degrees to program participants since its beginning in 2007. A similar extension of the Department’s educational mission began in 2012 with the start of the Master of

Science degree in Analytics. This program will likely soon enroll approximately 50 students each year into the rapidly expanding field of applied statistics. Faculty members in the department also play a major role in service to the University, to the international statistics community, and to the broader general scientific community. During the last three years, faculty members in the Department have served as editors or co-editors of three statistical journals: Chemometrics & Intelligent Laboratory Systems, Journal of Nonparametric Statistics, and Bayesian Analysis. In addition, they have filled 25 associate editor positions for numerous other journals, including the American Statistician, Biostatistics, Chemometrics & Intelligent Laboratory Systems, Electronic Journal of Statistics, Journal of Biometrics & Biostatistics, Journal of Business and Economics, Journal of the American Statistical Association: Applications & Case Studies, Journal of the American Statistical Association: Theory & Methods, Journal of Computational and Graphical Statistics, Journal of Nonparametric Statistics, Journal of Transportation and Statistics, SIAM Journal of Uncertainty Quantification, STAT, Statistics, and Statistics & Probability Letters. A detailed listing of editorial service provided by Departmental faculty is provided on page 82. The Departmental faculty are also actively engaged in service to the University, and have been instrumental in influencing its direction on both administrative and scientific matters. At the College level, faculty members have served on the Faculty Advisory Committee, the Diversity Committee, and the Dean Search Committee. At the University level, Departmental faculty members have served on dozens of policy making committees and bodies, including the Association of Former Students’ College-Level Teaching Awards Member Selection Committee; Core Curriculum Technology Enhanced Grant Committee; Department Heads Council; Distinguished Award Committee; Email Selection Advisory Committee; External Advisory Board for AgriLife Genomics and Bioinformatics Services (TAGS) Core; Faculty Senate; Faculty Senate College of Science Caucus; Massive Open On-line Course Exploration Committee; Massive Open On-line Course Advisory Committee; President’s Council on Climate and Diversity; President’s Task Force for Faculty Evaluations; Price, Waterhouse & Coopers Advisory Committee; Strategic Planning Committee Strategic Re- allocation Sub-council; Undergraduate Academic Appeals Panel; and the Workplace, Climate & Diversity Committee. In service outside of the University, faculty members have played a significant role in setting national science policy and participating in the governance of major scientific organizations. For instance, faculty members in the Department have served on the National Academy of Science Strategic Highway Research Program and the Board of Trustees for the National Institute of Statistical Standards. They have also assisted in the governance of the American Statistical Association (ASA), the nation’s largest organization devoted to

statistical science. During the last three years, faculty have served on the ASA’s Noether Senior Scholar Award and Noether Young Scholar Award Committees and have been elected as members of the ASA Section on Statistical Consulting. They have served on the Steering Committee for the ASA Conference on Statistical Practice, have co-chaired the ASA Committee on Membership and Retention, and have served on both the ASA Task Force on Membership Growth and as the ASA representative to the AAAS. Faculty members have also served on NSF and NIH review panels.

Administrative Structure of the Department

The graphic below depicts the organizational chart for the Department. Duties and responsibilities for faculty members in the department, and in particular for faculty holding administrative positions in the Department, are described in the Faculty Bylaws, which were adopted in the spring of 2015 and appear in Appendix J. Noteworthy features of the chart include the MS Analytics and Online Program, as well as the lack of an Undergraduate Advisor. As discussed below, the Department is currently in the process of creating an undergraduate degree program in statistics. We anticipate that this degree will begin in the Fall of 2016. An Undergraduate Advisor will be appointed in the Fall of 2015 when this program is approved at the university level. The MS Analytics and Online Program manages the distance learning master’s degree program and the newly instituted MS Analytics program. The Academic Director of the Program is Dr. Simon Sheather, and salaries of the Program staff are paid from the revenue that the Program generates. The program also provides partial salary support for Nathan Segrest, who assists with the program’s IT structure, as well as providing partial support for Technical Teaching Assistants (TTAs), who support the distance learning and analytics programs. In addition to the administrative structure depicted in the organizational chart, the Department also hosts the Center for Statistical Bioinformatics and the Institute for Applied Mathematics and Computational Science (IAMCS). It also sponsors a training program in bioinformatics and nutrition. The entities are described in Appendices D-F.

Professor and Head Assistant to Valen Johnson Department Head Department of Statistics Kristen Vodak Organizational Chart Administrative March 2015 Assistant Elaine James

Academic Director of Graduate Advisor Professor and Associate Distinguished Professors MS Analytics & Online Programs Jianhua Huang Department Head Raymond J. Carroll Simon Sheather Michael Longnecker Bani Mallick Clifford Spiegelman

Assistant to the Director Jennifer South Professors Associate Professors Senior Lecturers

Willa Chen Alan Dabney Derya Akleman Daren Cline Mikyoung Jun Julie Carroll P. Fred Dahm Huiyan Sang Elizabeth Kolodziej Jeffrey Hart Samiran Sinha Hwa Chi Liang Director - Analytics Ursula Müller-Harknett Suhasini Subba Rao Henrik Schmiediche Myra Gonzalez H. Joseph Newton Lan Zhou Keith Hatfield* Mohsen Pourahmadi Program Manager - Analytics Michael Sherman Javier Aldape Suojin Wang *Promotion effective 9/1/15 Thomas Wehrly Director of Operations Assistant Professors Kim Ritchie

Executive Professor Anirban Bhattacharya Director of Information Matthias Katzfuss Edward Jones Post Docs/Researchers Technology James Long Henrik Schmiediche Program Manager - Online Houssein Assaad (RJC) Penny Jackson Irma Hernandez-Magallanes (RJC) Sr. Microcomputer LAN Mathew McLean (RJC) Specialist Business Coordinator Daniel Mohsenizadeh (RJC) Steve Shoemake Wanda Ransome Roger Zoh (RJC) Nathan Segrest

Katherine Reed (VJ) Business Administrator Administrative Assistant Ardala Breda Andrade (VJ) Sandra Wood Nicole Padilla Nilotpal Sanyal (VJ) Ayako Yajima (VJ) Office Software Associate Xuedong Pan (VJ) Andrew Moua

Computer Technician Nathan Segrest Business Coordinator II Program Manager and Graduate Advisor II Athena Robinson Assistant to Raymond Carroll Amy Parker Joyce Sutherland 12

Resources

The physical home for the Department of Statistics is the Blocker Building, dedicated in 1983 and named in honor of John R. Blocker, a member of the class of ‘45 and former member of the Texas A&M University System Board of Regents. The Blocker building is a workhorse for teaching and study at Texas A&M University with its numerous lecture halls, classrooms and labs. In addition to housing the Department of Statistics, it is also home to a computer lab for general use by all A&M students, the Department of Mathematics, Health and Kinesiology, and the Dean’s Office for the College of Science. The Department of Statistics occupies the entire fourth floor, which contains 25,000 square feet divided into 105 offices used by faculty, visitors, lecturers, post docs, graduate students and staff. In addition, the department controls five conference and/or meeting rooms, three class and/or seminar rooms and a server room. The Department of Statistics operates a hybrid-computing environment of over 300 Windows, Mac and Linux systems to meet the computing needs of its faculty and students. The Department controls much of its own computing infrastructure and employs three full time IT professionals to oversee operations. Faculty have regular and recurring access to computing funds, ensuring their personal systems are up to date. A partial list of statistics software available includes Matlab, R, Stata, SAS, JMP and high performance commercial compilers. For computationally intensive research, the department operates a 20-node / 500 core Linux cluster. For teaching, it operates three computing labs with approximately 50 computers in each. Exclusive access and control of these resources enables the cluster and labs to be configured and tuned for statistics faculty research and teaching requirements. Texas A&M University operates multiple research computing clusters to which faculty have access. These include: “Ada,” a 845 node / 16900 core x86 cluster with a peak performance of 337 TFlops, 4PB storage and FDR network fabric; “Neumann,” a 2048 node / 32768 core Blue Gene Q cluster with a peak performance of 419 TFlops and 2PB of storage; “Eos,” a 412 node / 3552 core x86 cluster, 500TB storage and a QDR Infiniband fabric; “Brazos,” a 300 node / 3000 core x86 cluster, 200 TB storage and DDR Infiniband fabric. Several of these clusters contain special compute nodes with up to 2TB of RAM or with GPU equipped nodes. Two smaller Power P7+ clusters with 23 and 49 nodes are available as well. The aggregate peak performance of these computing resources is over 800 TFlops with more than 6PB of storage.

Analysis

The preeminent goal of the Department of Statistics is to establish itself as an international center for statistical research, education and service. In many ways, the department has achieved this goal: It is currently ranked among the top 15 statistics departments in the nation by US News and World Report (sixth among public institutions), and has been ranked as high as 11 (2010). Of course, it would be a mistake for the department to assess its success based entirely on such rankings, although it is necessary for the Department to establish goals and a set of metrics to be used in evaluating its progress toward achieving these goals. In this regard, the imperatives and metrics established by the University in assessing Vision 2020 goals are useful, as many of these imperatives and metrics are highly correlated with external rankings of the Department by entities like US News and World Report. They also coincide well with the goals that the Department has set for itself. Four of the twelve imperatives in the University’s Vision 2020 focus on enhancing the undergraduate experience, building the letters, arts & sciences core, strengthening the graduate program, and building on the tradition of professional education. The key metrics that are being applied by the University to the Department to assess progress toward achieving the Vision 2020 goals involve the following outcomes:

- Publications by faculty - Citations of faculty publications - Grant funding attracted by faculty - Honors and awards - Master’s of Science two-year graduation rates - Doctoral five-year graduation rates

Before discussing assessment criteria and how the Department has performed according to them, it is useful to first discuss the major initiatives that the Department is undertaking and how they support the four Vision 2020 imperatives listed above.

Undergraduate Program Beginning in the fall of 2014, the Department’s faculty endorsed several proposals to develop an undergraduate Bachelor of Science degree program in Statistics. Over the course of the next several months, the faculty (notably Drs. Dabny and Wehrly and other members of the Undergraduate Committee) developed and submitted a completed proposal to the College of Science (February 2015). This proposal is now working its way through administrative channels, and it is expected that the program will begin in the fall semester of 2016. The undergraduate degree program will benefit the Department and University in numerous ways. First and most obviously, it will provide Texas A&M University undergraduates with an opportunity to obtain a highly marketable degree in arguably the most interesting of all fields of study. Studies that attest to the marketability of statistics degrees abound and are described more fully in Appendx C. For convenience we repeat here two typical conclusions cited in that appendix:

According to the National Center for Education Statistics (NCES) Digest of Education Statistics (DES), the number of Bachelor of Science degrees in statistics increased 40% from 2009 to 2011, 78% from 2003 to 2011, 26% from 2011 to 2012, and 20% from 2012 to 2013.

According to the Bureau of Labor Statistics, there were 24,950 workers classified as statisticians in 2013. This represents a 21% increase in the five years since 2008. The field was projected to grow by a further 27% (classified by BLS as “much faster than average”) during 2012 – 2022.

In terms of Vision 2020 imperatives, the addition of an undergraduate statistics program will enhance the undergraduate experience at Texas A&M University, and it will substantially strengthen the University’s science core. The addition of this major will also have numerous benefits for the department. As the number of majors in the program grows, additional faculty lines will be provided to the Department (one new faculty line per 50 undergraduate majors). The addition of the major will also provide faculty with greater opportunity to teach advanced undergraduate courses in statistics. A subset of these advanced undergraduate offerings will be made available to our distance- learning master’s students, which will provide them with more elective opportunities to satisfy their degree requirements. Finally, the addition of an undergraduate major will enhance the reputation of the Department both within and outside of the University. A major impediment that the Department faces in establishing the undergraduate degree is its lack of control over a large classroom. This prevents the department from teaching large service courses in one or two sections, instead requiring it to devote substantial resources to teach these courses in multiple smaller sections. As the Department develops its undergraduate major, access to large classrooms in which to teach service courses will be essential if the Department is to broaden its offering of more advanced undergraduate courses in statistics.

Graduate Program The Department is also striving to enhance the quality of its graduate program. Since the last Academic program review, the department has undergone two major reviews of the graduate program, with the second still underway. In 2008, the Department restructured its graduate program and separated the qualifying exams for MS students and Ph.D. students. Prior to 2008, MS students and Ph.D. students took the same courses during the first year in the graduate program and took the same qualifying exam in August of their second year. This arrangement delayed the progress of students who entered the program with strong background in statistics. To address this problem, a fast Ph.D. track was created to allow students with strong background to advance more rapidly to the completion of their degree. This structural change also played an important role in maintaining a distinction between doctoral and master’s level courses as enrollments in the distance-learning master’s program skyrocketed. The 2008 restructuring also established a core curriculum for the Ph.D. program that consisted of seven courses: Probability Theory (STAT 614), Asymptotic Statistics (STAT 620), Linear Models (STAT 612), Methodology I (STAT 613), Applied Statistics and Data Analysis (STAT648), Computational Statistics (STAT 605), and Methodology II: Bayesian Statistics (STAT 632). Students were required to take three qualifying exams from the first six courses listed in this core, with two courses forming the basis for each exam. That is, the Theory Exam covered material taken from STAT 614 and 620; the Methodology Exam covered material taken from STAT 612 and 613; and the Applied and Computational Exam covered material from STAT 648 and 605. Students who passed two of the three exams were advanced to Ph.D. candidacy. Students were given two chances to pass the qualifying exams. The 2008 restructuring of the graduate program alleviated a number of problems associated with the program, perhaps most importantly by creating a mix of classes that were appropriate for presentation to students at either the master’s or doctoral level. It also provided for a more rapid route for incoming students with strong backgrounds in mathematics or mathematical statistics to move beyond the qualifying exam and begin thesis research. The revised structure of the program did not resolve a number of other existing problems, however. As implemented, the program created a barrier that prevented students who had failed the doctoral exam from quickly completing a master’s degree. Part of this problem stemmed from the fact that the courses required for the doctoral degree were different from those required for the master’s degree. Students who failed the doctoral qualifying exam often needed to take additional courses to obtain a master’s degree, despite the large overlap in material covered in some master’s and doctoral courses, with material covered in the doctoral courses being taught at a higher level. In addition, separate qualifying exams were administered to doctoral and master’s students, and there was no mechanism for students who failed the Ph.D. qualifying exam to be given a pass on the master exam without sitting for the master’s exam at a later date. Finally, by requiring students to pass only two of three qualifying exams, and giving students the option to take the examination twice, many students did not pass (or fail) the qualifying exam until August of their third year in the program. Students who failed the exam in their third year were then provided with up to

four years of funding to complete a master’s degree. These problems have hindered the Department’s effort to meet Vision 2020 goals of graduating 75% of MS students in two years, and 50% of PhD students in five years. To address these problems, Dr. Jianhua Huang, Graduate Advisor, and other members of the Graduate Committee began another review of the graduate program in the summer of 2014. That review is ongoing, but changes made to the program as a result of this review currently include the following:

- The department’s course list was revised to clearly identify the levels at which statistics graduate courses are taught (MS versus PhD), with a stipulation that MS level courses do not satisfy certain PhD level course requirements. - Upon approval of the Associate Department Head, students in the master’s program are permitted to substitute PhD courses toward their degree requirements. - All students can take the PhD qualifying exam in lieu of the MS qualifying exam; outcomes of PhD qualifying exam were modified to include PhD pass, MS pass, fail, and pass at either level contingent on further course work. - All PhD students are required to take at least 5 PhD level electives. - All PhD students are required to take 2 credits of statistical consulting (STAT 684) - Core PhD courses are evaluated using the following criteria: o “A” represents PhD level work o “B” represents MS level work o “C” represents work not at graduate level - The written Ph.D. qualifying exam will be offered in May, two weeks after the spring semester final exams. - Course grades and exam grades are both considered in evaluating the outcome of the doctoral qualifying exam. - Students with strong incoming background can take the doctoral exam after first year of courses; all other students take the exam after their second year. The PhD qualifying examination can be taken only once. - Students must pass a Preliminary Examination administered by the student’s advisory committee within three semesters after passing the PhD qualifying exam. - The presentation of PhD dissertation research will be open to the public.

In addition to these changes to the program, the Department’s review of its graduate program is continuing, and additional changes are expected after faculty discussion during the spring and summer of 2015. Particular items on the agenda include the following:

- Strengthen international collaborations with universities to (a) improve the visibility of the department, (b) help recruit outstanding graduate students, and (c) gain leverage in funding graduate students. - Enhance and standardize the departmental student award system. Create new awards for outstanding course work and outstanding research. Standardize the procedures for providing support for students to travel to conferences and workshops. - Expand the number of specialization areas available to PhD students. The Department will consider more applied PhD tracts in areas like bioinformatics and computational methods for “big data.” The Department 17

will also explore the creation of dual degree programs with other programs, e.g., geosciences, astronomy, and the social sciences. - Revisit the list of courses that graduate students are required to take, and reconsider the emphasis given to various courses in the curriculum.

In the area of recruiting, the department is reviewing its recruitment procedures and redoubling its effort to attract top quality doctoral students. Beginning in the fall of 2014, graduate student stipends were increased by approximately 45% to $20,000 per academic year; this increase makes TAMU graduate student stipends commensurate with the stipends received by students at our peer institutions. The Department also streamlined its electronic application procedure and in late February of 2015 sponsored its first Graduate Student Visitation Day. All admitted applicants to the graduate program who were currently residing in the continental United States were provided funds to visit the department on February 27, 2015. During the visitation day, several faculty provided overviews of their research to the students, and the students were familiarized with the Department and campus. A reception was held that evening at the home Dr. Raymond Carroll. Nine of our top thirteen domestic candidates attended this event, and we expect to attract at least four of them to TAMU next fall. Graduate students in the department play a proactive role in departmental life. In 2009 the Statistics Graduate Student Association was formed. A brief description of SGSA activities is provided on page 54.

Professional Education

The Department of Statistics enrolled its first class into the Master of Science in Analytics program in the Fall of 2013. The program, which is jointly offered with the Mays Business School, offers business and statistics courses to strengthen the quantitative skills of professionals with strong backgrounds in the sciences, mathematics, and engineering fields. Students entering this program acquire quantitative skills applicable in a wide variety of business environments, including manufacturing, utilities, information technologies, healthcare, natural resource management, transportation, supply chain management, finance and insurance, and energy production. Through the efforts of the Academic Director for MS Analytics and Online Programs, Dr. Simon Sheather, the MS Analytics program obtained two large grants from SAS that facilitated the rapid growth of the program during its first two years. In the Fall of 2014 the program enrolled 28 students, and the Department anticipates that it will enroll as many as 40 students in the Fall of 2015. This represents remarkable growth in enrollments in a field that has become highly competitive over the last five or so years. The Department’s support of professional education is unique among science departments in the College and reflects the diverse range of employment opportunities that exist for undergraduate and graduate students who have training in statistical science. Further details regarding the program are provided in Appendix B.

Challenges and Opportunities

Figure 1.

Figure 1 illustrates the decline in faculty strength from 2006 to 2014. This decline has adversely affected the Department’s international reputation and rating, as well as its performance on key indicators in assessing progress toward Vision 2020 goals. Although three faculty losses since 2008 have been due to retirement, seven other prominent faculty members left the Department between 2006-2014 for other reasons (Dahl, Genton, Liang (on leave without pay; resigned spring 2015), Ma, Lahiri, Wang, West). These individuals were high performing, mid-career faculty members who generated numerous publications, citations and grant funding. It is important to note that the decline in the size of the Department’s faculty has occurred during a rapid expansion in the size of the University since 2006, and that the University will continue to grow as the College of Engineering expands to 25,000 students by the year 2025. 20

The genesis for these losses stem from multiple sources and vary from one faculty member to another, but common among them were salaries that were not competitive given their research productivity and external funding records. In at least three of the seven cases noted above, departing faculty received salary increases of greater than 40% when they left TAMU, and these salary increases were provided by non-peer institutions whose academic reputations are not comparable to Texas A&M University. To stem the further loss of our most productive research faculty, the salary “savings” accrued from the loss of one of the departing faculty members was used to provide equity increases to a number of the Department’s most productive remaining senior faculty members. These equity adjustments did, however, result in the loss of an additional faculty line within the Department, and salary inequities continue to be an issue for the Department. Furthermore, this issue is likely to become more severe as the Department attempts to make replacement hires for lost faculty. The starting salaries required to attract new assistant professors from leading doctoral programs now exceeds the salaries currently provided to the outstanding assistant professors that the department hired only two years ago. Indeed, starting salaries of new assistant professors will soon eclipse the salaries of our remaining associate professors, and it is likely that the Department failed to hire a highly recruited assistant professor candidate in Spring 2015 because it was unable to make a competitive salary offer. Ironically, the success of our faculty (particularly of our junior faculty) is likely to lead to additional attrition if the Department is unable to provide additional equity adjustments for its most productive members, particularly among our junior and mid-career faculty. The problem of retaining faculty is further exacerbated by the relative geographical isolation of Texas A&M University: Several of our most productive junior faculty have spouses that have been unable to find suitable employment in College Station and so instead currently work in Houston.

Assessment As noted above, the University has identified a number of key metrics for the evaluation of the Department. The values of metrics used in this assessment are compiled by Academic Analytics, and our performance on the metrics is judged against a group of peer institutions identified in Vision 2020. This peer group includes the following institutions:

• University of California at Berkeley2/15 • University of California at Los Angeles30/30 • University of Michigan12/15 • University of North Carolina12/20 • Georgia Institute of Technology (not included in Academic Analytics summaries of statistics departments) • University of California at San Diego • University of California at Davis27 • University of Illinois at Urbana-Champaign34 • University of Wisconsin12 • University of Florida30 • University of Washington3/7 • Pennsylvania State University20 • University of Texas at Austin • Ohio State University27 • University of Maryland • Purdue University24 • University of Minnesota20/24 • Indiana University • Michigan State University47

Superscripts in this list denote the 2014 US News and World Report rankings of statistics/biostatistics departments. The Department of Statistics at Texas A&M University ranked 15th (out of 86 programs evaluated).

Figure 2 provides a summary of the Department’s performance on a variety of academic metrics (plot generated by Academic Analytics). This plot is based on a comparison with 18 other statistics departments at research universities granting doctoral degrees. As this figure demonstrates, the Texas A&M University Department of Statistics excels in essentially all areas of faculty evaluation within this broad comparison group.

Figure 2.

Unfortunately, concerns over propriety of data preclude the display of similar diagnostics within our Vision 2020 peer group. For this reason, data from Academic Analytics reports has been redacted and displayed in Table 1, which lists the Department’s ranking among our 18 peer institutions on key indicators of productivity. Note that University of Florida (AG), which contains only one faculty member, has been excluded from the rankings (though their main statistics department is included) and that Georgia Tech does not have a statistics department. These rankings are based on publications, citations and grant information collected from 2010-2013.

Table 1.

Metric Ranking among 18 peer institutions Number of faculty with journal publication 4 Journal publications per faculty member 9 Percentage of faculty with journal publication 14 Total journal publications 4 Citations per faculty member 9 Number of faculty with citation 3 Percentage of faculty with citation 13 Total citations 6 Grant dollars per faculty member 8 Grants per faculty member 14 Total grant dollars 8 Total number of grants 7 Awards per faculty member 5 Number of faculty members with awards 2 Percentage of faculty with Award 4 Total awards 2

There are two general trends apparent from Table 1. First, the Department, as a whole, typically ranks in the top half, and for many metrics in the top quarter, of our Vision 2020 peers. Second, the Department is less successful on several key metrics that involve the percentages of faculty achieving the outcomes associated with these metrics. This feature of the rankings can be attributed to a small proportion of our faculty that has not been research active in recent years. The department is currently working to address this problem and has recently adopted bylaws that impose minimum publication standards for faculty to maintain in order to avoid unsatisfactory ratings in annual and post-tenure reviews (see Appendix J.).

Despite limitations that the Department’s salary structure imposes on retaining and recruiting quality faculty, as well as the decline in the size of the faculty, the Department is poised to make significant improvements to its undergraduate and graduate programs. The addition of new faculty lines stemming from the anticipated success of the undergraduate major in statistics is likely to provide funding for 3-4 additional faculty lines. Changes to the graduate program will help the Department recruit better graduate students, and will decrease the average time required for students to complete their graduate studies. The Department extracts great benefit from its distance learning programs. These programs enhance the reputation of the Department and provide critical revenue to support graduate students, senior lecturers, on-campus research workshops, and student and faculty travel to scientific conferences. With only a moderate increase in institutional support, it is likely that the Department could achieve a top 10 national ranking, among both public and private universities, in most external evaluations of academic programs. Key resources required by the department include the following: i) One 250+ seat classroom dedicated to the Department for service teaching. As indicated above, the department is not able to teach its service courses in large classroom settings. This restricts the number of students that can be enrolled in these courses, as well as the number of courses that the department is able to offer. ii) An increase in-state graduate course fees from $69/credit hour to $150/credit hour. This will allow the department to expand its distance learning master’s program to in-state students. iii) Reimbursement for graduate course fees for students exempted by the Hazelwood Act. The department has not actively recruited active duty military into the distance learning program because doing so would result in a significant increase in program costs without offsetting revenue. iv) Equity increases for the Department’s most highly productive junior and mid-career level researchers. v) Reinstatement of teaching fees to replace IEEF funds. The Department’s IEEF and IEEF- replacement funds for FY13, FY14, and FY15 were $485,010, $436,811, and $388,523, respectively (please refer to Figure 3). This consistent reduction in teaching support has resulted in the loss of a senior lecturer and has further denigrated the Department’s ability to provide service teaching.

Figure 3.

IEEF & IEEF Replacement Funds

IEEF Funds

$485,010 $436,811 $388,523

Fiscal Year 2013 Fiscal Year 2014 Fiscal Year 2015

II. Student Report

Graduate Program in Statistics

The Department of Statistics offers a graduate program, leading to the degrees of Master of Science and Doctor of Philosophy. The Department also jointly sponsors graduate work with all subject matter area departments in setting up flexible minor programs in statistics. The Department of Statistics offers two options in its master's degree programs: (1) the Master of Science degree (thesis option) which requires the preparation of a thesis and (2) the Master of Science (non-thesis option) which requires more formal course work in lieu of the thesis. Within either option, students are allowed to choose either a broad-based or specialized program of study. All choices, however, provide a balanced training in statistical methods, computational statistics, and statistical theory, and are intended to prepare the student to adapt statistical methodologies to practical problems. The aim of the Ph.D. program is to provide comprehensive and balanced training in statistical methods, computational statistics, and the theory of statistics. Particular emphasis is placed on training students to independently recognize the relevance of statistical methods to the solution of specific problems and to enable them to develop new methods when they are needed. The training aims to convey a sound knowledge of existing statistical theory, including the mathematical facility to develop new results in statistical methodology. At the same time, the program is kept sufficiently flexible to permit students to develop their specific interests.

Master of Science Program

Non-Thesis Option

A student seeking the Master of Science degree under the Non-Thesis Option must fulfill the following requirements:

A. Coursework. Note that STAT 601, 651, 652, and 658 may not be used to fulfill any of the coursework requirements listed below.

1) STAT 604, 608, 641 and 642. 2) One credit hour of STAT 681. 3) Two semester credit hours of statistical consulting experience (STAT 684) earned in a minimum of two semesters. Rules governing completing this requirement are given below in Item B. 4) Three semester credit hours of STAT 685 for the preparation of a special problem (see item C below). 5) Eighteen semester credit hours based on one of the emphasis areas outlined below. 6) A total of 36 semester credit hours.

Broad-Based Plan 1) STAT 610, 611 2) Four additional courses from the MS elective courses list.

Biostatistics Emphasis 1) STAT 610, 611, 645 and 646 2) Two additional courses from the MS elective courses list.

Computational Emphasis 1) STAT 610 and 611 2) Two courses in Mathematics (e.g., MATH 609, MATH 610 or MATH 660). 3) Two courses in Computer Science (e.g., CPSC 603, CPSC 654 or CPSC 659).

Applied Emphasis 1) STAT 630, 657 2) Four additional courses from the MS elective courses list.

MS Elective Courses: STAT 607, 626, 636, 638, 645, 646, 647, 656, 657, 659

B. Substitution of STAT Ph.D. Courses for MS Coursework. With the approval of the Graduate Advisor and/or Associate Department Head, STAT Ph.D. courses can be used as substitutes for any of the MS courses listed in part A.

C. Consulting Experience. One semester credit hour of STAT 684 can be obtained through the completion of any of the experiences listed below.

1) One semester of service in the Statistical Consulting Center. 2) One semester of a departmentally approved internship.

3) Special experiences, with prior approval from the Department Head or the Associate Department Head that involves the following: a. At least one semester of activity b. The application of statistical knowledge c. Working with non-statisticians d. Sufficient statistical supervision.

D. Form a master's advisory committee and complete a special project under the direction of the chairman of the advisory committee. Three semester credit hours of STAT 685 are earned by completion of this project. Upon completion, the student is required to compose a written report and make an oral presentation on the work. The purpose of this project is to familiarize the student with the type of problems that may be encountered in future work and to give the student a chance to develop the ability to present results both verbally and in writing. In many cases, work done during an internship may be used as the basis for the student's master's project. However, this project must be completed under the supervision of the chairperson of the student's advisory committee.

E. Pass the departmental MS examination (see below).

F. Pass a final oral examination. This examination is concerned with the student's coursework and special problem. It is administered by the student's advisory committee.

Thesis Option

A student seeking the Master of Science degree under the Thesis Option must fulfill the following requirements:

A. Coursework. Note that STAT 601, 651, 652, and 658 may not be used to fulfill any of the coursework requirements listed below.

1) STAT 604, 608, 610, 611, 641 and 642. 2) One credit hour of STAT 681. 3) Six semester credit hours of STAT 691 for preparation of a thesis (see item B below). 4) Nine semester credit hours based on one of the emphasis areas outlined below. STAT 691 semester credit hours may not be used to satisfy this requirement. 5) A total of 34 semester credit hours.

Broad-Based Plan 1) Three additional courses from the MS elective courses list.

Biostatistics Emphasis 1) STAT 643 and 644 2) One additional courses from the MS elective courses list.

Computational Emphasis 1) At least one course in Mathematics (e.g., MATH 609, MATH 610 or MATH 660). 2) At least one course in Computer Science (e.g., CPSC 603, CPSC 654 or CPSC 659).

C. Form an advisory committee and complete a thesis under the direction of the chairman of the advisory committee. The Department does not insist that this represent an original contribution to the field of statistics. It is intended to train the student in carrying out independently a piece of research; this may represent an application of existing statistical methods in a new area or a comparative evaluation of statistical methods.

D. Pass the departmental MS examination (see below).

E. Pass a final oral examination. This examination is concerned with the student's coursework and thesis. It is administered by the student's advisory committee.

Master's Diagnostic Examination

The MS examination covers basic statistical methods. The examination is evaluated with the performance judged to be “Pass” or “Fail.” To receive a Master's Degree, a student must take and pass the exam. The diagnostic exam is offered twice a year--prior to the beginning of the fall semester and prior to the beginning of the spring semester, and must be taken at the earliest possible time after the student has completed the required courses: STAT 610, 611 (or 630), 604, 608, 641, and 642. Any exception to this time limit must be obtained in writing from the head of the Department. The results of a student's examination are reported to the faculty of the Statistics Department. If the student's performance is judged to be deficient, the examination may be retaken the next time it is offered. Only one retake of the examination is allowed. The Ph.D. Qualifying Examination can be taken as a substitution for the Master’s Diagnostic Examination. A student must receive a Pass at the MS level or a Pass at the Ph.D. level on the Ph.D. Qualifying Examination in order for the results from the Ph.D. Exam to qualify as a Pass on the MS Exam.

Doctor of Philosophy Program

The breadth of the field of statistics as well as the frontiers of knowledge in a particular research area are emphasized in the Ph.D. program. The student seeking a Ph.D. in statistics is required to fulfill the following requirements. A Ph.D. selection committee will examine the background of entering students to determine if they have the appropriate mathematics/statistics background to successfully complete the program. Those students determined to not have the appropriate background will need to complete some courses in the MS STAT program and/or courses in mathematics.

A. Courses

1) Required Courses – STAT 605, 612, 613, 614, 620, 632, 648 2) At least five courses from the elective course list provided below. 3) Two semester credit hours of statistical consulting experience (STAT 684) earned in a minimum of two semesters. Rules governing acceptable methods for completing this requirement are given below in Item B. 4) Four semester credit hours of STAT 681. 5) A sufficient number of research hours, STAT 691, or additional courses from the Ph.D. Elective Course list or M.S. Elective Courses to achieve a total of at least 96 semester credit hours beyond a Bachelor's degree or 64 semester credit hours beyond a Master's degree.

Ph.D. Elective Courses: STAT - 615, 616, 618, 621, 627, 631, 633, 642, 643, 644, 647, 665, 673, 674, 689

B. Consulting Experience. One semester credit hour of STAT 684 can be obtained through the completion of any of the experiences listed below.

1) One semester of service in the Statistical Consulting Center. 2) One semester of a departmentally approved Internship. 3) Special experiences, with prior approval from either the Department Head or the Associate Department Head that involve the following: a. At least one semester of activity b. The application of statistical knowledge c. Working with non-statisticians d. Sufficient statistical supervision.

C. Ph.D. Qualifying Examination. The Ph.D. Qualifying Exam will cover the material from the required courses: STAT 614, 620, 612, 613, 605, 648. The student’s performance on the Ph.D. Qualifying Exam combined with the student’s performance in the required courses will then be evaluated as

1) Pass at the Ph.D. level 2) Pass at the Ph.D. level conditional on retaking specified courses 3) Pass at the M.S. level with no option to retake the Ph.D. exam 4) Fail the exam with no option to retake the Ph.D. exam.

The exams will be offered in May every year approximately two weeks after the spring semester final exams. There are two schedules for a student to take the Ph.D. qualifying exam.

Schedule I: Exam is taken in May of the first academic year student is enrolled in the Ph.D. program.

Schedule II: Exam is taken in May of the second academic year that student is enrolled in the Ph.D. program. This schedule is for students that are taking background courses in statistics or mathematics prior to taking the required Ph.D. courses. A student using Schedule II will be evaluated at the end of their second and third semesters in the Ph.D. program regarding whether they will be allowed to continue in the Ph.D. program. Any student who has not taken the Ph.D. exam within two years of their entering the program will automatically be disqualified from the Ph.D. program.

D. Ph.D. Advisory Committee. After passing the Ph.D. qualifying exam, a student must select a faculty member of the Department of Statistics to be the student’s Ph.D. advisor and to direct the student’s research. The student and the selected faculty member should work together to form a Ph.D. advisory committee consisting of two more members from the statistics faculty and a faculty member outside of the department of statistics. A degree plan must be submitted using the electronic degree plan at the OGAPS website. The degree plan will include all required courses, five courses from the Elective Courses list, and sufficient hours to meet OGAPS requirements as listed above.

E. Take and pass the Preliminary Examination administered by the advisory committee within three semesters after passing the Ph.D. qualifying exam (see below).

F. Write a Ph.D. Dissertation and pass the final Defense of Dissertation Examination (see below). The presentation of student’s research in their dissertation defense will be open to the public.

Preliminary Examination

After a student has passed the departmental Ph.D. qualifying examination, formed an advisory committee, submitted a degree plan and has it approved by OGAPS, a student must take the OGAPS required preliminary examination. The prelim exam consists of the following parts:

1) A written examination developed by the statistics members of the student’s advisory committee. This exam is usually waived at the discretion of the departmental committee members. 2) A written examination administered by the member of the student’s advisory committee from outside the Statistics Department. This examination is usually waived. 3) An oral examination administered by the members of the student’s advisory committee. The oral exam generally consists of the student presenting a proposal for the student’s Ph.D. dissertation research and discussing any research results completed at the point of the exam.

Scheduling the preliminary examination can only take place after the student has an approved Ph.D. degree plan on file with OGAPS. The student must successfully pass the preliminary examination within three semesters after passing the Ph.D. qualifying exam and at least 14 weeks prior to the date of the dissertation defense. The results of the examination are reported to OGAPS using the Report of the Preliminary Examination, a form found at the OGAPS website.

The Ph.D. Dissertation

After successfully completing all the required courses and passing the Ph.D. Qualifying Exam, a period of time is to be devoted to formulating a research topic in either statistical methodology or statistical theory under the guidance of the student's dissertation advisor. The proposed research will be presented to the student’s advisory committee during the Preliminary Exam in order to obtain the committees input on the appropriateness of the research. The results of this research must be communicated in a written dissertation satisfying the guidelines established by OGAPS. The research must constitute an original contribution to the science of statistics and may derive new results in statistical theory or methodology or may be concerned with developing statistical methodology in new areas of application.

Once the student's advisory committee feels that the student has completed the dissertation, a final oral examination is conducted by the advisory committee in which the student defends the dissertation. This exam must be scheduled by submitting the Request and Announcement of the Final Examination form to OGAPS at least 10 working days before the final exam date.

Internship Program

Students after one year of coursework are eligible to participate in an internship with a sponsoring company, hospital, or federal agency. The internships are generally a semester's stay at the sponsor's site. If a student participates in one of the internship programs approved by the department head, then the student is given credit for one hour of STAT 684. In many cases, work done during the internship may be used as the basis for a Master’s project. However, this project must be completed under the supervision of the chairperson of the student’s advisory committee.

Undergraduate Course Offerings

201. Elementary Statistical Inference. (3-0). Credit 3. Data collection, tabulation, and presentation. Elementary description of the tools of statistical inference; probability, sampling, and hypothesis testing. Applications of statistical techniques to practical problems. May not be taken for credit after or concurrently any other course in statistics or INFO 303 has been taken.

211. Principles of Statistics I. (3-0). Credit 3. Introduction to probability and probability distributions. Sampling and descriptive measures. Inference and hypothesis testing. Linear regression, analysis of variance. Prerequisite: MATH 152 or 172.

212. Principles of Statistics II. (3-0). Credit 3. Design of experiments, model building, multiple regression, nonparametric techniques, contingency tables, and short introductions to response surfaces, decision theory and time series data. Prerequisite: STAT 211.

301. Introduction to Biometry. (3-0). Credit 3. Intended for students in animal sciences. Introduces fundamental concepts of biometry including measures of location and variation, probability, tests of significance, regression, correlation, and analysis of variance which are used in advanced courses and are being widely applied to animal- oriented industry. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

302. Statistical Methods. (3-0). Credit 3. Intended for undergraduate students in the biological sciences and agriculture (except agricultural economics). Introduction to concepts of random sampling and statistical inference; estimation and testing hypotheses of means and variances; analysis of variance; regression analysis; contingency tables. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

303. Statistical Methods. (3-0). Credit 3. Intended for undergraduate students in the social sciences. Introduction to concepts of random sampling and statistical inference, estimation and testing hypotheses of means and variances, analysis of variance, regression analysis, contingency tables. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.

307. Sample Survey Techniques. (3-0). Credit 3. Concepts of population and sample; the organization of a sample survey; questionnaire design. Basic survey designs and computation of estimates and variances. Prerequisites: STAT 301, 302, 303, or INFO 303.

407. Principles of Sample Surveys. (3-0). Credit 3. Principles of sample surveys and survey design; techniques for variance reduction; simple, stratified and multi-stage sampling; ratio and regression estimates; post-stratification; equal and unequal probability sample. Prerequisite: STAT 212.

408. Introduction to Linear Models. (3-0). Credit 3. Introduction to the formulation of linear models and the estimation of the parameters of such models, with primary emphasis on least squares. Application to multiple regression and curve fitting. Prerequisites: MATH 304; STAT 212.

414. Mathematical Statistics. (3-0). Credit 3. Introduction to the mathematical theory of statistics, including random variables and their distributions, expectation and variance, point estimation, confidence intervals and hypothesis testing. Prerequisite: MATH 221, 251 or 253.

485. Problems. Credit 1 to 6. Special problems in statistics not covered by another course in the curriculum. Work may be in either theory or methodology. Prerequisite: Approval of instructor. 36

Graduate Course Offerings

601. Statistical Analysis. (3-2). Credit 4. For students in engineering, physical, and mathematical sciences. Introduction to probability, probability distributions, and statistical inference; hypotheses testing; introduction to methods of analysis such as tests of independence, regression, analysis of variance with some consideration of planned experimentation. Prerequisite: MATH 152 or 172.

604. Topics in Statistical Computations. (3-0). Credit 3. Efficient uses of existing statistical computer programs (SAS, R, etc.), generation of random numbers; using and creating functions and subroutines; statistical graphics; programming of simulations studies; and data management issues. Prerequisites: MATH 221, 251, or 253.

605. Advanced Statistical Computations. (3-0). Credit 3. Programming languages, statistical software, and computing environments; development of programming skills using modern methodologies; data extraction and code management; interfacing lower-level languages with data analysis software; simulation; MC integration; MC- MC procedures; permutation tests; bootstrapping. Prerequisite: STAT 612 and STAT 648.

607. Sampling. (3-0). Credit 3. Planning, execution and analysis of sampling from finite populations; simple, stratified, multistage and systematic sampling; ratio estimates. Prerequisite: STAT 601 or 652 or concurrent enrollment in STAT 641.

608. Regression Analysis. (3-0). Credit 3. Multiple, curvilinear, nonlinear, robust, logistic and principal components regression analysis; regression diagnostics, transformations, analysis of covariance. Prerequisite: STAT 601 or 641.

610. Theory of Statistics - Distribution Theory. (3-0). Credit 3. Brief introduction to probability theory; distributions and expectations of random variables, transformations of random variables, and order statistics; generating functions and basic limit concepts. Prerequisite: MATH 409 or concurrent enrollment in MATH 409.

611. Theory of Statistics - Inference. (3-0). Credit 3. Theory of estimation and hypothesis testing; point estimation, interval estimation, sufficient statistics, decision theory, most powerful tests, likelihood ratio tests, chi-square tests. Prerequisite: STAT 610 or equivalent.

612. Theory of Linear Models. (3-0). Credit 3. Matrix algebra for statisticians, Gauss-Markov theorem; estimability; estimation subject to linear restrictions; multivariate normal distribution; distribution of quadratic forms; inferences for linear models; theory of multiple regression and AOV; random- and mixed-effects models. Prerequisite: Course in linear algebra.

613. Statistical Methodology I. (3-0). Credit 3. Elements of likelihood inference; exponential family models; group transformation models; survival data; missing data; estimation and hypothesis testing; nonlinear regression models; conditional and marginal inferences; complex models-Markov chains, Markov random fields, time series, and point processes. Prerequisite: STAT 612.

614. Probability for Statistics. (3-0). Credit 3. Probability and measures; expectation and integrals, Kolmogorov's extension theorem; Fubini's theorem; inequalities; uniform integrability; conditional expectation; laws of large numbers; central limit theorems. Prerequisite: STAT 610 or its equivalent.

615. Stochastic Processes. (3-0). Credit 3. Survey of the theory of Poisson processes, discrete and continuous time Markov chains, renewal processes, birth and death processes, diffusion processes, and covariance stationary processes. Prerequisites: STAT 611; MATH 409.

616. Statistical Aspects of Machine Learning I: Classical Multivariate Methods. (3-0). Credit 3. Core methods from traditional multivariate analysis and various extensions. Probability distributions of random vectors and matrices, multivariate normal distributions, model assessment and selection in multiple regression, multivariate regression, dimension reduction, linear discriminant analysis, logistic discriminant analysis, cluster analysis, multidimensional scaling and distance geometry, and correspondence analysis Prerequisites: STAT 611 and 612.

618. Statistical Aspects of Machine Learning II: Modern Techniques. (3-0). Credit 3. Second course in statistical machine learning. Recursive partition and tree-based methods, artificial neural networks, support vector machines, reproducing kernels, committee machines, latent variable methods, component analysis, nonlinear dimensionality reduction and manifold learning, matrix factorization and matrix completion, statistical analysis of tensors and multi-indexed data. Prerequisites: STAT 610, 611, and 613.

620. Asymptotic Statistics. (3-0). Credit 3. Review of basic concepts and important convergence theorems; elements of decision theory; delta method; Bahadur representation theorem; asymptotic distribution of MLE and the LRT statistics; asymptotic efficiency; limit theory for U-statistics and differential statistical functionals with illustration from M-,L-,R-estimation; multiple testing. Prerequisite: STAT 614.

621. Advanced Stochastic Processes. (3-0). Credit 3. Conditional expectation; stopping times; discrete Markov processes; birth-death processes; queuing models; discrete semi-Markov processes; Brownian motion; diffusion processes, Ito integrals, theorem and limit distributions; differential statistical functions and their limit distributions; M-,L-,R-estimation. Prerequisite: STAT 614 or STAT 615.

623. Statistical Methods for Chemistry. (3-0). Credit 3. Chemometrics topics of process optimization, precision and accuracy; curve fitting; chi-squared tests; multivariate calibration; errors in calibration standards; statistics of instrumentation. Prerequisites: STAT 601 or STAT 652 or STAT 641 or approval of instructor.

626. Methods in Time Series Analysis. (3-0). Credit 3. Introduction to statistical time series analysis; autocorrelation and spectral characteristics of univariate, autoregressive, moving average models; identification, estimation and forecasting. Prerequisite: STAT 601 or 642 or approval of instructor.

627. Nonparametric Function Estimation. (3-0). Credit 3. Nonparametric function estimation; kernel, local polynomials, Fourier series and spline methods; automated smoothing methods including cross-validation; large sample distributional properties of estimators; recent advances in function estimation. Prerequisites: STAT 611.

630. Overview of Mathematical Statistics. (3-0). Credit 3. Basic probability theory including distributions of random variables and expectations. Introduction to the theory of statistical inference from the likelihood point of view including maximum likelihood estimation, confidence intervals, and likelihood ratio tests. Introduction to Bayesian methods. Prerequisites: Math 221, 251, or 253.

631. Statistical Methods in Finance. (3-0). Credit 3. Regression and the capital asset pricing model, statistics for portfolio analysis, resampling, time series models, volatility models, option pricing and Monte Carlo methods, copulas, extreme value theory, value at risk, spline smoothing of term structure. Prerequisites: STAT 610, 611, 608.

632. Statistical Methodology II-Bayesian Modeling and Inference. (3-0). Credit 3. Decision theory; fundamentals of Bayesian inference; single and multi-parameter models, Gaussian model; linear and generalized linear models; Bayesian computation; asymptotic methods; non-interative MC; MCMC; hierarchical models; nonlinear models; random effect models; survival analysis; spatial models. Prerequisite: STAT 613.

633. Advanced Bayesian Modeling and Computation. (3-0). Credit 3. Bayesian methodology, and applications of Bayesian methods in bioinformatics, biostatistics, signal processing, machine learning, and related fields. Prerequisite: STAT 608, 613, 632.

636. Applied Multivariate Analysis. (3-0). Credit 3. Multivariate extensions of the chi-square and t-tests, discrimination and classification procedures; applications to diagnostic problems in biological, medical, anthropological, and social research; multivariate analysis of variance, principal component and factor analysis, canonical correlations. Prerequisites: MATH 423 and STAT 653 or approval of instructor. Cross-listed with INFO 657.

638. Introduction to Applied Bayesian Methods. (3-0). Credit 3. Students will learn how uncertainty regarding parameters can be explicitly described as a posterior distribution which blends information from a sampling model and prior distribution Course will emphasize modeling and computations under the Bayesian paradigm. Topics include: prior distributions, Bayes Theorem, conjugate and non-conjugate models, posterior simulation via the Gibbs sampler and MCMC, hierarchical modeling. Prerequisite: STAT 604, 608, or 630.

641. The Methods of Statistics I. (3-0). Credit 3. An application of the various disciplines in statistics to data analysis, introduction to statistical software; demonstration of interplay between probability models and statistical inference. Prerequisites: Concurrent Enrollment in STAT 610 or approval of instructor.

642. The Methods of Statistics II (3-0). Credit 3. Design and analysis of experiments; scientific method; graphical displays; analysis of nonconventional designs and experiments involving categorical data. Prerequisites: STAT 641.

643. Biostatistics I. (3-0). Credit 3. Bio-assay for quantitative and quantal responses; statistical analysis of contingency, including effect estimates, matched samples and misclassification. Prerequisites: STAT 608, 630, and 642 or STAT 610.

644. Biostatistics II. (3-0). Credit 3. Generalized linear models; survival analysis with emphasis on nonparametric models and methods. Prerequisites: STAT 643 or approval of instructor.

645. Applied Biostatistics and Data Analysis. (3-0). Credit 3. Survey of crucial topics in biostatistics; application of regression in biostatistics; analysis of correlated data; logistic and Poisson regression for binary or count data; survival analysis for censored outcomes; design and analysis of clinical trials; sample size calculation bysimulation; bootstrap techniques for assessing statistical significance; data analysis using R. Prerequisites: STAT 651, 652, and 659, or equivalent or prior approval of instructor.

646. Statistical Bioinformatics. (3-0). Credit 3. An overview of relevant biological concepts and technologies of genomic/proteomic applications; methods to handle, visualize, analyze, and interpret genomic/proteomic data; exploratory data analysis for genomic/ proteomic data; data preprocessing and normalization; hypotheses testing; classification and prediction techniques for using genomic/ proteomic data to predict disease status. Prerequisites: STAT 604, 651, 652 or equivalent or prior approval of instructor.

647. Spatial Statistics. (3-0). Credit 3. Spatial correlation and its effects; spatial prediction (kriging); spatial regression; analysis of point patterns (tests for randomness and modelling patterns); sub sampling methods for spatial data. Prerequisite: STAT 601 or STAT 611 or equivalent.

648. Applied Statistics and Data Analysis. (3-0). Credit 3. Background to conduct research in the development of new methodology in applied statistics. Topics covered will include: exploratory data analysis; sampling; testing; smoothing; classification; time series; and spatial data analysis. Prerequisite: Approval of instructor.

651. Statistics in Research I. (3-0). Credit 3. For graduate students in other disciplines; non-calculus exposition of the concepts, methods and usage of statistical data analysis; T-tests, analysis of variance, and linear regression. Prerequisite: MATH 102 or equivalent.

652. Statistics in Research II. (3-0). Credit 3. Continuation of STAT 651. Concepts of experimental design, individual treatment comparisons, randomized blocks and factorial experiments, multiple regression, chi-square tests and a brief introduction to covariance, non-parametric methods, and sample surveys. Prerequisite: STAT 651.

653. Statistics in Research III. (3-0). Credit 3. Advanced topics in ANOVA; analysis of covariance; and regression analysis including analysis of messy data; non-linear regression; logistic and weighted regression, diagnostics and model building; emphasis on concepts, computing and interpretation. Prerequisite: STAT 652.

656. Applied Analytics Using SAS Enterprise Miner. (3-0) Credit 3. Introduction to data mining and will demonstrate the procedures; Optimal prediction decisions; comparing and deploying predictive models; neural networks; constructing and adjusting tree models; the construction and evaluation of multi-stage models. Prerequisite: STAT 657.

657. Advanced Programming Using SAS. (3-0). Credit 3. Programming with SAS/IML, programming in SAS data step, advanced use of various SAS procedures. Prerequisites: STAT 604, 642.

658. Transportation Statistics. (3-0). Credit 3. Design of experiments, estimation, hypotheses testing, modeling, and data mining for transportation specialists. Prerequisites: STAT 211 or STAT 651.

659. Applied Categorical Data Analysis. (3-0). Credit 3. Introduction to analysis and interpretation of categorical data using ANOVA/regression analogs; includes contingency tables, loglinear models, logistic regression; use of computer software such as SAS, GLIM, SPSSX. Prerequisite: STAT 601 or 641 or 652 or equivalent.

661. Statistical Genetics. (3-0), Credit 3. Basic concepts in human genetics, sampling designs, gene frequency estimation, Hardy-Weinberg equilibrium, linkage disequilibrium, association and transmission disequilibrium test studies, linkage and pedigree analysis, segregation analysis, polygenic models, DNA sequence analysis. Prerequisites: STAT 610 and 611.

662. Advanced Statistical Genetics. (3-0). Credit 3. This course is a continuation of the course, STAT 661 Statistical Genetics. A strong background in statistics, genetics, and mathematics is required. Topics include counting methods, EM algorithm, Newton's method, scoring in genetics, genetic identity coefficients, descent graph, molecular phylogeny, models of recombination, sequence analysis, diffusion processes and linkage disequilibrium mappings. Prerequisite: STAT 610, 611, and 661.

665. Statistical Application of Wavelets. (3-0). Credit 3. This is a course on the use of wavelets methods in statistics. The course introduces wavelet theory, provides an overview of wavelet-based statistical methods. Topics include smoothing of noisy signals, estimation function data and representation of stochastic processes. Some emphasis is given to Bayesian procedures. Prerequisite: STAT 611 or approval by the instructor.

673. Time Series Analysis I. (3-0). Credit 3. An introduction to diverse modes of analysis now available to solve for univariate time series; basic problems of parameter estimation, spectral analysis, forecasting and model identification. Prerequisite: STAT 611 or equivalent.

674. Time Series Analysis II. (3-0). Credit 3. Continuation of STAT 673. Multiple time series, ARMA models, test of hypotheses, estimation of spectral density matrix, transfer function and forecasting. Prerequisites: STAT 673. 40

681. Seminar. Credit 1. Oral presentations of special topics and current research in statistics. May be repeated for credit. Prerequisite: Graduate classification in statistics.

684. Professional Internship. Credit 1 to 3. Practicum in statistical consulting for students in Ph.D. program. Students will be assigned consulting problems brought to the Department of Statistics by researchers in other disciplines. Prerequisite: STAT 642 or equivalent.

685. Directed Studies. Credit 1 to 6. Individual instruction in selected fields in statistics; investigation of special topics not within scope of thesis research and not covered by other formal courses. Prerequisites: Graduate classification and approval of department head.

689. Special Topics in Statistics. Credit 1 to 4. Selected topics in an identified area of statistics. Open to non- majors. May be repeated for credit. Prerequisite: Approval of instructor.

691. Research. Credit 1 or more. Research for thesis or dissertation. Prerequisite: Graduate classification.

Scheduling Coursework

The following list indicates the Department's usual schedule of course offerings. Those courses marked even or odd are offered only in even numbered and odd numbered years, respectively. Because several courses are offered only every other year, it is important to plan a program of study and schedule of courses as early as possible.

Course Semester(s) Course Semester(s) Offered Offered 201 1,2 631 1 (even) 211 1,2,3 632 1 212 1,2 633 2 301 1,2 636 1 302 1,2,3 638 1 303 1,2,3 641 1 307 2 642 2 407 1 643 4 408 2 644 4 414 1 645 1 485 1,2,3 646 2 601 1 647 1 604 1,2,3 648 1 605 2 651 1,2,3 607 1 652 1,2,3 608 2,3 653 2 610 1 656 2 611 2 657 2 612 1 658 4 613 2 659 2,3 614 1 661 4 615 1 (odd) 662 4 616 1 665 4 618 2 673 1 (even) 620 2 674 2 (odd) 621 2 (even) 681 1,2 623 4 684 1,2,3 626 3 685 1,2,3 627 2 (odd) 689 4 630 1,2,3 691 1,2,3

1: Fall, 2: Spring, 3: Summer, 4: As resources allow.

Graduate Program Admissions Criteria

Admissions criteria for the Graduate Program in the Department of Statistics are based on the following requirements:

o GRE Scores o Transcripts o Resume o 3 Letters of Recommendation o Knowledge of Matrix Algebra, along with courses in Calculus I and II, as well as computer programming

Applicants with a strong background in mathematics, statistics, and computer programming are preferred.

GRE Scores for First Time Graduate Students

Major Semester Student Average Average Minimum Minimum Maximum Maximum Year Headcount GRE New GRE GRE New GRE GRE New GRE STAT Spring 2008 13 1249 1000 1370 STAT Summer 2008 5 1176 1080 1360 STAT Fall 2008 59 1251 780 1460 STAT Spring 2009 39 1291 950 1530 STAT Summer 2009 34 1270 1040 1440 STAT Fall 2009 83 1246 550 1530 STAT Spring 2010 27 1354 1070 1510 STAT Summer 2010 26 1288 1090 1500 STAT Fall 2010 81 1300 1010 1500 STAT Spring 2011 35 1276 970 1490 STAT Summer 2011 41 1368 1180 1540 STAT Fall 2011 109 1334 1060 1570 STAT Spring 2012 28 319 1193 299 1120 334 1240 STAT Summer 2012 35 318 1337 305 1190 330 1450 STAT Fall 2012 93 317 1364 298 1170 335 1500 STAT Spring 2013 25 320 1400 312 1390 327 1430 STAT Summer 2013 27 317 1262 301 1100 332 1420 STAT Fall 2013 62 321 1297 301 1100 334 1530

Graduate Students Applied, Admitted and Enrolled 2007-2009

Applied Admitted Enrolled

Year Ethnicity Gender Masters Doctoral Masters Doctoral Masters Doctoral Asian Only Female 1 1 1 Male 2 1 1 1 1 Black Only Male 1 1 Black only + Multi- Male 1 racial w/Black Hispanic or Latino of Male 1 1 1 2007 any Race International Female 27 21 8 8 5 5 Male 22 36 6 9 5 4 Unknown or Not Male 1 1 1 Reported White Only Female 10 10 9 Male 14 2 14 2 12 1 2007 Total 79 60 43 20 35 11 Asian Only Female 4 3 Male 8 1 6 4 Black Only Female 1 1 Hispanic or Latino of Female 1 1 1 any Race Male 2 2 2 2008 International Female 18 26 1 8 2 6 Male 28 27 3 5 2 2 Unknown or Not Male 1 1 Reported White Only Female 14 2 14 2 13 2 Male 30 2 30 1 24 1 2008 Total 106 59 61 17 47 12 American Indian Only Female 2 2 1 Male 1 1 Asian Only Female 6 2 6 1 3 Male 6 1 6 1 1 Black Only Female 7 7 Male 5 5 Black only + Multi- Female 6 racial w/Black Male 1 2009 Hispanic or Latino of Female 1 1 1 1 1 any Race Male 6 6 1 International Female 6 5 6 5 3 5 Male 14 15 12 15 4 10 Unknown or Not Female 2 2 1 Reported Male 2 2 3 White Only Female 31 30 14 Male 47 3 47 3 26 3 2009 Total 136 27 133 26 64 19

Graduate Students Applied, Admitted and Enrolled 2010-2011

Applied Admitted Enrolled

Year Ethnicity Gender Masters Doctoral Masters Doctoral Masters Doctoral Asian Only Female 4 1 3 3 Male 7 4 7 5 Black only + Multi- Female 2 2 2 racial w/Black Male 2 2 2 Hispanic or Latino of Female 3 2 1 any Race Male 4 2 3 1 2 1 International Female 55 52 3 5 1 5 2010 Male 51 70 6 4 2 5 Multi-racial excluding Female 1 1 1 Black Male 1 1 1 Unknown or Not Female 16 25 1 2 Reported Male 21 37 1 White Only Female 15 5 15 2 11 2 Male 45 2 42 1 33 2 2010 Total 227 198 89 13 66 15 Asian Only Female 9 9 7 Male 11 11 10 Black only + Multi- Female 1 1 racial w/Black Male 6 6 2 Hispanic or Latino of Female 3 3 2 any Race Male 4 4 1 International Female 3 3 3 3 2 3 2011 Male 6 2 6 2 6 4 Multi-racial excluding Female 1 1 1 Black Male 2 2 2 Unknown or Not Female 2 2 2 Reported Male 1 1 White Only Female 23 23 17 Male 59 3 59 3 47 3 2011 Total 129 10 129 10 98 11

Graduate Students Applied, Admitted and Enrolled 2012-2013

Applied Admitted Enrolled

Year Ethnicity Gender Masters Doctoral Masters Doctoral Masters Doctoral Asian Only Female 5 5 4 Male 7 7 5 Black only + Multi- Female 2 2 1 racial w/Black Male 3 3 3 Hispanic or Latino of Female 4 4 3 any Race Male 5 5 2 International Female 2 6 2 6 1 6 2012 Male 1 5 1 5 5 Multi-racial excluding Female 1 1 Black Male 1 1 1 Unknown or Not Female 1 1 1 Reported Male 4 4 2 White Only Female 18 4 18 4 15 2 Male 48 5 48 5 38 4 2012 Total 102 20 102 20 76 17 Asian Only Female 9 1 9 1 6 Male 7 7 3 Black only + Multi- Female 4 4 3 racial w/Black Hispanic or Latino of Male 4 4 4 any Race International Female 1 1 1 1 1 1 2013 Male 8 8 8 Multi-racial excluding Female 1 1 1 Black Unknown or Not Female 2 2 2 Reported Male 2 2 2 White Only Female 15 2 15 2 11 2 Male 37 7 37 7 27 4 2013 Total 82 19 82 19 60 15

Students by GPR Range (Cumulative GPR as of the beginning of semester)

Semester Real Classification GPR Range Student % of Cumulative Cumulative Year Major Level (Beginning Headcount Total Headcount % of Semester) Fall 2008 STAT Doctoral 3.75-4.00 28 2.82% 28 3% 3.50-3.74 5 0.50% 33 3% 3.00-3.49 12 1.21% 45 5% 0 or unknown 4 0.40% 49 5% Masters 3.75-4.00 14 1.41% 63 6% 3.50-3.74 12 1.21% 75 8% 3.00-3.49 14 1.41% 89 9% 2.50-2.99 3 0.30% 92 9% 2.00-2.49 3 0.30% 95 10% 0.01-1.99 1 0.10% 96 10% 0 or unknown 38 3.83% 134 13% Fall 2009 STAT Doctoral 3.75-4.00 34 3.42% 168 17% 3.50-3.74 10 1.01% 178 18% 3.00-3.49 10 1.01% 188 19% 2.50-2.99 1 0.10% 189 19% Masters 3.75-4.00 34 3.42% 223 22% 3.50-3.74 9 0.91% 232 23% 3.00-3.49 19 1.91% 251 25% 2.50-2.99 4 0.40% 255 26% 0 or unknown 49 4.93% 304 31% Fall 2010 STAT Doctoral 3.75-4.00 31 3.12% 335 34% 3.50-3.74 10 1.01% 345 35% 3.00-3.49 12 1.21% 357 36% 0 or unknown 1 0.10% 358 36% Masters 3.75-4.00 25 2.52% 383 39% 3.50-3.74 16 1.61% 399 40% 3.00-3.49 20 2.01% 419 42% 2.50-2.99 9 0.91% 428 43% 2.00-2.49 2 0.20% 430 43% 0.01-1.99 1 0.10% 431 43% 0 or unknown 43 4.33% 474 48%

Semester Real Classification GPR Range Student % of Cumulative Cumulative Year Major Level (Beginning Headcount Total Headcount % of Semester) Fall 2011 STAT Doctoral 3.75-4.00 25 2.52% 499 50% 3.50-3.74 9 0.91% 508 51% 3.00-3.49 11 1.11% 519 52% 2.50-2.99 1 0.10% 520 52% 0 or unknown 1 0.10% 521 52% Masters 3.75-4.00 25 2.52% 546 55% 3.50-3.74 22 2.22% 568 57% 3.00-3.49 26 2.62% 594 60% 2.50-2.99 9 0.91% 603 61% 2.00-2.49 3 0.30% 606 61% 0.01-1.99 1 0.10% 607 61% 0 or unknown 51 5.14% 658 66%

Fall 2012 STAT Doctoral 3.75-4.00 24 2.42% 682 69% 3.50-3.74 7 0.70% 689 69% 3.00-3.49 6 0.60% 695 70% 0 or unknown 2 0.20% 697 70% Masters 3.75-4.00 24 2.42% 721 73% 3.50-3.74 14 1.41% 735 74% 3.00-3.49 37 3.73% 772 78% 2.50-2.99 8 0.81% 780 79% 2.00-2.49 3 0.30% 783 79% 0.01-1.99 1 0.10% 784 79% 0 or unknown 36 3.63% 820 83% Fall 2013 ANLY Masters 3.00-3.49 1 0.10% 821 83% 0 or unknown 10 1.01% 831 84% STAT Doctoral 3.75-4.00 24 2.42% 855 86% 3.50-3.74 7 0.70% 862 87% 3.00-3.49 7 0.70% 869 88% 0 or unknown 4 0.40% 873 88% Masters 3.75-4.00 29 2.92% 902 91% 3.50-3.74 18 1.81% 920 93% 3.00-3.49 28 2.82% 948 95% 2.50-2.99 6 0.60% 954 96% 2.00-2.49 5 0.50% 959 97% 0 or unknown 34 3.42% 993 100% Summary 993 100.00% - -

Institutional Support for Full Time Students

Fiscal Year 2009 Fiscal Year 2012 Institutional Salary Support $1,000,125 Institutional Salary Support $908,250 Tuition - Fall, Spring and Summer $278,291 Tuition - Fall, Spring and Summer $315,387 College of Science Funded Scholarships $12,500 College of Science Funded Scholarships $83,500 Departmental Funded Scholarships $6,800 Departmental Funded Scholarships $7,400 TOTAL $1,297,716 TOTAL $1,314,537

Fiscal Year 2010 Fiscal Year 2013 Institutional Salary Support $1,235,225 Institutional Salary Support $893,160 Tuition - Fall, Spring and Summer $341,220 Tuition - Fall, Spring and Summer $231,101 College of Science Funded Scholarships $12,500 College of Science Funded Scholarships $69,000 Departmental Funded Scholarships $8,600 Departmental Funded Scholarships $15,625 TOTAL $1,597,545 TOTAL $1,208,886

Fiscal Year 2011 Fiscal Year 2014 Institutional Salary Support $1,206,680 Institutional Salary Support $966,690 Tuition - Fall, Spring and Summer $315,387 Tuition - Fall, Spring and Summer $246,739 College of Science Funded Scholarships $74,000 College of Science Funded Scholarships $27,000 Departmental Funded Scholarships $16,000 Departmental Funded Scholarships $9,800 TOTAL $1,612,067 TOTAL $1,250,229

Honors & Awards Received by Students

YEAR STUDENT AWARD/FELLOWSHIP • Garcia, Tanya Texas A&M University Louis Stokes Alliance for Minority Participation (TAMUSLSAMP) Fellowship • Emanuel Parzen Research Graduate Fellowship Award Ghosh, Souparno • Laha Travel Award 2009 Lennox, Kristen • Emanuel Parzen Graduate Research Fellowship Award • Rolfes, Jennifer Texas A&M University Louis Stokes Alliance for Minority Participation (TAMUSLSAMP) Fellowship Xun, Xiaolei • William S. Connor Award

Bandyopadhyay, Soutir • Emanuel Parzen Graduate Research Fellowship Chen, Dai • Norbert Hartmann, Jr. Fellowship De, Debkumar • Statistics Former Student Fellowship Garcia, Tanya • Philanthropic Educational Organization (PEO) Scholar Award Kolodziej, Elizabeth • Distinguished Graduate Student Award for Excellence in Teaching Young (University-Wide) Roh, Soojin • James Goodlett Fellowship 2010 Sin, Ying • ASA Travel Award SRCOS Sun, Ranye • Eva & Lee Smith Fellowship Sun, Tanya • William S. Connor Award Xu, Kun • Norbert Hartmann, Jr. Fellowship Xun, Xiaolei • Margaret Sheather Memorial Award in Statistics You, Jia • Ruth & Howard Newton Fellowship

Ball, Robyn • NASA GSRP Fellowship • Statistics Former Student Fellowship Chen, Shuia • Eva & Lee Smith Fellowship Garcia, Tanya • Gertrude Cox Scholarship • Statistics Former Student Fellowship Jeong, Jaehong • James Goodlett Fellowship Pflueger, Michelle • Margaret Sheather Memorial Award in Statistics 2011 Sarkar, Abhra • JSM Student Paper Award Song, Qifan • William S. Connor Award Xu, Ganggang • Emanuel Parzen Graduate Research Fellowship • Statistics Former Student Fellowship Zhang, Bohai • Ruth & Howard Newton Fellowship • Statistics Former Student Fellowship Zhang, Nan • Norbert Hartmann, Jr. Fellowship

• Dean’s Graduate Scholarship Algeri, Sara • Non-Teaching Assistantship • Eva & Lee Smith Fellowship Ball, Robyn • Philanthropic Educational Organization (PEO) Scholar Award Cai, Quan • Eva & Lee Smith Fellowship 2012 Cheng, Yichen • Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural) Durgin, Bryce • Capital One Modeling Competition Gregory, Karl • Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural) • Eva & Lee Smith Fellowship Liang, Liang • Ruth & Howard Newton Fellowship

Little, Alex • Margaret Sheather Memorial Award Mintz, Steven • Ruth & Howard Newton Fellowship Mukhopadhyay, • Subhadeep Emanuel Parzen Graduate Research Fellowship Award • Ruth & Howard Newton Fellowship Seem, Emily • Statistics Former Student Fellowship Shin, Minsuk • Statistics Former Student Fellowship Shin, Yei-Eun • Norbert Hartmann, Jr. Fellowship Sinha, Shyamalendu • Norbert Hartmann, Jr. Fellowship Song, Qifan • Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural) Sun, Ranye • Capital One Modeling Competition • Norbert Hartmann, Jr. Fellowship Wang, Xiao • James Goodlett Fellowship Whang, Stephanie • Capital One Modeling Competition Xu, Ganggang • ENAR Distinguished Student Paper Award Xu, Kun • William S. Connor Award Xue, Jingnan • James Goodlett Fellowship Xue, Kun • Capital One Modeling Competition

Algeri, Sara • Eva & Lee Smith Fellowship Ball, Robyn • Philanthropic Educational Organization (PEO) Scholar Award Cai, Quan • Eva & Lee Smith Fellowship Jennings, Elizabeth • Margaret Sheather Memorial Award in Statistics • James Goodlett Fellowship Li, Furong • Norbert Hartmann, Jr. Fellowship • Eva & Lee Smith Fellowship Liang, Liang • Ruth & Howard Newton Fellowship Mintz, Steven • Ruth & Howard Newton Fellowship Sarkar, Abhra • JSM SBSS Student Paper Competition Winner • Anant M. Kshirsagar Endowed Fellowship 2013 Seem, Emily • Statistics Former Student Fellowship • Ruth & Howard Newton Fellowship Shin, Yei Eun • Norbert Hartmann, Jr. Fellowship Shin, Minsuk • Statistics Former Student Fellowship Sinha, Shyamalendu • Norbert Hartmann, Jr. Fellowship Song, Qifan • Emanuel Parzen Graduate Research Fellowship Su, Ya • William S. Connor Award • James Goodlett Fellowship Wang, Xiao • Norbert Hartmann, Jr. Fellowship Xu, Ganggang • International Biometric Society’s Easter North American Region Xue, Jingnan • James Goodlett Fellowship

Cai, Quan • Capital One Modeling Competition, 1st Place Ghosh, Riddhi • OGAPS Dean’s Doctoral Fellowship • Emanuel Parzen Graduate Research Fellowship He, Kejun • Anant M. Kshirsagar Endowed Fellowship He, Shiyuan • Anant M. Kshirsagar Endowed Fellowship 2014 Herta, Patrick • College of Science Dean’s Doctoral Fellowship Jennings, Elizabeth • Philanthropic Educational Organization (PEO) Scholar Award Jreij, Vennessa • OGAPS Graduate Diversity Fellowship Lee, Donghyuk • Anant M. Kshirsagar Endowed Fellowship Liang, Liang • Capital One Modeling Competition, 1st Place 52

Liu, Senmao • Capital One Modeling Competition, 1st Place • College of Science Dean’s Doctoral Fellowship Metheney, Erica • College of Science Lechner Fellowship Niu, Yabo • OGAPS Dean’s Doctoral Fellowship Peiskee, J.D. • Capital One Modeling Competition, 3rd Place Philbin, Robert • College of Science Lechner Fellowship • College of Science Lechner Fellowship Pugh, Chelsea • Eva & Lee Smith Fellowship • Norbert Hartmann, Jr. Fellowship Ramalingaiah, Indu • Capital One Modeling Competition, 3rd Place • Ruth & Howard Newton Fellowship • Norbert Hartmann, Jr. Fellowship Stabile, Lauren • Statistics Former Student Fellowship • James Goodlett Fellowship Sundararajan, Raanju • Anant M. Kshirsagar Endowed Fellowship • OGAPS Dean’s Doctoral Fellowship Wang, Tianying • College of Science Dean’s Doctoral Fellowship Wang, Xiao • Capital One Modeling Competition, 3rd Place Wen, Yujin • Capital One Modeling Competition, 1st Place • William S. Connor Award Xue, Jingnan • Capital One Modeling Competition, 1st Place Zhang, Bohai • Capital One Modeling Competition, 3rd Place Zhou, Weiyin • Margaret Sheather Memorial Award in Statistics

The Statistics Graduate Student Association

The Statistics Graduate Student Association represents all graduate students in the Department of Statistics at Texas A&M University. It is led by the elected officers, Mary Frances Dorn (President), Alex Asher (Vice President and President-elect), Amir Nikooienejad (Treasurer), Shelby Cummings (Secretary), and Quan Cai (Web Designer). Our mission is to provide the best possible environment to encourage the interaction between students and faculty by providing forums for students to connect with faculty as they discuss their current research, encouraging participation in academic events outside of the traditional classroom setting, and by giving back to the community that supports all of us in the A&M family. The SGSA organizes a number of academic and professional events throughout the year. One of the most important functions of the SGSA is to foster connections between the students and faculty. We do this mainly through informal talks given by faculty about their research interests. On a biennial basis, we also invite a renowned statistician from outside of our department to give a talk and to meet with our students. We are currently preparing for an annual workshop on high-performance computing led by our department’s Director of Information Technology. Additionally, we organize visits by recruiters from a variety of industries. This year, we have already hosted five recruitment presentations from companies including Shell, Rackspace, and Capital One, and are preparing for another event next month. Finally, we provide the opportunity for students to give talks in front of their fellow students. This year, we have scheduled a couple of graduating students to give their practice defense. The SGSA also serves to bring the students together as a community outside of the workplace. Some of the social activities this year include an Ultimate Pi Day celebration, a combination game night and Lunar New Year celebration, pumpkin carving, and bowling. We still have two important events scheduled this semester. One is our popular Faculty Appreciation Barbecue that brings together students, post docs, faculty, and their families. Another is our participation as an organization in the Big Event, the campus-wide service project to say “thank you” to the Bryan/College Station community. These events, both academic and social, help to bring together the students, whether they are first-years or finishing their dissertations, both domestic and international. Our continuing goal for the SGSA is to promote and to strengthen these connections so that all students feel that they are part of the Department of Statistics family.

STUDENT PUBLICATIONS 2009-2013

Student Publications

2009

2010

2011

2012

2013

0 2 4 6 8 10 12 14

Professional Development Opportunities for Students

The Department of Statistics and Texas A&M University offer a wide range of Professional Development opportunities to graduate students seeking careers both in and outside of academia. The Statistics Department provides faculty career advising and mentoring. Students within the department can obtain financial assistance for opportunities to travel and present at conferences. The Statistics Graduate Student Association (SGSA) hosts several industry recruitment events each semester to explore professional internships and job opportunities outside of TAMU. SGSA also holds student panels for those in the program to ask questions about research, advisors, job hunting and how to succeed in the program. In addition, SGSA hosts workshops, presentations and lunch seminars with current faculty. There are currently 8 campus units outside of the Department of Statistics that provide professional development opportunities for our students: the Career Center, Center for Teaching Excellence, Graduate Student Council, International Student Services, Office of Graduate and Professional Studies, Student Counseling Center, University Libraries, and the University Writing Center. TAMU’s Center for Teaching Excellence (CTE) provides opportunities for current students to enhance their knowledge and experience as a Teaching Assistant with TA certification, TA mentor training, STEM teaching professional development courses, teaching seminar series, consulting and more. The CTE also houses the Academy for Future Faculty which supports graduate students and post-docs in preparation for a career in higher education. Students can earn an Academy for Future Faculty certificate and can access tools for portfolios and syllabus builders, attend free seminars and workshops on a range of subjects for teaching in higher education. The Career Center provides a wide range of services including resume help, career advising, workshops, internships, mock interviews and career fairs. The Office of Graduate and Professional Studies promotes professional development in four areas: academic development, leadership and communication, instructions and assessment, and career development. They provide a search engine for students to identify professional development opportunities across campus. They have also implemented a 3 Minute Thesis Competition (developed at the University of Queensland) in which students have three minutes to present a compelling oration on their thesis. The Office of Graduate and Professional Studies, along with the University Writing Center, also offers thesis/dissertation workshops and seminars. Along with other resources, the Office of Graduate and Professional Studies and the Career Center also offer access to the Versatile PhD. This resource is the largest online community for non-academic and non-faculty careers. MS and PhD students can see real resumes and CV’s, read real success stories and career panels, consult forums and search for job listings outside academia.

AVERAGE YEAR TO DEGREE, BY DEGREE PROGRAM (STATISTICS)

PhD MS

7.00

6.00

5.00

4.00

3.00

2.00

1.00

0.00 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13

Year Doctoral (PhD) Masters (MS) 2006-07 4.07 2.31 2007-08 3.25 2.33 2008-09 3.90 2.77 2009-10 5.64 3.21 2010-11 5.44 2.73 2011-12 5.46 3.01 2012-13 6.06 3.11

STAT Masters Graduation and Retention Report

2 - Year 3 - Year % Master % Retain in % Master % Retain in Cohort Year Headcount Completion Master Completion Master 2001 17 35.30% 41.20% 82.40% 2002 20 35.00% 50.00% 70.00% 5.00% 2003 9 55.60% 44.40% 77.80% 11.10% 2004 9 55.60% 33.30% 100.00% 2005 10 70.00% 10.00% 90.00% 2006 14 64.30% 35.70% 100.00% 2007 14 28.60% 42.90% 64.30% 2008 33 24.20% 33.30% 42.40% 18.20% 2009 36 11.10% 38.90% 33.30% 13.90% 2010 30 16.70% 30.00% 36.70% 3.30% 2011 32 9.40% 28.10% 21.90% 9.40% 2012 46 6.50% 26.10%

STAT Doctoral Graduation and Retention Report

4 - Year 5 - Year 6 - Year

Cohort % Doctoral % Retain in % Not Enr but % Doctoral % Retain in % Not Enr but % Doctoral % Retain in % Not Enr but _Year Headcount Completion Doctoral Earn Mas Deg Completion Doctoral Earn Mas Deg Completion Doctoral Earn Mas Deg 2001 14 14.30% 42.90% 14.30% 42.90% 14.30% 14.30% 50.00% 7.10% 14.30% 2002 7 28.60% 28.60% 42.90% 71.40% 28.60% 71.40% 28.60% 2003 12 41.70% 33.30% 16.70% 83.30% 8.30% 91.70% 2004 9 44.40% 11.10% 33.30% 66.70% 11.10% 11.10% 77.80% 11.10% 2005 8 37.50% 25.00% 25.00% 50.00% 12.50% 25.00% 62.50% 25.00% 2006 15 13.30% 26.70% 46.70% 46.70% 13.30% 26.70% 60.00% 26.70% 2007 28 17.90% 32.10% 39.30% 53.60% 10.70% 25.00% 67.90% 3.60% 17.90% 2008 17 29.40% 23.50% 5.90% 47.10% 17.60% 52.90% 5.90% 2009 17 41.20% 35.30% 64.70% 11.80% 2010 22 18.20% 40.90% 27.30%

Master’s Degrees Awarded 2009-2014

Name Month Received Advisor(s) Ali, Mir Usman December Boggess/ Longnecker Bergstresser, Dana Lea May Sheather/Speed Fellman, Bryan Michael December Boggess/Longnecker Jann, Dominic Andrew May Speed/ Longnecker Krassavine, Konstantin December (Online) Speed/Longnecker Li, Jing December West, W. Lee, Jun Bum May Subba Rao, S. Longsine, Lindsay Anne May Wehrly, T.

Pan, Ying-An May Longnecker/Speed Perritt, Jon Ross August Longnecker/Boggess 2009 Pirlepesov, Fakhiriddin December Carroll, R. Shoulders, Jeromie Lamun August (Online) Speed/Longnecker Walters, Lori Katherine May Boggess/Speed Wan, Qiujie August Speed, F.M. Wang, Yiyi December Dahl, D. Wei, Shan December Hart, J. Wiley, Allison LuAnn May Dabney, A. Xun, Xiaolei December Mallick/Carroll Yang, Zhixian May Liang, F. Ackerman, Clarissa M. December (Online) Sheather, S. Bankston, Thomas Clifton December (Online) Speed, F.M. Black, Rebecca A. August Speed/Longnecker Bussell, Sammy J. Jr. December (Online) Speed/ Longnecker Byers, Michael David May (Online) Speed/Longnecker Cefalu, Matthew Steven May Longnecker/Boggess Chen, Dai May Huang, J. Christensen, Brent Thomas May (Online) Speed/Longnecker

Decker, Thomas Virgil May (Online) Speed/Longnecker Gil, Randall Edward May Carroll, R.

2010 Hopp, Ashley Jean December (Online) Speed/Longnecker Hughes, Kelley Leigh December (Online) Wehrly/Longnecker Kim, Hei Joung May Subba Rao, S. Lane, David Edward December (Online) Speed/Longnecker Lu, Ming May Wang, S. Riester, Katherine Demetra December (Online) Perrett/Speed Rolfes, Jennifer A. August Speed/Longnecker Yoo, Seung Yoon December Sinha, S. Zhang, Yiwei May Fan, R.

Alzubaydi, Michael J. December (Online) Dabney, A. Andersen, Clark R. December (Online) Speed/Wehrly Cepulch, Gregory Joseph May Hart, J. Chang, Qing December Fan, R. Chown, Justin A. August Sherman/Jun Dorji, Cheku August Dahm, P.F. Finch, William May (Online) Speed, F.M. Goldsby, Jennifer S. December Longnecker, M. Greenfield, Jason O’Neal May (Online) Perrett, J. Gregory, Karl Bruce May Lahiri, S. Gu, Manxi May Fan, R. He, Zhuoya December (Online) Huang, J. Hetz, Shira May Sheather, S.

Kennedy, Kelly Marie May Wehrly, T.

King, Simon J. December (Online) Perrett, J. 2011 Krutsick, Robert S. August (Online) Dabney/Longnecker Levine, Ian R. August (Online) Dabney/Speed Little, Bryce P. December (Online) Dahl, D. Lu, Jianxu December Fan/Longnecker Lydon, Daniel T. December (Online) Dabney, A. Massey, Ronnie May (Online) Speed/Longnecker Oh, Minkyung May Sinha, S. Pflueger, Michelle L. May (Online) Huang, J. Phillips, Christopher T. December Dabney, A. Sheng, Jinfei December Huang, J. Tang, Xincheng December Dabney, A. Wang, Jieyu May Liang, F. Zhang, Li Yun August (Online) Dabney, A. Austria, Gener M. May (Online) Speed, F.M. Barman, Poulami May Spiegelman, C. Bateman, Katherine A. August Longnecker/Speed Bennett, John C. December (Online) Sheather, S. Blaskowski, Stacie M. December (Online) Sinha, S. Chen, Shuai May Huang, J. Connelly, Karen E. May (Online) Wehrly, T. Franklin, Cynthia A. May (Online) Wehrly, T. Goddard, Scott D. August Genton, M. 2012 Goll, Johannees August (Online) Dabney, A. Gordon, Charles M. May (Online) Sinha, S. Gudupuri, Vennela August (Online) Perrett/Speed Hanley-Burkhart, Jennifer E. May (Online) Sinha, S. Housley, Emily E. August (Online) Mallick, B. Jennings, Elizabeth M. August Carroll, R. Little, Alexander A. May (Online) Wehrly, T. Lucas, William F. December Speed, F.M. 61

McManus, Weston K. May (Online) Speed, F.M. Moody, Grant A. August (Online) Toby, E. Napier, Todd A. December Longnecker, M. Neumann, Anthony M. May Longnecker, M. Olmstead, Kaitlin S. December (Online) Cline, D. Reed, Paul W. December (Online) Jun, M. Ryan, Christopher W. May (Online) Dabney, A. Shetty, Nathan S. December (Online) Spiegelman/Mallick Tuteja, Navneet August (Online) Huang/Longnecker Torno, Nathan B. May West, W. Tripathi, Anjani May (Online) Mallick, B. Uppalapati, Deepthi December (Online) Dahl, D. Wang, Kai-Sin December Longnecker, M. Wang, Ling December (Online) Speed, F.M. Whitten, Jennifer L. December (Online) Wehrly, T. Williams, Kaylee D. May (Online) Mallick, B. Yingling, Michael D. December (Online) Wehrly, T. Zhang, Mi May (Online) Huang, J. Zhang, Rong May (Online) Hart, J. Akdede, Merve August Longnecker, M. Beck, Sarah J. December (Online) Dabney, A. Bein, Justin Matthew December (Online) Spiegelman, C. Brady, Ryan Douglass August (Online) Spiegelman, C. Brown, Angela N. May (Online) Wehrly, T. Cope, Tara Marie August (Online) Wehrly, T. Cox, Cody Lee August (Online) Huang, J. Daligou, Servais D. August (Online) Mallick, B. Dean, Amber E. May (Online) Hart, J. Frederiksen, Eric L. May (Online) Huang, J. Green, Abigail Brice December (Online) Sinha, S. Harper, Nathan Lee December (Online) Dabney, A. Hasbun, Jorge A. May (Online) Dabney, A.

2013 Hong, Ji August (Online) Pourahmadi, M. Jackson, Steven M. May (Online) Cline, D. Jagannathan, Shilpa December Longnecker, M. Jorgensen, Janine M. May (Online) Carroll, R. Kim, Jinsu December Huang, J. Kim, Shiheun December Longnecker, M. Lee, Younguk August Jones, E. Lizarraga, Laci Elizabeth December (Online) Dabney, A. Martin, Zachary James August (Online) Jones, E. Negash, Yonatan December (Online) Jones, E. Nimchuk, Nicholas May (Online) Spiegelman, C Phan, Jennifer Lee December (Online) Huang, J. Pitts, Mark Anthony December (Online) Speed, F.M. 62

Platt, Stephanie Ross August (Online) Sheather, S. Poole, Jason Eugene December (Online) Dabney, A. Roychowdhury, Lakshmi May Lahiri, S. Stolz, Phillip Lawrence December (Online) Dahm, P. F. Walker, Tobias May (Online) Dabney, A. Whang, Stephanie S. May Huang, J. Wilson, Celeste K. May (Online) Sherman, M. Wong, Yuen Sum December (Online) Huang, J. Algeri, Sara August Johnson, V. Aucoin, Deron Lane December (Online) Zhou, L. Beltramo, Alvin F. August (Online) Dabney, A. Bessinger, Alexander M. May (Online) Sheather, S. Byler, Daniel Mahlon December (Online) Sheather/Katzfuss Chapman, Richard Scott August (Online) Sheather, S. Costello, Lance John August (Online) Sheather, S. Davis, Taylor K. May (Online) Sheather, S. Evert, Daniel James December (Online) Sheather, S. Fetzer, Jeffrey R. May (Online) Dabney, A. Galang, Joel Samson May (Online) Sheather, S. Goldsmith, Anne Wiley August Hart, J. Goodhue, Jonathan Thiel December (Online) Sheather/Katzfuss Gosink, John Joseph December (Online) Zhou, L. Govan, Barney May (Online) Huang, J. Hejmadi, Uday August (Online) Sheather, S. Hosek, Kathleen May (Online) Sheather, S. Johnson, Kurt Benjamin December (Online) Jones, E. Joseph, James A. May (Online) Sheather, S. 2014 Kreisler, Craig Jordan May (Online) Sinha, S. Lee, Melissa Michelle May (Online) Spiegelman, C. Li, Kelvin December (Online) Sheather/Katzfuss Liu, Dan August (Online) Sheather, S. Lucas, Geoffrey M. December (Online) Zhou, L. Magagnoli, Joseph Carlo December (Online) Sheather, S. Morse, Jennifer Lee May (Online) Sheather, S. Olivares, Rolando Javier May Longnecker, M. Pestrivok, Aleksei August (Online) Sheather, S. Philbin, Robert A. August (Online) Jun, M. Przybylinski, Eric Brady December (Online) Zhou, L. Roane, Warren Maurice August (Online) Sheather/Katzfuss Rodriguez, Christopher Jessie May (Online) Sheather, S. Scott, Zachary M.H May (Online) Wehrly, T. Szydziak, Elisa May (Online) Sheather, S. Temple, Samuel Robert May (Online) Sheather, S. Tran, Hung Manh May (Online) Sheather, S. Vu, Cong-Tam Dinh May (Online) Longnecker, M. 63

Walsh, Colm May (Online) Jones, E. Wang, Ruoxin August Wang, S. Wilkerson, Huiwen May (Online) Dabney, A. Womack, Scott Forrest May (Online) Jun, M. Zhang, Wenling August(Online) Jones, E. Zhou, Qian May Longnecker, M. Zhou, Weiyin May(Online) Dabney, A.

Ph.D. Degrees Awarded 2009-2014

Name Dissertation Title Advisor(s) Ghosh, Souparno Copula Based Hierarchical Bayesian Models (August) Mallick, B. Herring, Amanda Space-Time Forecasting and Evaluation of Wind Speed Genton, M. Scott with Statistical Tests for Comparing Accuracy of Spatial Predictions (August) Lee, Seokho Principal Components Analysis for Binary Data (May) Huang/Carroll 2009 Litton, Nathaniel Deconvolution in Random Effects Models via Normal Hart, J. Mixtures (August) Savchuk, Olga Choosing a Kernel for Cross-Validation (August) Hart/Sheather Wagaman, John C. Model-Based Pre-Processing in Protein Mass Huang/West Spectrometry (December) Bandyopadhyay, On Parametric and Nonparametric Methods for Lahiri, S Soutir Dependent Data (August) Dhavala, Soma Sekhar Bayesian Semiparametric and Models for Mallick, B. Heterogeneous, Cross-Platform Differential Gene Expression (December) Hartman, Brian M. Bayesian Hierarchical, Semiparametric, and Non- Mallick, B. parametric Methods for International New Product Diffusion (August) Joshi, Adarsh Bayesian model Selection for High-Dimensional High- Dahl/Johnson Throughput Data (May) Kolodziej, Elizabeth Y. Nonparametric Methods for Point Processes and Sherman, M. Geostatistical Data (August) Lennox, Kristin P. Bayesian Nonparametric Methods for Protein Structure Dahl, D. Prediction (August) Lindsey, Charles D. Coherent Control of Laser Field and Spectroscopy in Sheather, S. Dense Atomic Vapor (May) Marchenko, Yulia Multivariate Skew-t Distributions in Econometrics and Genton, M. 2010 Environmetrics (December) Redd, Andrew M. An Addictive Bivariate Hierarchical Model for Functional Carroll, R. Data and Related Computations (August) Rister, Krista Dianne Resampling Methodology in Spatial Prediction and Lahiri, S. Repeated Measures Time Series (December) Sun, Xiuzhen Bias Reduction and Goodness-of-Fit Tests in Conditional Wang/Sinha Logistic Regression Models (August) Wei, Jiawei Secondary Analysis of Case-Control Studies in Genomic Carroll, R. Contexts (August) Wu, Mingqi Population SAMC, ChIP-chip Data Analysis and Beyond Liang, F. (December) Zhang, Saijuan Bayesian Methods in Nutrition Epidemiology and Carroll/Huang Regression-Based Predictive Models in Healthcare (December) Zhong, Ming Extended Homozygosity Score Test to Detect Positive Fan, R. Selection in Genome-Wide Scans (May)

Barney, Bradley J. Bayesian Joint Modeling of Binomial and Rank Response Johnson/Sheather Data (August) Chen, Lianfu Topics on Regularization of Parameters in Multivariate Pourahmadi, M. Linear Regression (December) Chen, Nai-Wei Goodness-of-Fit Tests Issues in Generalized Linear Mixed Wehrly, T. Models (December) Garcia, Tanya Pamela Efficient Semiparametric Estimators for Biological, Genetic, Ma, Y. and Measurement Error Applications (August) Glab, Daniel L. Testing Lack-of-Fit of Generalized Linear Models via Wehrly, T. Laplace Approximation (May) Jin, Ick Hoon Statistical Inferences for Models with Intractable Liang, F. Normalizing Constants (August)

Konomi, Bledar Bayesian Spatial Modeling of Complex and High Mallick/Sang Dimensional Data (December)

2011 Maadoliat, Mehdi Dimension Reduction and Covariance Structure for Huang, J. Multivariate Data, Beyond Gaussian Assumption (August) Mondal, Anirban Bayesian Quantification for Large Scale Spatial Inverse Mallick, B. Problems (August) Pan, Huijun Bivariate B-Splines and Its Application in Spatial Data Huang/Zhou Analysis (August) Singh, Trijya Efficient Small Area Estimation in the Presence of Carroll/Wang Measurement Error in Covariates (August) Sun, Ying Inference and Visualization of Periodic Sequences (August) Hart/Genton Talluri, Rajesh Bayesian Gaussian Graphical Models Using Sparse Mallick, B. Selection Priors and Their Mixtures (August) Wang, Qi Frequent-Bayes Goodness-of-Fit Tests (August) Hart, J. Xu, Ganggang Variable Selection and Function Estimation Using Huang/Wang Penalized Methods (December) Crawford, Scott Efficient Estimation in a Regression Model with Missing Müller-Harknett, U. Responses (August) Jann, Dominic A. Bayesian Logistic Regression with Jaro-Winkler String Speed/Sheather Comparator Scores Provides Sizable Improvement in Probabilistic Record Matching (December) Kim, Mi Jeong Efficient Semiparametric Estimators for Nonlinear Ma, Y. Regressions and Models under Sample Selection Bias

(August) Kohli, Priya Prediction and Estimation of Random Fields (August) Pourahmadi/Chen

2012 Lee, Jun B. A Novel Approach to the Analysis of Nonlinear Time Series Subba Rao, S. with Applications to Financial Data (May) Park, Jincheol Bayesian Analysis for Large Spatial Data (August) Liang, F. Wang, Xuan Statistical Methods for the Analysis of Mass Spectrometry- Dabney, A. Based Proteomics Data (May) Xun, Xiaolei Statistical Inference in Inverse Problems (May) Mallick/Carroll Zhan, Dongling The k-Sample Problem When k is Large and n Small (May) Hart, J. D. Zhang, Lin Application of Bayesian Hierarchical Models in Genetic Mallick/ Data Analysis (December) Baladandayuthapani

Ball, Robyn L. Statistical Methods for High Dimensional Biomedical Data Dabney, A. (May) Chen, Hsiang-Chun Interference for Clustered Mixed Outcomes from a Wehrly, T. Multivariate Generalized Linear Mixed Model (August) Cheng, Yichen Stochastic Approximation and Its Application in MCMC Liang, F. (August) Gaucher, Beverly J. Factor Analysis for Skewed Data and Skew-Normal Hart/Wehrly

Maximum Likelihood Factor Analysis (May) Mukhopadhyay, Nonparametric Inference for High Dimensional Data (May) Lahiri/Parzen

2013 Subhadeep Wang, Yiyi Statistical Models for Next Generation Sequencing Data Dahl/Liang (May) Xu, Kun Semiparametric Estimation and Inference with Mis- Ma, Y. Measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine, and Neurology (December) Zhu, Xinxin Wind Speed Forecasting for Power System Operation Sang/Genton (August) Chown, Justin Andrew New Approaches in Testing Common Assumptions for Müller-Harknett, U. Regressions with Missing Data (August) De, Debkumar Essays on Bayesian Time Series and Variable Selection Liang/Mallick (May) Feng, Shuo A Likelihood Based Framework for Data Integration with Huang, J. Application to eQTL Mapping (August) Gregory, Karl Bruce Two-Sample Testing in High Dimension and a Smooth Carroll/Lahiri Block Bootstrap for Time Series (August) Kim, Jinsu A Bootstrap Metropolis-Hastings Algorithm for Bayesian Liang, F. Analysis of Big Data (December) Lin, Fang-Yu Combining Strategies for Parallel Stochastic Liang/Carroll Approximation Monte Carlo Algorithm of Big Data (December) Lu, Ming Investigation of Simple Linear Measurement Error Models Dahm, P.F. (SLMEMS) with Correlated Data (December) Miao, Jiangang New Advances in Logistic Regression for Handling Missing Wang/Sinha 2014 and Mismeasured Data with Applications in Biostatistics (August) Qu, Yuan Estimation of Large Spectral Function and Its Application Huang, J. (August) Roh, Soojin Robust Ensemble Kalman Filters and Localization for Jun/Genton Multiple State Variables (August) Sarkar, Abhra Bayesian Semiparametric Density Deconvolution and Mallick/Carroll Regression in the Presence of Measurement Errors (August) Song, Qifan Variable Selection for Ultra-High Dimensional Data Liang, F. (August) Sun, Rayne Thresholding Multivariate Regression and Generalized Pourahmadi/Carroll Principal Components (May) Wang, Yanqing Relative Risks Analysis in Nutritional Epidemiology Carroll/Mallick (August)

Wei, Rubin Highly Nonlinear Measurement Error Models in Nutritional Carroll, R. Epidemiology (May)

Ph.D. Graduate Employers 2009-2014

Student Job Title Employer Gosh, Souparno Assistant Professor Texas Tech University Herring, Amanda Scott Assistant Professor Colorado School of Mines Lee, Seokho Lecturer Korea University of Foreign Studies

2009 Litton Nathaniel Manager of Statistical Analysis Capital One Auto Finance Savchuk, Olga Visiting Instructor University of South Florida Wagaman, John Assistant Professor Western Carolina University Bandyopadhyay, Soutir Assistant Professor Lehigh University Dhavala, Soma Sekhar Associate Research Scientist Dow AgroSciences LLC, Global Research Center Hartman, Brian Assistant Professor University of Connecticut Joshi, Adarsh Manager, Biostatistics (Oncology Biomarkers) Gilead Sciences Kolodziej, Elizabeth Y. Senior Lecturer Texas A&M University, Statistics Lennox, Kristin Statistician Lawrence Livermore National Laboratory Lindsey, Charles D. Senior Statistician, Software Developer StataCorp Marchenko, Yulia Associate Director of Biostatistics StataCorp 2010 Redd, Andrew M. Assistant Professor University of Utah Rister, Krista Dianne Senior Statistician Capital One Sun, Xiuzhen (Jenny) Research Assistant Professor Boston Medical Center Wei, Jiawei Statistical Methodologist Novartis Wu, Mingqi Statistician Shell Global Solutions Zhang, Saijuan Biometrician Merck Zhong, Ming Principal Statistician Capital One Barney, Bradley Assistant Professor Kennesaw State University Chen, Lianfu Quantitative Statistics Analyst Sakonnet Technology Chen, Nai-Wei Biostatistics Statistical Consultant University of Texas Medical Branch at Galveston 2011 Garcia, Tanya Assistant Professor Texas A&M University, Biostatistics Glab, Daniel L. Postdoctoral Trainee Mexican American & US Latino Rsch. Ctr, Texas A&M

Jin, Ick Hoon Research Scientist Ohio State University, Center for Biostatistics Konomi, Bledar (Alex) Assistant Professor University of Cincinnati Maadodiat, Mehdi Assistant Professor Marquette University Mondal, Anirban Assistant Professor Case Western Reserve University Pan, Huijun Sr. Consultant, Claim Analytics Travelers Insurance Singh, Trijya Assistant Professor Le Moyne College Sun, Ying Assistant Professor King Abdullah University of Science & Technology Talluri, Rajesh Postdoctoral Fellow, Biostatistics UT- MD Anderson Cancer Center Wang, Qi Group Model Variation Standard Chartered Bank Xu, Ganggang Assistant Professor Binghamton University, State University of New York Crawford, Scott Academic Professional Lecturer University of Wyoming Jann, Dominic A. Senior Associate Analytic Engineer SAS Institute Kim, Mi Jeong Senior Engineer Samsung Electronics Kohli, Priya Assistant Professor of Mathematics Connecticut College Lee, Jun B. Quantitative Analyst CLS Group

2012 Park, Jincheol Postdoctoral Fellow Ohio State University, Stat & Math Bioscience Inst. Wang, Xuan Research Statistical Analyst UT-MD Anderson Cancer Center Xun, Xiaolei Senior Biometrician Novartis Zhan, Dongling Assistant Director Data & Research Services, Texas A&M University Zhang, Lin Assistant Professor University of Minnesota Ball, Robyn L. Postdoctoral Associate The Jackson Laboratory Chen, Hsiang-Chun Research Statistical Analyst MD Anderson Cancer Center Cheng, Yichen Postdoctoral Researcher Fred Hutchinson Cancer Research Center Gaucher, Beverly J. Mathematical Statistician USDA, National Agricultural Statistics Service

2013 Mukhopadhay, Subhadeep Assistant Professor Temple University Wang, Yiyi Director, Home Office Claims Liberty Mutual Insurance Xu, Kun Postdoctoral Associate University of Miami Zhu, Xinxin Statistical Modeler LexisNexis Group

Chown, Justin Andrew Postdoctoral Researcher Université catholique de Louvain De, Debkumar Research Intern Echelon Capital Strategies, LLC Feng, Shuo Statistician/Scientist II Ceva Biomune Gregory, Karl Bruce Postdoctoral Researcher University of Mannheim Kim, Jinsu Enterprise Solution Specialist LG CNS Co., Ltd. Lin, Fang-Yu AVP, Risk Modeler JP Morgan Chase Lu, Ming Searching for industry position Miao, Jiangang Senior Data Analyst American International Group, Inc. 2014 Qu, Yuan Visiting Assistant Professor Purdue University Roh, Soojin Searching for industry position Sarkar, Abhra Postdoctoral Associate Duke University Song, Qifan Assistant Professor Purdue University Sun, Rayne AVP, Corp. Investment Quan. Finance Analyst Bank of America Wang, Yanqing Postdoctoral Researcher Fred Hutchinson Cancer Center Wei, Rubin Senior Statistician Eli Lilly & Company

III. FACULTY INFORMATION

Department of Statistics Faculty, 2014-2015

V. E. Johnson, Professor and Head; Ph.D. in Statistics: University of Chicago, 1989; longitudinal data, nonparametric statistics, applied statistics, biostatistics, categorical data, Bayesian methods.

M. T. Longnecker, Professor and Associate Head; Ph.D. in Statistics: Florida State University, 1976; statistical education and consulting.

D. Akleman, Senior Lecturer; Ph.D. in Agricultural Economics: Texas A&M University, 1996; time series, stochastic processes, risk analysis, artificial intelligence, econometrics.

A. Bhattacharya, Assistant Professor; Ph.D. in Statistics: Duke University, 2012; Factor models, Gaussian process, high-dimensional data, large contingency tables.

J. H. Carroll, Senior Lecturer; MS in Statistics: Texas A&M University, 1990; Statistics education.

R. J. Carroll, Distinguished Professor; Ph.D. in Statistics: Purdue University, 1974; longitudinal data, measurement error, nutritional epidemiology, bioinformatics.

W. Chen, Professor; Ph.D. in Statistics: New York University, 2001; long memory time series, econometrics

D. B. H. Cline, Professor; Ph.D. in Statistics: Colorado State University, 1983; Stochastic networks, nonlinear time series, ergodicity, Markov chains, distribution tails, regular variation

A. Dabney, Associate Professor; Ph.D. in Biostatistics: University of Washington, 2006; microarrays, bioinformatics, classification methods.

P. F. Dahm, Professor and Graduate Advisor; Ph.D. in Statistics: Iowa State University, 1979; measurement error models, biostatistics, econometrics.

C. E. Gates, Professor Emeritus; Ph.D. in Experimental Statistics: North Carolina State University, 1955; design and analysis of experimental data, estimation of wildlife abundance and modeling non-linear growth curves.

J. D. Hart, Professor; Ph.D. in Statistics: Southern Methodist University, 1981; nonparametric function estimation, time series, bootstrap methods.

K. Hatfield, Lecturer; MBA in Operations Research: North Texas State University, 1980; Statistics education and consulting.

R. R. Hocking, Professor Emeritus; Ph.D. in Statistics: Iowa State University, 1962; regression, mixed models and multivariate analysis.

J. Huang, Professor; Ph.D. in Statistics: University of California, Berkeley, 1997; nonparametric and semiparametric methods, statistical function estimation using polynomial splines, statistical methods for longitudinal data/panel data, multivariate/functional data analysis, survival analysis, duration data, event history analysis, statistics application in business.

O. C. Jenkins, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1972; statistical sampling and experimental design.

E. R. Jones, Executive Professor, Ph.D. in Statistics: Virginia Polytechnic and State University, 1976; applied statistics, statistical computing, data mining/machine learning.

M. Jun, Associate Professor, Ph.D. in Statistics: University of Chicago, 2005; statistical methodologies, environmental problems, space-time covariance modeling, numerical model evaluation in air quality problems, combining numerical model output with observed data.

M. Katzfuss, Assistant Professor, Ph.D. in Statistics: Ohio State University, 2011; Spatial and spatio-temporal statistics, Bayesian inference, massive datasets, probabilistic forecasting, applications to environmental data.

E. Y. Kolodziej, Senior Lecturer, Ph.D. in Statistics: Texas A&M University, 2010; spatial statistics, statistics education, consulting.

H. C. Liang, Senior Lecturer, Ph.D. in Statistics: University of New Mexico, 2003; Linear models, statistical education, undergraduate research.

J. P. Long, Assistant Professor, Ph.D. in Statistics: University of California, Berkeley, 2013; Applied statistics, machine learning, time series, classification, astrostatistics, errors-in-variables.

B. Mallick, Distinguished Professor; Ph.D. in Statistics: University of Connecticut, 1994; Bayesian hierarchical modeling, nonparametric regression and classification, bioinformatics, spatio-temporal modeling, machine learning, functional data analysis, Bayesian nonparametrics, petroleum reservoir characterization, uncertainty analysis of computer model outputs.

J. H. Matis, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1970; biomathematics, compartmental analysis, statistical ecology and applied stochastic processes.

U. Müller-Harknett, Professor; Ph.D. in Mathematics: University of Bremen, 1997; non- and semi-parametrics, efficient estimation.

H. J. Newton, Professor and Dean; Ph.D. in Statistics: State University of New York at Buffalo, 1975; time series analysis, computational statistics.

E. Parzen, Distinguished Professor Emeritus; Ph.D. in Mathematics: University of California (Berkeley), 1953; statistical science-developing statistical methods for time series analysis, data analysis, and change analysis.

M. Pourahmadi, Professor, Ph.D. in Statistics: Michigan State University, 1980, time series analysis and prediction theory, multivariate analysis, longitudinal data analysis, mixed-effects models, data mining, stochastic volatility models.

L. J. Ringer, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1966; applied statistics, survey sampling and reliability.

H. Sang, Associate Professor, Ph.D. in Statistics: Duke University, 2008; Bayesian statistics with focus on spatial and spatio-temporal statistics. 74

H. Schmiediche, Director of Information Technology; Ph.D. in Statistics: Texas A&M University, 1993; computational statistics.

S. J. Sheather, Professor and Academic Director of MS Analytics & Online Programs; Ph.D. in Statistics: LaTrobe University, 1986; development of regression diagnostics and robust and flexible regression methods, statistical models of wine quality.

M. Sherman, Professor; Ph.D. in Statistics: University of North Carolina at Chapel Hill, 1992; biostatistics, spatial statistics.

S. Sinha, Associate Professor, Ph.D. in Statistics: University of Florida, 2004; methodological research: missing data technique, measurement error, splines, Bayesian methods: parametric and nonparametric methods, application: epidemiology, genetic epidemiology.

W. B. Smith, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1967; multivariate analysis, missing data methods, correspondence analysis.

F. M. Speed, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1969; computational statistics, biostatistics, linear models, applied statistics, multivariate methods, environmental and industrial statistics, teaching statistics real time.

C. H. Spiegelman, Distinguished Professor; Ph.D. in Statistics & Applied Mathematics: Northwestern University, 1976; calibration curves, measurement error models, applied statistics, especially to chemistry.

S. Subba Rao, Associate Professor; Ph.D. in Statistics: University of Bristol, UK, 2001; time series, nonstationary processes, nonlinear processes, recursive online algorithms, spatio-temporal models.

E. Toby, Professor Emerita; Ph.D. in Mathematics: University of California, San Diego, 1988; biostatistics, diffusions processes.

S. Wang, Professor; Ph.D. in Statistics: University of Texas at Austin, 1988; biostatistical inferences, missing and mis-measured data modeling and analysis, non- and semi-parametric methodology, resampling methods, small sample asymptotics, survey sampling.

T. E. Wehrly, Professor; Ph.D. in Statistics: University of Wisconsin, 1976; stochastic models, directional data, mathematical statistics, nonparametric function estimation.

L. Zhou, Associate Professor, Ph.D. in Statistics: University of California, 1997; statistical Methodology and application in bioinformatics, nutrition and epidemiology, functional/longitudinal data analysis.

J. Zinn, Professor of Mathematics and Statistics; Ph.D. in Mathematics: University of Wisconsin, 1972; empirical processes, bootstrapping.

Honors & Awards Received by Faculty

YEAR NAME AWARD 2009 A. Dabney Montague Scholar, Center for Teaching Excellence M. Longnecker Elected Fellow, American Statistical Association

2010 R. Carroll Oderoff Lecture, University of Rochester E. Toby Distinguished Achievement Award – Teaching, Association of Former Students

2011 A. Dabney Distinguished Achievement Award – Teaching, The Association of Former Students M. Longnecker Statistics Education Award, Mu Sigma Rho M. Speed 12th Man Award

2012 R. Carroll Honorary Doctorate, Institut de Statistique, Universite Catholique de Louvain S. Sheather Namesake, Fish Camp T. Wehrly 12th Man Award

2013 R. Carroll Fellow, American Association of the Advancement of Science J. Huang Fellow, Institute of Mathematical Statistics Fellow, American Statistical Association B. Mallick Fellow, American Association for the Advancement of Science H. Newton Fellow, American Association for the Advancement of Science S. Sheather Distinguished Achievement Award – Teaching, The Association of Former Students 12th Man Award S. Wang Visiting Fellowship Award, Australian National University Mathematical Sciences Research J. Hart 12th Man Award

2014 J. Calvin Professor Emeritus of Statistics R. Carroll Inaugural Holder of the Jill and Stuart A. Harlin ’83 Chair in Statistics Gottfried E. Noether Senior Scholar Award F. Dahm 12th Man Award C. Spiegelman Member of the Houston Forensic Science Local Government Corporation Fellow to American Association for the Advancement of Science E. Toby Professor Emerita of Statistics

Department of Statistics 2014-2015 Committee Assignments

COMMITTEE CHAIR MEMBERS Department Head Johnson Associate Head Longnecker Admissions Committee Huang Mallick, Jun, Wehrly Advisory Committee Longnecker Akleman, Hart, Huang, Katzfuss, Johnson, Jun, Sheather, Mueller-Harknett Assistantship Duties Longnecker J.H. Carroll Awards R. Carroll Mallick, Spiegelman Bioinformatics Mallick Dabney, Sinha, Zhou Colloquia-Special Events Bhattacharya Computing Schmiediche Sinha Consulting Center Jones Diversity Akleman Endowed Positions Committee Sheather Spiegelman, Johnson, Mallick Examinations (Masters) Longnecker Faculty Recruiting Hart Johnson, Katzfuss, Mueller- Harknett, Jun, Sang Graduate Curriculum Committee Huang Longnecker, Cline, Subba Rao, Mueller-Harknett, Bhattacharya Graduate Service Pourahmadi Zhou, Wehrly Graduate Admissions Committee Huang Mallick, Jun, Wehrly Graduate Committee Huang Mallick, Cline, Dahm, Longnecker, Sinha, Jun, Wang Grant Opportunities Spiegelman Subba Rao Library Long NISS Spiegelman Promotion & Tenure Committee Chen Pourahmadi, Wang, R. Carroll, Mueller-Harknett, Jun, Sherman Public Relations/Magazine Johnson SECC Representative Johnson SRCOS Representative Johnson Student Evaluation Committee Sherman Mueller-Harknett, Chen, Sinha, Subba Rao, Jun, Bhattacharya, Wang Teaching Assignments Longnecker Tenure & Promotion Chen R. Carroll, Jun, Mueller- Harknett, Sherman, Wang, Pourahmadi Undergraduate Minors Wehrly Dabney, Hatfield, Kolodziej, Toby, Johnson, Sang, Dahm Undergraduate Service J.H. Carroll Longnecker Undergraduate Committee Wehrly Dabney, Hatfield, Kolodziej, Toby, Johnson, Sang, Liang Website Committee Schmiediche Longnecker, Sang, Katzfuss 81

FACULTY EDITORIAL SERVICE

Bhattacharya, Anirban Reviewer: Annals of Applied Statistics, Annals of Statistics, Bayesian Analysis, Bernoulli, Biometrika, Electronic Journal of Statistics, Journal of the American Statistical Association, Journal of Machine Learning Research

Chen, Willa Editorial Board Member: Journal of the American Statistical Association – T&M (2014-Present) Journal of Computational and Graphical Statistics (2009-Present) Electronic Journal of Statistics (2010-2013) Journal of the American Statistical Association – A&CS (2009-2012)

Cline, Daren Reviewer: Econometric Theory, Bernoulli, Stochastic Process and their Applications, Biometrika, ASCE Journal of Transportation Engineering, Electronic Journal of Statistics, Statistics and Probability Letters, Annals of Statistics, Journal of Difference Equations and Applications, Extremes, Journal of the American Statistical Association, Statistical Methodology, Cogent Mathematics

Dahm, P. Fred Reviewer: Agronomy Journal, American Journal of Public Health, American Statistician, Biometrics, Communications in Statistics, IEEE Transactions on Communications, Journal of the American Statistical Association, Psychometrika, Statistics and Probability Letters, Statistics in Medicine, Technometrics, Western Journal of Agricultural Economics

Hart, Jeff Editorial Board Member: Journal of the American Statistical Association (2008-2011, 1996-2002)

Huang, Jianhua Editorial Board Member: STAT—The ISI’s Journal for the Rapid Dissemination of Statistics Research (2015-Present)

Johnson, Valen Co-Editor: Bayesian Analysis (2010-2014) Associate Editor: Journal of the American Statistical Association (1992-1996, 2011-Present) Bayesian Analysis (2006-2010)

Jones, Edward R. Editorial Board Member: Journal of the American Statistical Association (2014-Present) Journal of Business and Economics Statistics (2012-Present) Statistics and Probability Letters (2008-2014)

Jun, Mikyoung Editorial Board Member: STAT, (2012-Present) Journal of Agricultural, Biological, and Environmental Statistics (JABES) (2011-Present) Journal of the Korean Statistical Society (2008-Present)

Katzfuss, Matthias Reviewer: Journal of Computational and Graphical Statistics, Journal of Computational and Graphical Statistics, Annals of Applied Statistics, Biometrics 82

Kolodziej, Elizabeth Book Review: Resampling Methods, Journal of the American Statistical Association

Liang, Hwa Chi Editorial Board Member: Missouri Journal of Mathematical Sciences (2013-Present)

Long, James Reviewer: Journal of the American Statistical Association, The Astrophysical Journal, Astronomy and Computing, Astronomy and Astrophysics

Mallick, Bani Editorial Board Member: Journal of Computational and Graphical Statistics (2004-Present) Biostatistics (2009-Present) SIAM/ASA Journal on Uncertainty Quantification (2013-Present) Chemometrics (2013-Present) Journal of Applied Mathematics and Stochastic Analysis (2005-2009)

Müller-Harknett, Ursula Editorial Board Member: Statistics and Probability Letters (2011-present).

Pourahmadi, Mohsen Editorial Board Member: Journal of the American Statistical Association (2014-Present) Journal of Business and Economics Statistics (2012-Present) Statistics and Probability Letters (2008-2014) Electronic Journal of Statistics (2010-2012) Journal of Applied Mathematics and Stochastic Analysis (2005-2009)

Sang, Huiyan Editorial Board Member: STAT (2013-Present)

Sherman, Michael Editorial Board Member: Journal of the American Statistical Association (2005-2014)

Sinha, Samiran Reviewer: Biological Psychiatry, Biometrics, Communication of Statistics, Computational Statistics and Data Analysis, Electronic Journal of Statistics, Journal of Applied Statistics, Journal of the American Statistical Association, Journal of Multivariate Analysis, Journal of the Nonparametric Statistics, Journal of the Royal Statical Society, Series B, Journal of the Statistical Planning and Inference, SCIENCE CHINA Mathematics, Stat, Statistics and its Interface, Statistics in Medicine

Spiegelman, Cliff Editorial Board Member: JASA (one month as acting T&M editor), Environmetrics, Journal of Chemometrics, Journal of Proteomics, Journal of Transportation Statistics, Journal of Transportation and Statistics

Subba Rao, Suhasini Editorial Board Member: Statistics (2012-Present)

Wang, Suojin Editor-in-Chief: Journal of Nonparametric Statistics (2007–2012) 83

Editorial Board Member: Biometrics (1997–2005) InterStat (1995–2009) Journal of Nonparametric Statistics (2004–2007, 2013–Present) Statistics & Probability Letters (2014–Present)

Wehrly, Tom Statistics and Probability Letters (1982–2007)

Zhou, Lan Reviewer: An International Journal, Annals of Applied Statistics, Biometrics, Biostatistics, Canadian Journal of Statistics, Computational Statistics and Data Analysis, Electronic Journal of Statistics, Journal of American Statistical Association, Journal of Computational and Graphical Statistics, Journal of Machine Learning Research, Journal of Nonparametric Statistics, Journal of Statistical Computation and Simulation, Journal of Statistical Planning and Inference, Journal of Statistical Theory and Practice, Life Data Analysis, Scandinavian Journal of Statistics, Statistical Applications in Genetics and Molecular Biology, Statistica Sinica

Primary Investigator Awards 2006-2013

Name Years Granting Agency Role Direct Indirect Total 2005-2008 National Aeronautics and Space PI $527,245 $44,835 $572,080 2005-2013 NIH - Training Grant PI $3,200,954 $199,464 $3,400,418 2007-2008 Baylor College of Medicine PI $21,023 $9,565 $30,588 Carroll, R. J. 2008-2011 University of Alabama PI $150,004 $5,472 $155,476 2012-2013 California Table Grape Comm. PI $2,126 $106* $2,232

2006-2007 NSF - Fractional Cointegration PI $42,405 $19,930* $62,335 NSF - Long Memory Time Chen, W. W. 2006-2010 Series PI $89,250 $40,610 $129,860 2010-2013 NSF-Restriciton Likelihood PI $119,682 $55,653 $175,335

2013-2016 NSF - NeTS Small PI $10,523 $4,946* $15,469 Cline, D. B.

2008-2011 Battelle Labs PI $422,846 $198,738* $621,584 Dept of Health and Human 2008-2012 Svcs PI $276,320 $125,727 $402,047 2008-2011 Pacific Northwest Natl Labs PI $427,528 $200,938* $628,466 2008-2011 American Inst. For Cancer Res. PI $76,835 $36,112* $112,947 Dabney, A. R. 2010-2011 Pacific Northwest Natl Labs PI $194,195 $91,272* $285,467 2011-2013 Natl Inst of Food and Agri. PI $2,362,466 $338,887 $2,701,353 2011-2013 NIH - Epigenetics of the Aging PI $312,501 $138,966 $451,467 2012 National Aeronautics and Space PI $8,712 $4,095* $12,807 2013- American Cancer Society PI $179,500 $84,365* $263,865

NSF - Cluster-Based 2006-2010 Bootstrapping PI $77,129 $35,538 $112,667 Hart, J. D. NSF-New Method for 2011-2013 Estimating Random Effects PI $100,040 $43,932 $143,972

Collaborative Research - 2006-2009 Statistical Learning PI $69,581 $29,402 $98,983 2009-2013 Conf. on Statistical Methods PI $18,407 $8,651* $27,058 Huang, J. 2012-2013 NSF - Collaborative Research PI $85,476 $27,852 $113,328 2013- Department of Defense PI $101,672 $47,786* $149,458

Name Years Granting Agency Role Direct Indirect Total NIH - Consistent Model 2012-2016 Selection PI $812,992 $310,708 $1,123,770 Johnson, V. E. UTMDCC - Reducing 2012-2013 Symptom PI $17,720 $3,281 $21,001

2009-2012 NSF - Nonstationary Spatial PI $51,148 $23,784 $74,932 Jun, M. 2012-2013 NSF - In-depth Development PI $103,126 $42,050 $145,176

2012-2013 US Dept of Agriculture PI $36,752 $17,274 $54,026 Longnecker, M.

NSF - Bayesian Nonlinear 2002-2006 Regression PI $21,977 $7,859 $29,836 NSF - ATD: Bayesian Data Mallick, B. 2009-2011 Missing PI $301,579 $53,821 $355,400 UTMDACC - Education 2012-2013 Experience Program PI $53,105 n/a $53,105

NSF - Efficient Estimation in Mueller-Harknett, 2009-2012 Semiparametric Regression PI $80,525 $37,445 $117,970 U.

NSF - Generalized Linear Pourahmadi, M. 2009-2011 Models PI $139,260 $55,473 $194,733

Dept. Of Health and Human 2007-2008 Svc. PI $66,887 $11,082 $77,969 Dept. Of Health and Human 2007-2008 Svc. PI $81,931 $35,124 $117,055 NIH - Development of a Sheather, S. J. 2007-2008 Controlled Hemorrhage PI $532,827 $250,429* $783,256 NSF - Texas Census Research 2012-2013 Ctr. PI $75,000 $35,250* $110,250 UTMDACC - Education 2012 Experience PI $33,142 n/a $33,142

2001-2006 NIH - Fetal Alcohol Exposure PI $32,357 $15,208* $47,565 Sherman, M. 2006-2013 NIH - Fetal Alcohol Exposure PI $357,171 $148,211 $505,382

Name Years Granting Agency Role Direct Indirect Total DOE - Thirteenth North American Meeting of New 2010-2011 Researchers PI $12,665 n/a $12,665 NIH - North American Meeting Sinha, S. 2010-2012 of New Researchers PI $27,962 n/a $27,962 NSF - Collaborative Research: 2010-2013 Statistics Methods PI $29,981 $13,942 $43,923 2013-2015 NCI - Innovative Approaches PI $57,871 $27,199* $85,070

2008-2012 NSF - Beyond Stationarity PI $124,312 $14,422 $138,734

Subba Rao, S. NSF - Fourier Methods in the 2011-2013 Analysis of Non-Stationary PI $89,833 $39,303 $129,136

NIH - Health Maintenance 2006-2009 Consortium PI $177,575 $83,460* $261,035 University of N. Carolina - Long 2003-2006 Term Care Needs PI $33,811 $15,891* $49,702 NIH - Program for Rural and Wang, S. 2007-2012 Minority Health Disparity PI $2,996,480 $1,408,346* $4,404,826 2008-2012 Baylor College of Medicine PI $193,724 $80,093 $273,817 Robert Wood Johnson 2008-2013 Foundation PI $438,836 $53,617 $492,453 2009-2011 Natl Inst of Mental Health PI $499,543 $234,785* $734,328

2006-2011 NSF - Integrated Undergraduate PI $185,068 $13,894 $198,962 Wehrly, T.

Zhou, L. NSF - Statistics Methods for 2009-2013 Complex Functional Data Pi $206,362 $88,130 $294,492

*Indirect costs estimated

Co-Principal and Collaborating Investigator Awards 2006-2013

(Please note that award totals in some instances refer to total grant amount, not amount received by individual collaborating investigators)

Name Years Granting Agency Role Direct Indirect Total National Institute for 2005-2006 Environmental Health Co-PI $34,025 $28,849 $62,874 NIH - Bayesian Models for 2005-2009 Gene Express Co-PI $57,630 $26,221 $83,851 2005-2013 NIH - Measurement Error Co-PI $451,740 $203,712 $655,452 Carroll, R. 2006-2007 NSF - Beowulf Cluster Co-PI $5,560 $278* $5,838 2009-2011 NSF - Cluster Computing Co-PI $14,849 $6,979* $21,828 NSF - Bayesian Data 2009-2013 Missing Co-PI $142,819 $27,249 $170,068 2010-2013 KAUST - IAMCS Co-PI $3,915,206 $1,200,000 $5,115,206 2012-2013 Columbia University Co-PI $56,285 $26,454* $82,739

National Science Dabney, A. R. 2010-2013 Foundation Co-PI $90,900 $3,846 $94,746

2006-2007 NSF - Beowulf Cluster Co-PI $5,560 $278* $5,838 Hart, J. D.

NSF - A New Approach of 2010-2013 Statistical Modeling Co-PI $109,553 $10,694 $120,247

Huang, J. NSF - Conf. on Resampling 2010-2011 Methods Co-PI $4,986 $2,343* $7,329 2011-2013 KAUST - IAMCS Co-PI $581,873 $273,480* $855,353

2008-2010 NSF - CMG Research Co-PI $81,790 $31,882 $113,672 Jun, M. 2011-2013 KAUST - IAMCS Co-PI $581,873 $273,480* $855,353

Name Years Granting Agency Role Direct Indirect Total NIH - Bayesian Models for Gene 2006-2009 Expression Co-PI $233,863 $106,408 $340,271 2006-2013 NIH - Measurement Error Co-PI $451,740 $203,712 $655,452 NIH - Nutrition, Biostatistics and 2001-2006 Bioinformatics Co-PI $18,490 $1,470 $19,960 NSF - CMG Research on Multiscale 2006-2007 Spatial Models Co-PI $55,443 $22,164 $77,607 NSF - CMG Research: Statistical 2006-2010 Analysis of Large Non-Gaussian Co-PI $174,430 $67,944 $242,374 Mallick, B. K. 2006-2007 NSF - Beowulf Cluster Co-PI $5,560 $278* $5,838 NSF - A Unified Framework for 2007-2009 Statistical Modeling Co-PI $44,858 $21,083* $65,941 2007-2011 NSF - Multiscale Data Integration Co-PI $324,267 $121,788 $446,055 2008-2013 Lawrence Livermore Natl Labs Co-PI $393,265 $184,835* $578,100 2010-2013 DOE - Bayesian Uncertainty Co-PI $357,162 $36,673 $393,835 2011-2013 KAUST - IAMCS Co-PI $581,873 $273,480* $855,353 DOE - Scalable Multilevel 2013-2016 Uncertainty Quantification Co-PI $6,811 $3,201* $10,012

2006-2008 NSF - Noyce Scholarship Co-PI $43,970 $20,666* $64,636 NSF - Center for the Appli. Of IT Newton, H. J. 2007-2008 in Teaching Co-PI $416,295 $195,659* $611,954 2007-2008 Supplemental to the ITS Ctr. Co-PI $22,101 $6,853 $28,954

NSF - A New Approach of 2010-2013 Statistical Modeling Co-PI $109,533 $10,694 $120,227 Sang, H. 2011-2013 KAUST - IAMCS Co-PI $581,873 $273,480* $855,353

2009-2013 NIH - Lipoprotein Density Co-PI $326,753 $66,822 $393,575 Sheather, S. J.

Wang, S. 2006-2007 NSF-Beowulf Cluster Co-PI $5,560 $278* $5,838

*Indirect costs estimated

Faculty Collaborations within Texas A&M

Raymond Carroll Nutrition and Food Science

Daren Cline Computer Science and Engineering Industrial and Systems Engineering

Alan Dabney Nutrition and Food Science Neuroscience and Experimental Therapeutics Mathematics Genetics

Jeffrey Hart Civil Engineering Petroleum Engineering

Jianhua Huang Industrial Engineering Electrical and Computer Engineering Physics and Astronomy Atmospheric Science Computer Science Economics Agriculture Economics Accounting Geography

Valen Johnson Sociology

Matthias Katzfuss Atmospheric Sciences Geography

Edward Jones Bush School of Government Veterinary Integrative Biosciences Veterinary Medicine and Central Texas Specialty Hospital Geography Horticultural Studies Sociology Hispanic Studies AgriLife College Station and AgriLife Stephenville Educational Administration

Mikyoung Jun Atmospheric Science Geography 90

Hwa Chi Liang Petroleum Engineering

James Long Mathematics Physics and Astronomy

Michael Longnecker Nutrition and Food Science Horticultural Sciences Entomology Ecosystem Science and Management Landscape Architecture and Urban Planning Nuclear Engineering Biology Small Animal Clinical Sciences

Bani Mallick Mathematics Petroleum Engineering Industrial Engineering Mechanical Engineering Material Science Nuclear Engineering Marketing Veterinary School Aerospace Engineering

Mohsen Pourahmadi Biostatistics and Epidemiology Mathematics

Huiyan Sang Health and Kinesiology Architecture Electrical and Computer Engineering Industrial and Systems Engineering

Simon Sheather Sociology Landscape Architecture and Urban Planning Information and Operations Management

Samiran Sinha Health Science Center

Cliff Spiegelman Entomology Civil Engineering

Suojin Wang Public Health Architecture Education and Human Development Pharmacy

Lan Zhou Animal Science Biochemistry Nutrition and Food Science Entomology

SCH per FTE and Student/Faculty Ratio Statistics Department Summary

SCH per Faculty FTE Student FTE to Faculty FTE Ratio (Excludes GATs FTE)

STAT RANK LD UD UG MS PHD TOTAL LD UD UG MS PHD TOTAL FALL Faculty 440.5 401.9 423.0 205.8 54.6 175.1 2009 GAT 508.0 294.8 332.4 137.4 Total 456.9 333.3 378.0 205.8 54.6 161.6 40.2 21.2 34.6 5.3 4.4 23.9

FALL Faculty 533.5 462.9 500.1 219.7 46.6 196.8 2010 GAT 357.0 249.7 268.4 114.9 Total 490.2 328.2 385.3 219.7 46.6 167.6 43.3 59.4 50.9 18.3 5.2 19.3

FALL Faculty 783.9 366.1 509.6 302.7 45.4 202.5 2011 GAT 591.0 281.7 329.3 101.9 Total 735.2 324.5 432.1 302.7 45.4 164.6 65.6 42.7 50.5 25.2 5.0 19.5

FALL Faculty 799.5 396.4 540.2 119.5 233.9 2012 GAT 507.0 348.8 379.1 161.9 Total 732.1 376.8 482.5 119.5 214.1 63.4 42.7 50.1 13.3 23.1

FALL Faculty 713.5 633.4 664.6 110.6 275.6 2013 GAT 468.0 702.0 585.0 46.8 Total 688.1 638.1 658.0 110.6 217.4 51.2 45.7 47.8 12.3 22.7

FACULTY SUMMARY 2009 2010 2011 2012 2013 I. Personnel a. Tenured and Tenure-Track 34 33 33 33 33 Faculty Professor 19 18 18 20 19 Assistant Professor 9 6 5 3 5 Associate Professor 4 7 7 7 6 Distinguished Professor 2 2 3 3 3 b. Non-Tenure-Track Faculty 8 6 9 13 13 Senior Professor 0 0 0 1 1 Executive Professor 0 0 0 1 1 Visiting Professor 1 1 3 2 3 Visiting Assistant Professor 0 0 1 1 1 Visiting Associate Professor 0 0 0 0 0 Lecturer 2 1 1 2 2 Senior Lecturer 5 4 4 6 5 c. Postdoctoral Fellows 16 17 7 10 13 d. Graduate Majors 170 170 184 162 162 e. Undergraduate Majors 0 0 0 0 0 f. Support Staff 15 18 18 16 16 II. Instructional Activities a. Graduate Semester Credit Hours 5,814 5,962 5,688 5,342 5,331 b. Undergraduate Semester Credit 14,300 14,571 14,599 15,800 16,992 Hours c. PhD Degrees 6 6 11 10 8 d. Masters Degrees 19 16 23 36 34 e. Undergraduate Degrees 0 0 0 0 0 III. Research Activities a. Research Publications 90 99 80 92 72 b. Research Presentations 143 129 143 99 94 c. Federal 3,724,360 3,726,479 4,049,321 3,562,405 3,173,948 d. State 0 0 135,434 67,441 39,807 e. Private/Non-Profit 195,926 185,024 173,888 128,339 558,599 f. Industrial/Corporate 0 0 0 0 0 g. International 3,468,746 1,749,042 1,749,042 1,749,042 492,881 h. Other Govt 95,198 42,445 28,142 719 1,407 Total 7,484,230 5,702,990 6,135,826 5,507,945 4,266,642

Goldplate Funding 2007-2015

FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 FY2013 FY2014 FY2015

Faculty Salaries $3,668,881 $3,785,045 $3,994,639 $4,097,517 $4,022,608 $3,886,025 $3,903,245 $4,035,427 $4,120,724

Summer Teaching $82,741 $82,741 $82,741 $82,741 $82,741 $41,741 $41,741 $41,741 $41,741

Staff $278,078 $290,591 $299,263 $304,237 $304,237 $235,677 $235,677 $249,975 $258,913

GAT/GANT $345,198 $345,198 $345,198 $345,198 $345,198 $142,270 $142,270 $142,270 $142,270

Operating $45,608 $117,508 $117,508 $117,508 $117,508 $103,830 $103,830 $103,139 $103,139

TOTAL $4,420,506 $4,621,083 $4,839,349 $4,947,201 $4,872,292 $4,409,543 $4,426,763 $4,572,552 $4,666,787

Budget Budget Reduction Reduction #1 #2

Semester Credit Hours Taught by Faculty Rank for Fall 2009

Undergraduate Graduate

Grand Rank 1XX 2XX 3XX 4XX Total MS PhD Total Total Professor 0 474 285 60 819 902 571 1,473 2,292 % of Level 0.0 16.7 8.1 44.4 12.7 49.0 61.1 53.0 24.8 % of Rank 0.0 20.7 12.4 2.6 35.7 39.4 24.9 64.3 100.0

Assoc. 0 438 0 0 438 465 168 633 1,071 Professor % of Level 0.0 15.4 0.0 0.0 6.8 25.2 18.0 22.8 11.6 % of Rank 0.0 40.9 0.0 0.0 40.9 43.4 15.7 59.1 100.0 Asst. Professor 0 441 332 0 773 177 88 265 1,038 % of Level 0.0 15.6 9.5 0.0 11.9 9.6 9.4 9.5 11.2 % of Rank 0.0 42.5 32.0 0.0 74.5 17.0 8.5 25.5 100.0 Subtotal 0 1,353 617 60 2,030 1,544 827 2,371 4,401 % of Level 0.0 47.7 17.6 44.4 31.4 83.8 88.4 85.4 47.6 % of Rank 0.0 30.7 14.0 1.4 46.1 35.1 18.8 53.9 100.0 Senior Lecturer 0 162 823 75 1,060 250 93 343 1,403 % of Level 0.0 5.7 23.5 55.6 16.4 13.6 9.9 12.4 15.2 % of Rank 0.0 11.5 58.7 5.3 75.6 17.8 6.6 24.4 100.0 Lecturer 0 558 0 0 558 0 0 0 558 % of Level 0.0 19.7 0.0 0.0 8.6 0.0 0.0 0.0 6.0 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Visiting 0 0 0 0 0 48 15 63 63 % of Level 0.0 0.0 0.0 0.0 0.0 2.6 1.6 2.3 0.7 % of Rank 0.0 0.0 0.0 0.0 0.0 76.2 23.8 100.0 100.0 Subtotal 0 720 823 75 1,618 298 108 406 2,024 % of Level 0.0 25.4 23.5 55.6 25.0 16.2 11.6 14.6 21.9 % of Rank 0.0 35.6 40.7 3.7 79.9 14.7 5.3 20.1 100.0 GATs - Lecture 0 762 2,064 0 2,826 0 0 0 2,826 % of Level 0.0 26.9 58.9 0.0 43.6 0.0 0.0 0.0 30.5 % of Rank 0.0 27.0 73.0 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 762 2,064 0 2,826 0 0 0 2,826 % of Level 0.0 26.9 58.9 0.0 43.6 0.0 0.0 0.0 30.5 % of Rank 0.0 27.0 73.0 0.0 100.0 0.0 0.0 0.0 100.0 Total 0 2,835 3,504 135 6,474 1,842 935 2,777 9,251

Semester Credit Hours Taught by Faculty Rank for Fall 2010

Undergraduate Graduate

Grand Rank 1XX 2XX 3XX 4XX Total MS PhD Total Total Professor 0 360 376 135 871 929 519 1,448 2,319 % of Level 0.0 12.0 10.6 100.0 13.0 48.4 62.8 52.8 24.6 % of Rank 0.0 15.5 16.2 5.8 37.6 40.1 22.4 62.4 100.0 Assoc. 0 660 398 0 1,058 503 177 680 1,738 Professor % of Level 0.0 22.0 11.2 0.0 15.8 26.2 21.4 24.8 18.4 % of Rank 0.0 38.0 22.9 0.0 60.9 28.9 10.2 39.1 100.0 Asst. Professor 0 618 285 0 903 207 66 273 1,176 % of Level 0.0 20.6 8.0 0.0 13.5 10.8 8.0 9.9 12.5 % of Rank 0.0 52.6 24.2 0.0 76.8 17.6 5.6 23.2 100.0 Subtotal 0 1,638 1,059 135 2,832 1,639 762 2,401 5,233 % of Level 0.0 54.6 29.8 100.0 42.3 85.5 92.2 87.5 55.4 % of Rank 0.0 31.3 20.2 2.6 54.1 31.3 14.6 45.9 100.0 Senior Lecturer 0 231 726 0 957 243 60 303 1,260 % of Level 0.0 7.7 20.4 0.0 14.3 12.7 7.3 11.0 13.4 % of Rank 0.0 18.3 57.6 0.0 76.0 19.3 4.8 24.0 100.0 Lecturer 0 596 0 0 596 0 0 0 596 % of Level 0.0 19.9 0.0 0.0 8.9 0.0 0.0 0.0 6.3 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Visiting 0 0 0 0 0 36 5 41 41 % of Level 0.0 0.0 0.0 0.0 0.0 1.9 0.5 1.5 0.4 % of Rank 0.0 0.0 0.0 0.0 0.0 88.9 11.1 100.0 100.0 Subtotal 0 827 726 0 1,553 279 65 344 1,896 % of Level 0.0 27.6 20.4 0.0 23.2 14.5 7.8 12.5 20.1 % of Rank 0.0 43.6 38.3 0.0 81.9 14.7 3.4 18.1 100.0 GATs - Lecture 0 536 1,775 0 2,311 0 0 0 2,311 % of Level 0.0 17.9 49.8 0.0 34.5 0.0 0.0 0.0 24.5 % of Rank 0.0 23.2 76.8 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 536 1,775 0 2,311 0 0 0 2,311 % of Level 0.0 17.9 49.8 0.0 34.5 0.0 0.0 0.0 24.5 % of Rank 0.0 23.2 76.8 0.0 100.0 0.0 0.0 0.0 100.0 Total 0 3,000 3,561 135 6,696 1,918 826 2,744 9,440

Semester Credit Hours Taught by Faculty Rank for Fall 2011

Undergraduate Graduate

Grand Rank 1XX 2XX 3XX 4XX Total MS PhD Total Total Professor 0 426 498 177 1,101 945 483 1,428 2,529 % of Level 0.0 14.6 14.5 100.0 16.9 51.2 58.5 53.4 27.5 % of Rank 0.0 16.8 19.7 7.0 43.5 37.4 19.1 56.5 100.0

Assoc. 0 0 413 0 413 353 139 492 905 Professor % of Level 0.0 0.0 12.0 0.0 6.3 19.1 16.8 18.4 9.8 % of Rank 0.0 0.0 45.6 0.0 45.6 39.0 15.4 54.4 100.0 Asst. Professor 0 585 344 0 929 9 41 50 979 % of Level 0.0 20.1 10.0 0.0 14.3 0.5 5.0 1.9 10.7 % of Rank 0.0 59.7 35.2 0.0 94.9 0.9 4.2 5.1 100.0 Subtotal 0 1,011 1,256 177 2,444 1,307 663 1,970 4,414 % of Level 0.0 34.7 36.6 100.0 37.5 70.8 80.4 73.7 48.0 % of Rank 0.0 22.9 28.4 4.0 55.4 29.6 15.0 44.6 100.0 Senior Lecturer 0 234 627 0 861 198 99 297 1,158 % of Level 0.0 8.0 18.3 0.0 13.2 10.7 12.0 11.1 12.6 % of Rank 0.0 20.2 54.1 0.0 74.4 17.1 8.5 25.6 100.0 Lecturer 0 1,077 0 0 1,077 0 0 0 1,077 % of Level 0.0 37.0 0.0 0.0 16.5 0.0 0.0 0.0 11.7 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Visiting 0 0 0 0 0 309 18 327 327 % of Level 0.0 0.0 0.0 0.0 0.0 16.7 2.2 12.2 3.6 % of Rank 0.0 0.0 0.0 0.0 0.0 94.5 5.5 100.0 100.0 Other 0 0 0 0 0 33 45 78 78 % of Level 0.0 0.0 0.0 0.0 0.0 1.8 5.5 2.9 0.8 % of Rank 0.0 0.0 0.0 0.0 0.0 42.3 57.7 100.0 100.0 Subtotal 0 1,311 627 0 1,938 540 162 702 2,640 % of Level 0.0 45.0 18.3 0.0 29.7 29.2 19.6 26.3 28.7 % of Rank 0.0 49.7 23.8 0.0 73.4 20.5 6.1 26.6 100.0 GATs - Lecture 0 591 1,550 0 2,141 0 0 0 2,141 % of Level 0.0 20.3 45.1 0.0 32.8 0.0 0.0 0.0 23.3 % of Rank 0.0 27.6 72.4 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 591 1,550 0 2,141 0 0 0 2,141 % of Level 0.0 20.3 45.1 0.0 32.8 0.0 0.0 0.0 23.3 % of Rank 0.0 27.6 72.4 0.0 100.0 0.0 0.0 0.0 100.0 Total 0 2,913 3,432 177 6,522 1,847 825 2,672 9,194

Semester Credit Hours Taught by Faculty Rank for Fall 2012

Undergraduate Graduate

Grand Rank 1XX 2XX 3XX 4XX Total MS PhD Total Total Professor 0 114 597 194 905 926 469 1,395 2,300 % of Level 0.0 3.6 16.3 100.0 12.9 53.1 61.5 55.6 24.1 % of Rank 0.0 5.0 26.0 8.4 39.3 40.3 20.4 60.7 100.0 Assoc. 0 717 233 0 950 400 193 593 1,543 Professor % of Level 0.0 22.6 6.4 0.0 13.5 22.9 25.3 23.6 16.2 % of Rank 0.0 46.5 15.1 0.0 61.6 25.9 12.5 38.4 100.0 Asst. Professor 0 357 0 0 357 0 0 0 357 % of Level 0.0 11.2 0.0 0.0 5.1 0.0 0.0 0.0 3.7 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 1,188 830 194 2,212 1,326 662 1,988 4,200 % of Level 0.0 37.4 22.7 100.0 31.4 76.0 86.8 79.3 44.0 % of Rank 0.0 28.3 19.8 4.6 52.7 31.6 15.8 47.3 100.0 Senior Lecturer 0 234 1,361 0 1,595 246 69 315 1,910 % of Level 0.0 7.4 37.2 0.0 22.7 14.1 9.0 12.6 20.0 % of Rank 0.0 12.3 71.3 0.0 83.5 12.9 3.6 16.5 100.0 Lecturer 0 1,248 0 0 1,248 0 0 0 1,248 % of Level 0.0 39.3 0.0 0.0 17.7 0.0 0.0 0.0 13.1 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Visiting 0 0 0 0 0 159 30 189 189 % of Level 0.0 0.0 0.0 0.0 0.0 9.1 3.9 7.5 2.0 % of Rank 0.0 0.0 0.0 0.0 0.0 84.1 15.9 100.0 100.0 Other 0 0 0 0 0 14 2 16 16 % of Level 0.0 0.0 0.0 0.0 0.0 0.8 0.3 0.6 0.2 % of Rank 0.0 0.0 0.0 0.0 0.0 87.5 12.5 100.0 100.0 Subtotal 0 1,482 1,361 0 2,843 419 101 520 3,363 % of Level 0.0 46.6 37.2 0.0 40.4 24.0 13.2 20.7 35.2 % of Rank 0.0 44.1 40.5 0.0 84.5 12.5 3.0 15.5 100.0 GATs - Lecture 0 507 1,472 0 1,979 0 0 0 1,979 % of Level 0.0 16.0 40.2 0.0 28.1 0.0 0.0 0.0 20.7 % of Rank 0.0 25.6 74.4 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 507 1,472 0 1,979 0 0 0 1,979 % of Level 0.0 16.0 40.2 0.0 28.1 0.0 0.0 0.0 20.7 % of Rank 0.0 25.6 74.4 0.0 100.0 0.0 0.0 0.0 100.0 Total 0 3,177 3,663 194 7,034 1,745 763 2,508 9,542

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Semester Credit Hours Taught by Faculty Rank for Fall 2013

Undergraduate Graduate

Grand Rank 1XX 2XX 3XX 4XX Total MS PhD Total Total Professor 0 780 0 213 993 1,263 571 1,834 2,827 % of Level 0.0 23.5 0.0 100.0 12.5 65.9 71.8 67.6 26.5 % of Rank 0.0 27.6 0.0 7.5 35.1 44.7 20.2 64.9 100.0 Assoc. 0 339 300 0 639 256 100 356 995 Professor % of Level 0.0 10.2 6.8 0.0 8.0 13.4 12.6 13.1 9.3 % of Rank 0.0 34.1 30.2 0.0 64.2 25.7 10.1 35.8 100.0 Asst. Professor 0 468 966 0 1,434 9 21 30 1,464 % of Level 0.0 14.1 21.8 0.0 18.0 0.5 2.6 1.1 13.7 % of Rank 0.0 32.0 66.0 0.0 98.0 0.6 1.4 2.0 100.0 Subtotal 0 1,587 1,266 213 3,066 1,528 692 2,220 5,286 % of Level 0.0 47.8 28.5 100.0 38.5 79.7 87.0 81.9 49.5 % of Rank 0.0 30.0 24.0 4.0 58.0 28.9 13.1 42.0 100.0 Senior Lecturer 0 0 2,235 0 2,235 201 84 285 2,520 % of Level 0.0 0.0 50.4 0.0 28.0 10.5 10.6 10.5 23.6 % of Rank 0.0 0.0 88.7 0.0 88.7 8.0 3.3 11.3 100.0 Lecturer 0 1,158 0 0 1,158 0 0 0 1,158 % of Level 0.0 34.9 0.0 0.0 14.5 0.0 0.0 0.0 10.8 % of Rank 0.0 100.0 0.0 0.0 100.0 0.0 0.0 0.0 100.0 Visiting 0 342 585 0 927 168 15 183 1,110 % of Level 0.0 10.3 13.2 0.0 11.6 8.8 1.9 6.7 10.4 % of Rank 0.0 30.8 52.7 0.0 83.5 15.1 1.4 16.5 100.0 Other 0 0 0 0 0 20 4 24 24 % of Level 0.0 0.0 0.0 0.0 0.0 1.0 0.5 0.9 0.2 % of Rank 0.0 0.0 0.0 0.0 0.0 83.3 16.7 100.0 100.0 Subtotal 0 1,500 2,820 0 4,320 389 103 492 4,812 % of Level 0.0 45.2 63.6 0.0 54.2 20.3 13.0 18.1 45.0 % of Rank 0.0 31.2 58.6 0.0 89.8 8.1 2.1 10.2 100.0 GATs - Lecture 0 234 351 0 585 0 0 0 585 % of Level 0.0 7.0 7.9 0.0 7.3 0.0 0.0 0.0 5.5 % of Rank 0.0 40.0 60.0 0.0 100.0 0.0 0.0 0.0 100.0 Subtotal 0 234 351 0 585 0 0 0 585 % of Level 0.0 7.0 7.9 0.0 7.3 0.0 0.0 0.0 5.5 % of Rank 0.0 40.0 60.0 0.0 100.0 0.0 0.0 0.0 100.0 Total 0 3,321 4,437 213 7,971 1,917 795 2,712 10,683

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History of Courses Taught: Statistics Department Fall 2007 Fall 2008 Fall 2009 Fall 2010 Fall 2011 Fall 2012 Total Total Average Sections Enrollment Sections Enrollment Sections Enrollment Sections Enrollment Sections Enrollment Sections Enrollment Sections Enrollment Enrollment STAT Elem Stat 3 173 4 240 3 254 3 256 2 209 3 246 18 1,378 77 201 Inference STAT Prin of Stat I 12 546 10 591 10 592 9 622 6 634 6 697 53 3,682 69 211 STAT Prin of Stat II 1 58 1 77 2 99 2 122 2 128 2 116 10 600 60 212 STAT Intro to 2 85 2 75 2 87 2 74 2 77 2 95 12 493 41 301 Biometry STAT Statistical 13 611 13 598 13 610 13 615 12 589 13 634 77 3,657 47 302 Methods STAT Statistical 10 488 12 462 10 444 10 479 10 478 10 492 62 2,843 46 303 Methods STAT Sample 1 26 1 20 1 27 1 19 4 92 23 307 Survey Tcnq STAT Principles 1 9 1 12 1 17 1 10 1 22 1 23 6 93 16 407 Sample Surv STAT Math 1 30 1 39 1 20 1 35 1 37 1 41 6 202 34 414 Statistics I STAT Directed 1 2 1 2 2 485 Studies STAT Statistical 3 54 2 37 2 41 2 44 2 48 2 59 13 283 22 601 Analysis STAT Stat Comp 1 28 2 30 2 35 2 41 7 134 19 604 Anly Prob Statistical 2 63 2 63 4 126 32 Computations STAT Sampling 2 11 2 9 2 16 2 9 2 10 3 24 13 79 6 607 STAT Distribution 2 90 2 94 4 184 46 610 Theory Thry of 2 83 2 72 2 98 3 93 9 346 38 Statistics I STAT Thry of Linear 1 30 1 12 1 28 1 16 1 14 1 15 6 115 19 612 Models STAT Intermed Thry 1 24 1 24 24 613 of Stat STAT Adv Thry of 1 6 1 21 1 13 3 40 13 614 Statistics Probability for 1 14 1 13 2 27 14 Stat STAT Stochastic 1 10 1 12 1 8 1 6 1 15 5 51 10 615 Processes STAT Stat Mach 1 21 1 21 21 618 Learn & Mining STAT Stat Large 1 15 1 22 2 37 18 620 Sample Thry 102

STAT Stat Meth for 1 6 1 6 6 623 Chem STAT Overview of 2 56 2 40 3 53 3 58 3 57 2 49 15 313 21 630 Math Stat STAT Stat Decision 1 19 1 26 1 10 1 27 4 82 20 632 Thry Stat Meth II 1 13 1 14 2 27 14 Bayes Model STAT Meth 2 18 2 45 2 27 2 27 2 26 2 41 12 184 15 636 Multivariate Anly STAT Methods of 2 55 2 29 2 49 2 25 2 31 2 29 12 218 18 641 Stat I STAT Biostatistics I 1 18 2 10 1 6 1 5 1 4 6 43 7 643 STAT Appl Biostat & 2 8 3 17 5 25 5 645 Data Anly STAT Spatial 1 8 1 6 1 8 1 19 1 15 1 8 6 64 11 647 Statistics STAT Applied Stat & 1 17 1 11 1 11 3 39 13 648 Data Analys STAT Stat in 5 235 5 291 6 208 5 185 5 207 4 170 30 1,296 43 651 Research I STAT Stat in 4 86 3 91 3 89 4 92 3 53 3 74 20 485 24 652 Research II STAT Stat in 2 17 2 17 8 653 Research III STAT Advanced 2 26 2 24 2 27 2 46 8 123 15 657 Programming Sas STAT Transportation 1 11 1 11 2 22 11 658 Statistic STAT Statistical 1 3 1 7 2 10 5 661 Genetics STAT Stat Data 1 3 1 3 2 6 3 671 Modeling I STAT Time Series 1 14 1 16 1 9 3 39 13 673 Anly I STAT Seminar 2 30 2 31 3 37 2 38 2 38 2 40 13 214 16 681 STAT Professional 2 18 2 16 3 22 4 25 3 14 3 14 17 109 6 684 Internshp STAT Directed 11 15 12 16 7 13 9 14 7 17 5 13 51 88 2 685 Studies STAT Special 2 20 2 20 5 39 2 13 1 4 2 10 14 106 8 689 Topics in STAT Research 12 21 19 41 22 47 20 54 20 49 19 40 112 252 2 691 Total 105 2,890 117 3,019 116 3,036 117 3,122 105 3,044 101 3,166 661 18,277 985

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IV. APPENDIX

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APPENDIX A.

MS Statistics and Online Programs

In Fall 2007, under the direction of Mike Speed, Director and Simon Sheather, Department Head, the department’s first cohort of 20 students were enrolled in the Distance Learning MS in Applied Statistics program. In 2008, the Transcripted Certificate of Applied Statistics was introduced. In 2009, a joint Texas A&M University/SAS certificate was approved with currently 116 students having received a certificate. This same year, we celebrated our first graduate of the program and the number of supported on-campus graduate students was expanded with the introduction of Technology Teaching Assistants. In the last academic year there were over 1000 enrollments in graduate level Statistics courses online with 117 professionals having completed their MS degree in Statistics. In terms of student quality, more than 90% of distance learning students to date have passed the Masters Qualifying Exam at their first attempt. Our alumni have proven successful by moving on to excel in their fields as vice presidents, teachers, engineers, analysts and scientists working for fortune 500 companies such as, Intel Corp, Chevron, Bank of America and Amgen. Below is a selection of the employers of our graduates.

Addx Corporation Deloitte Advanced Analytics at Cardinal Health Denton High School Amgen eBay Enterprise Armstrong World Industries Ericsson AT&T Gallagher Benefit Services Audimation Services, Inc. Highmark Health Bank of America Humble ISD BBA Solutions IMS Health Biomedical Research Foundation INC Research Boeing Commercial Airplanes Infinity Property & Casualty Company CA Technologies Informatics Centre of Excellence, Cancer Care Ontario Capital One Financial Corp., Plano Intel Corporation Chevron Investment Solutions Group Chief Business Office - Veterans Health Janus Capital Collin College KLAS Enterprises Computer Sciences Corporation Korn Ferry Continuum Analysis Laboratory Corporation of America Corning Incorporated Lake Region Medical CRO Leidos Biomedical Research, Inc for NCI Cyberonics

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Mathnasium RVA Medtronic Montgomery High School National Oilwell Varco (NOV) Newmont Mining Corporation North Shore Long Island Jewish Health System Pearson North America PPD PRA International Pros QBE First Rigid Closed Top Division Royal Bank of Canada RTI International Sandia National Laboratories SAS Slalom Consulting SpectraCell Laboratories, Inc St. Jude Medical SUNY Adirondack College SUNY Upstate Clinical Campus Systems Kinetics The EMMES Corporation TheHunt.com Transamerica U. S. Air Force U. S. Department of State U. S. Gypsum Co. University of Houston University of Kansas Medical Center University of Washington University of Washington - Dept of Surgery UPC Cablecom Utah Insurance Group Vanderbilt University Medical Center Washington University, St. Louis Zurich North America

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In 2011, Mike Speed retired as Director and Simon Sheather took on this role, as well as continued his role as Department Head. From 2006-2013, more than 10 new graduate courses were introduced. The following is a complete list of courses that have been offered at a distance, including the new courses that were designed specifically for distance delivery. The courses marked * are new courses. • STAT 601 Statistical Analysis • STAT 604 Topics in Statistical Computations • STAT 607 Sampling • STAT 608 Regression Analysis • STAT 626 Methods in Time Series Analysis • STAT 630 Overview of Mathematical Statistics • STAT 636 Methods in Multivariate Analysis • STAT 638 Introductions to Applied Bayesian Methods* • STAT 641 The Methods of Statistics I • STAT 642 The Methods of Statistics II • STAT 643 Biostatistics I • STAT 645 Applied Biostatistics and Data Analysis* • STAT 646 Statistical Bioinformatics* • STAT 651 Statistics in Research I • STAT 652 Statistics in Research II • STAT 653 Statistics in Research III • STAT 656 Applied Analytics Using SAS Enterprise Miner* • STAT 657 Advanced Programming Using SAS* • STAT 659 Categorical Data Analysis • STAT 681 Seminar • STAT 684 Consulting Credit • STAT 685 Directed Studies

Since the program’s inception and in light of the rapid growth, the need for more faculty and staff was imperative to continue the program’s success. In fall 2007, the program operated with a director, one part-time program coordinator, an IT specialist and six faculty to teach our online students. In 2008/2009, with applications increasing, and our enrollment more than quadrupling the first year, the need to hire a full time program coordinator, business coordinator to handle accounting and a software specialist to assist the IT specialist was eminent. At this time, the number of courses being taught had increased to thirteen and the number of faculty teaching were ten. To date, with the continued increase in numbers and ultimate success of the Distance

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Learning MS in Applied Statistics program, certificate and non-degree seeking students, there are more than 500 students enrolled taking more than 1000 graduate level statistics courses. Currently, this entire program is run with an academic director, program manager, administrative assistant, a chief of operations and software specialist who oversee technology and 16 TTAs who aid in the set up and recording of classes. In addition, there is a business coordinator who splits her time with other programs. There are currently ten faculty teaching seventeen courses. The table below summarizes the course enrollments in distance education each semester since the Fall 2008 semester.

Semester In State Out of State Total Fall 2008 105 87 192 Fall 2009 123 157 280 Fall 2010 186 224 410 Fall 2011 167 269 436 Fall 2012 173 274 447 Fall 2013 176 233 409 Fall 2014 271 300 571

Spring 2009 100 106 206 Spring 2010 129 152 281 Spring 2011 137 221 358 Spring 2012 147 269 416 Spring 2013 171 260 431 Spring 2014 211 254 465 Spring 2015 253 292 545

Summer 2009 87 92 179 Summer 2010 66 101 167 Summer 2011 84 145 229 Summer 2012 132 156 288 Summer 2013 140 143 283 Summer 2014 179 141 320 Summer 2015 200* 146* 346*

*Projected numbers

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The table below summarizes graduates by calendar year.

2009 2

2010 11 2011 13 2012 26 2013 27 2014 38 2015 46*

*Projected numbers

The table below summarizes the number of certificates completed by calendar year.

2008 2 2009 8 2010 7 2011 22 2012 35 2013 19 2014 19

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APPENDIX B.

MS ANALYTICS OVERVIEW

THE NEED FOR ANALYTICS The U.S. is suffering through a shortage of people with deep analytical skills to analyze big data, an issue deeply impacting corporations. By 2018, that gap is expected to reach between 140,000 and 190,000, according to the McKinsey Global Institute. In order to regain a competitive advantage, businesses need to retrain the talent currently in place.

THE HISTORY OF THE PROGRAM Approvals Needed to Offer the MS Analytics Degree

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The Department of Statistics has teamed with the Mays Business School to offer a Master of Science in Analytics, ideal for corporate managers and professionals. The degree is geared towards those with expertise in a wide array of industries: oil & gas, retail, healthcare, electronics, and energy.

The program will culminate in a quantitative analysis project specific to your employer. The part-time, five-semester program will provide graduates with comprehensive and balanced training in statistical and business processes. We’re looking to produce data scientists who are thought leaders and innovators

THE MODERN SKILL-SET • Business Acumen to ask the RIGHT business question. • Deep Analytical Skills such as market analysis, predictive modeling, web analytics, risk analysis, forecasting • Technical Expertise such as programming, data warehousing, mining, and visualization • Soft Skills such as teamwork, communication, and presentation skills

CURRICULUM • 75% Statistics and 25% Business.

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LOCATION CITYCENTRE, HOUSTON

Our program is taught Tuesday and Thursday evenings in-person at Houston's CITYCENTRE (I-10 & Beltway 8). The CityCentre facility was designed by a team of faculty, staff and students to be the ideal environment for executive learning.

We also offer the degree at a distance via live video stream for individuals outside of a 50-mile radius of Houston throughout North America (USA, Mexico, Canada). Live video participants will interact with students and faculty in Houston and are required to appear in-person twice: a 3-day orientation in Week 0 and in their final semester to present their capstone project. Our goal is to replicate the classroom experience, even if you are not in Houston. In addition to giving students the ability to join live classes via video, we record each class. The flexible delivery ensures you won’t miss any material in the event you are unable to make it to class or have to travel for work.

ADMISSION Admission to the Texas A&M Masters in Analytics program is highly competitive. Strong candidates must meet the following criteria and qualifications: • Grades o Competitive undergraduate or graduate GPA or strong GRE/GMAT scores • Statistics Competency o Completed at least one statistics course with an A or B • Work Experience o At minimum 3 years of full-time work experience • Purpose o A well-written statement of purpose about how this analytics degree will help your organization • Organizational Support o Support from current employer for access and mentorship with a business problem and large data set

REQUIRED APPLICATION MATERIALS • Completed pre-questionnaire (http://analytics.stat.tamu.edu/#contact) • 3 letters of recommendation or 3 recommendation forms (http://www.stat.tamu.edu/dist/Graduate_Letter_of_Rec.pdf) • Unofficial GRE/GMAT scores if available (may be waived after transcript review) • Unofficial college transcripts • Current résumé Once your complete information is reviewed by a committee, you will receive additional instructions regarding the official application process, should you progress to this stage.

Prior to final admission, all candidates will be required to interview.

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COST The total cost of a Masters in Analytics degree is $50,000 ($10,000 per semester), which includes tuition, required fees, books, supplies, hotel and meals during orientation, and a laptop preloaded with all necessary software. No assistantships or scholarships are available at this time. Given the value added to your organization through the unique work-based project, we strongly suggest that enrollees request sponsorship from their employer for the degree.

COMPETITION In just 2 years has grown from a handful to over 90 data science and analytics programs.

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APPENDIX C.

Proposal for an Undergraduate Major in Statistics.

In the summer of 2014, the Department voted to develop an undergraduate degree program in Statistics. The overall curriculum was designed during the fall semester. Various faculty members developed nine new undergraduate courses to be included in the curriculum. Notable aspects of the curriculum are nine required courses and two elective courses in statistics, four required and two elective courses in mathematics, two elective computer science courses, and four elective courses in an outside specialization area. First-year students will take an overview course that introduces the students to the field of statistics. The curriculum is designed to be flexible, allowing a student, in conjunction with the undergraduate advisor, to develop a program that meets the student’s needs. For example, a student planning to go to graduate school in statistics could take four additional mathematics courses as the outside specialization area. A student who wished to work in genomics would take biologically oriented mathematics and statistics electives and would have biology/genetics as the outside specialization area. All students will be required to take a writing-intensive capstone course. The program was approved by the College of Science Undergraduate Curriculum Committee in March 2015. The TAMU Undergraduate Curriculum Committee will consider the program during their April 2015 meeting. We anticipate that students will be able to enroll in the program in Fall 2016 with an annual enrollment of more than 60 new students per year. A document describing the program and its motivation follows. Pending approval at the University level, this document will be forwarded to the Texas Higher Education Coordinating Board for final approval of the undergraduate major.

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Texas A&M University

Bachelor of Science with a major in Statistics

Program Review Outline

BACKGROUND & PROGRAM DESCRIPTION

Administrative Unit: Department of Statistics, College of Science

The educational objectives of the new program are: master the depth of knowledge required for the degree; work effectively with data; demonstrate critical thinking; communicate effectively; practice personal and social responsibility; demonstrate social, cultural, and global competence; prepare to engage in lifelong learning; work collaboratively. Evaluation will be done via performance metrics on required coursework, in addition to data we will collect on the students after they have completed the program. For more details, see the main proposal document.

The program curriculum will include existing courses in the Departments of Statistics, Mathematics, Computer Science and Engineering, and Industrial and Systems Engineering. In addition, the Department of Statistics will develop ten new courses for the program.

The proposed implementation date is Fall 2016.

Texas A&M University certifies that the proposed new degree program meets the criteria under the 19 Texas Administrative Code, Section 5.45 in regards to need, quality, financial and faculty resources, standards and costs. New costs during the first five years will not exceed $2 million.

I. NEED

A. Employment Opportunities

Statisticians are in demand in all sectors of society. Statisticians use statistical methods to collect and analyze data and help solve real-world problems in business, engineering, the sciences, and other fields. Nearly every agency in the federal government employs statisticians. Biostatisticians work in pharmaceutical companies, public health agencies, and hospitals. In business, statisticians design experiments for product testing and development. Actuaries use mathematics, statistics, and financial theory to study uncertain future events, especially those of concern to insurance and pension companies.

In a 2009 NY Times article, statistics was cited as being a rapidly expanding field, with employers such as Google and IBM hiring increasing numbers from the field. “I keep saying that the sexy job in the next 10 years will be statisticians. And I’m not kidding.”2 Hal Varian,

2 Lohr, Steve. “For Today’s Graduate, Just One Word: Statistics.” New York Times. 5 August 2009. 116

chief economist at Google. “Data availability is going to continue to grow. To make that data useful is a challenge. It’s generally going to require human beings to do it,” according to Dr. Varian.

The Texas Workforce Commission currently lists 500 jobs with the keyword of “statistics” (searched July 11, 2014). According to The Wall Street Journal’s Numbers Guy, Carl Bialik, as of March 2013, there were 28,305 postings for jobs in statistics, analytics, and “big data” at the jobs website icrunchdata; this was up from 16,500 three years earlier.4

McKinsey Global Institute published a study in May 2011 entitled “Big Data: The next frontier for innovation, competition, and productivity” that predicts “by 2018 the US will have a shortage of 140,000 – 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with know-how to use the analysis of big data to make effective decisions.”5

In December 2014, LinkedIn published a list of the year’s “hottest skills” for recruiting on the site. Statistical analysis and data mining was listed as number one.6

B. Projected Enrollment We anticipate enrollments of 25, 45, 55, 60, and 65 students in the first five years, respectively. At steady state, we expect annual enrollments of 65 students, for an approximate total of 260 students in the program.

C. Existing State Programs Rice University, Baylor University, the University of Texas at San Antonio, Southern Methodist University, and the University of Houston-Downtown all offer B.S. degrees in statistics. However, the Department of Statistics at Texas A&M would be the only large statistics department in Texas to offer a B.S. degree in statistics. The Department of Mathematics already offers an Applied Mathematical Sciences (APMS) degree that offers specialization in, among other things, statistics. However, there are very few students in the statistics track (5 or fewer a year), so we expect the vast majority of students pursuing a statistics degree to be new students.

3 http://www.bls.gov/oes/2013/may/oes152041.htm http://www.bls.gov/ooh/math/statisticians.htm 4 http://online.wsj.com/articles/SB10001424127887323478304578332850293360468 5 http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation 6 http://talent.linkedin.com/blog/index.php/2014/12/the-25-hottest-skills-to-recruit-for-on-linkedin 117

II. QUALITY & RESOURCES

A. Faculty The Department of Statistics has an adequate number of faculty for teaching the program’s courses in the first two years, since many elective courses will not be needed in the first two years of the program. Rather, during the first two years of the program, students in the new program will take courses that are currently offered as service courses. We have requested new faculty positions, to begin in the third year, and these new faculty will be responsible for teaching the remaining elective courses. Courses will be assigned to faculty by matching course content to faculty interests and areas of expertise. The duties of current faculty that are reassigned will be met by reducing their teaching duties in the graduate program. We anticipate that this reassignment can be managed to have a minimal effect on the graduate programs of the department. The required courses outside the Department of Statistics are existing courses on the TAMU College Station campus.

B. Program Administration Academic advising will be provided by the Director of Undergraduate Programs as well as by a new full-time staff member dedicated to academic advising. An existing staff member will have one quarter of their time reassigned to assist with administrative tasks for the program.

C. Other Personnel None.

D. Supplies, Materials No special supplies or materials will be necessary.

E. Library No additional library resources will be necessary.

F. Equipment, Facilities The program will use existing facilities of the Department of Statistics and the College of Science for classroom, office space, and computer labs. Facilities and equipment will be made available and adequate to conduct this program and to ensure quality in teaching and learning, and be consistent with standards of similar programs in Texas and the US.

G. Accreditation Texas A&M is current with institutional accreditation by the Southern Association of Colleges and Schools. There are no specialized accreditation agencies currently available for undergraduate statistics.

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Catalog Description

Statistics is the science of collecting and analyzing data for the purpose of making confident decisions in the presence of uncertainty. Large and complex data sets are ubiquitous in the modern day and age, and statisticians are in high demand. Multidisciplinary application areas vary widely and include health and medicine, business, physical sciences, engineering, environmental studies, and government. The curriculum in statistics provides training in all necessary areas, including a mathematical and probabilistic foundation, strategies for designing studies and collecting data, the visualization and analysis of data using popular software such as SAS and R, and the process of using sample data to draw confident conclusions about a population. Depending on the electives selected, a student completing this program will be prepared to enter employment as a statistical analyst or continue to graduate school in statistics or a related field.

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Curriculum in Statistics

FRESHMAN YEAR

First Semester (Th-Pr) Cr Second Semester (Th-Pr) Cr ENGL 104 Composition (3-0) 3 HIST 106 History of the U.S. (3-0) 3 and Rhetoric HIST 105 History of the (3-0) 3 MATH 172 Calculus (4-0) 4 U.S. MATH 171 Analytic (4-0) 4 STAT 182 Foundations of (1-0) 1 Geometry and Calculus Statistics Science Elective1 4 Computer science elective2 4 Science Elective1 4 14 16

SOPHOMORE YEAR

First Semester (Th-Pr) Cr Second Semester (Th-Pr) Cr Communication (3-0) 3 MATH 304 Linear Algebra (3-0) 3 requirement3 MATH 221 Several (4-0) 4 POLS 207 State and Local (3-0) 3 Variables Calculus Government POLS 206 American Natl. (3-0) 3 STAT 212 Principles of Statistics II (3-0) 3 Government STAT 211 Principles of (3-0) 3 Computer science elective2 4 Statistics I Science Elective1 3 Elective hours4 3 16 16

JUNIOR YEAR

First Semester (Th- Cr Second Semester (Th-Pr) Cr STAT 404 Statistical (3-0) 3 STAT 408 Linear Models (3-0) 3 Computing STAT 414 Mathematical (3-0) 3 STAT 415 Mathematical (3-0) 3 Statistics I Statistics II Mathematics elective5 3 Outside specialization elective6 3 Outside specialization 3 Elective hours4 6 elective6 Elective hours4 3 15 15

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SENIOR YEAR

First Semester (Th-Pr) Cr Second Semester (Th-Pr) Cr STAT 406 Design and (3-0) 3 STAT 482 Capstone Course in (3-0) 3 Analysis of Experiments Statistics Mathematics elective5 3 Statistics elective7 3 Statistics elective7 3 Outside specialization elective6 3 Outside specialization 3 Elective hours4 4 elective6 Elective hours4 3 15 13

Notes:

1. Two lower-level science courses are to be selected from ASTR 111; BIOL 111; BIOL 112; CHEM 101/111 or CHEM 103/CHEM 113; CHEM 102/CHEM 112 or CHEM 104/CHEM 114; PHYS 208; PHYS 218. A third science course is to be selected from any course satisfying the life and physical sciences requirement for the University Core Curriculum. 2. Select 8 hours from CSCE 110, CSCE 111, CSCE 121, or CSCE 206. 3. Select 3 hours from COMM 203, COMM 205, or COMM 243, which fulfills the communication requirement for the University Core Curriculum. 4. Three elective hours must be chosen from the approved University Core Curriculum list for language, philosophy and culture, three elective hours must be chosen from the approved University Core Curriculum list for creative arts, and three elective hours must be chosen from the approved University Core Curriculum list for social and behavior sciences. In addition, 6 hours of courses must be in the area of international and cultural diversity. These may be in addition to University Core Curriculum courses, or if a course in this category satisfies an area or the Core, it can be used to meet both requirements. 5. Students must take at least one course from the following courses: MATH 220, MATH 308, MATH 409, MATH 410, MATH 417 or MATH 437, MATH 442, MATH 446, MATH 447, MATH 469, ISEN 420, ISEN 421, ISEN 424. The student must take a total of at least 12 hours of mathematics and statistics elective courses. 6. Students must take 12 hours in an outside specialization area upon approval by a departmental advisor. At least 6 hours must be upper level hours. 7. Students must take at least two courses from the following courses: STAT 407, STAT 426, STAT 436, STAT 438, STAT 445, STAT 446, STAT 459, STAT 485, STAT 489, STAT 491, ISEN 314. The student must take a total of at least 12 hours of mathematics and statistics elective courses.

*If a grade of D or F is earned in any of the following courses, MATH 151/MATH 171, MATH 152/MATH 172, MATH 221/MATH 251/MATH 253, MATH 220, MATH 323, MATH 308, STAT 211, or STAT 212, this course must be immediately retaken and a grade of C or better earned. The department will allow at most two D’s in upper-level (325-499) courses. If a third D is earned, one of the three courses in which a D was earned must be retaken and a grade of C or better earned.

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APPENDIX D.

Postdoctoral Training Program in Biostatistics, Bioinformatics and the Biological Basis of Nutrition and Cancer

Director: Raymond J. Carroll

In 2001, the Department of Statistics was awarded A National Cancer Institute (NCI) R25T grant (CA-R25T090301: Postdoctoral Training Program in Biostatistics, Bioinformatics and the Biological Basis of Nutrition and Cancer, Raymond J. Carroll, P.I.). This multidisciplinary grant included investigators from the Department of Statistics, the Department of Electrical and Computer Engineering, and the Faculty of Nutrition. The associate director of the grant, Dr. Nancy Turner, is now a professor in the Department of Nutrition and Food Sciences. Department of Statistics mentors have included Bani Mallick, Jianhua Huang, Alan Dabney, Marina Vannucci, and Naisyin Wang. The Program has received $500,000 per year in direct costs, and has also had substantial matching funds from the College of Science, the College of Engineering, and the College of Agriculture and Life Sciences. The purpose of the grant was to train postdoctoral statisticians and electrical engineers on the role of nutrition in cancer development. The 6 investigators in Nutrition, all lab-based biochemists, serve as mentors for all trainees. The trainees first visit 3 laboratories for a month each, and then select a mentor for the rest of their time in the program. They spend approximately 20% of their time physically in the lab of their nutrition mentors and are provided offices within the Department of Statistics or the Department of Electrical and Computer Engineering. The trainees spend 2-3 years in the program, and there are 4 trainees in any given year. NCI requires all trainees to be U.S. citizens or permanent residents. To date, there have been 26 trainees, including current ones. They are listed below. Most of them left the program with at least one first-authored paper in a nutrition or cancer journal. The substantial direct exposure to a lab means that many of the trainees have a very deep understanding of the biological issues around nutrition and cancer, and the technologies associated with them. The Program was renewed in 2006 and 2011, with almost perfect scores each time. These scores reflect that the trainees are actually contributing to our understanding of nutrition and cancer. We had every expectation of renewal in 2016, but unfortunately the NCI withdrew the Program Announcement in 2013, and there is no possibility of submitting a renewal. We are contemplating submitting a “renewal” but for the only mechanism possible, a T32, although the amount of funding available to support postdocs via a T32 is much less than for the R25T. There is also a possibility that the Cancer Prevention Institute of Texas (CPRIT), a State of Texas agency, will announce a competition for training programs.

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Current and Past Trainees

Trainee Ph.D. Current Title Current Employment Aniruddha Datta University of Southern California J.W. Runyon, Jr. ’35 Professor II TAMU Electrical & Computer Engineering Danh Nguyen UC Davis, California Professor University of California, Irvine Medical School Qi Zheng Texas A&M University Associate Professor TAMU School of Public Health Mahlet Tadesse Harvard University Associate Professor Georgetown College Kimberly Drews Texas Tech University Associate Research Professor George Washington University Wenjiang Fu University of Toronto Professor University of Houston Ivan Ivanov University of South Florida Clinical Associate Professor TAMU, School of Veterinary Medicine Michael Swartz Rice University Assistant Professor University of Texas, School of Public Health Erchin Serpedin University of Virginia Professor TAMU Electrical and Computer Engineering Sujay Datta University of Connecticut Associate Professor University of Akron Lan Zhou University of California Associate Professor TAMU Department of Statistics Ann Chen Medical University of S. Carolina Assistant Member Moffitt Cancer Center Xiaoning Qian Yale University Assistant Professor University of South Florida Ivan Zorych Rutgers University Unknown Recently at Columbia University with D. Madigan Yuliya Kaprievitch Medical University of S. Carolina Lecturer University of Tasmania Scott Schwartz Duke University Research Associate University of Texas, Austin Nikolay Bliznyuk Cornell University Assistant Professor University of Florida Carmen Tekwe University of Buffalo Assistant Professor TAMU School of Public Health Tanya Garcia Texas A&M University Assistant Professor TAMU School of Public Health Xiangfang Li Rutgers University Assistant Professor Prairie View A&M University Maria Joseph Iowa State University Senior Statistician General Dynamics Information Technology Amin Zollanvari Texas A&M University Assistant Professor Electronic Engineering Istanbul Kemerburgaz University Roger Zoh Iowa State University Research Assistant Professor TAMU School of Public Health Houssein Assaad The University of Texas at Dallas Research Assistant Professor STATA Corporation Daniel Mohsenizadeh Texas A&M University Research Assistant Professor TAMU Electrical and Computer Engineering Mathew McLean Cornell University Research Assistant Professor TAMU Department of Statistics

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APPENDIX E.

Institute for Applied Mathematics and Computational Science (IAMCS) and the Department of Statistics

The Institute for Applied Mathematics and Computational Science (IAMCS) was founded in 2008 with James A. Calvin (Statistics) as the Director. The IAMCS received substantial funding for a 6-year contract from the King Abdullah University of Science and Technology in Saudi Arabia (KAUST), the only western style university in that country. In 2010 Dr. Calvin took a position at KAUST, and Raymond J. Carroll became the new Director, a position he still holds. The IAMCS had members from many colleges in the University, particularly the College of Science, the College of Engineering and the College of Geosciences. The great majority of the initial members were from the Departments of Statistics, Mathematics and Computer Science and Engineering. In Statistics, the members have included Bani Mallick, Jianhua Huang, Valen Johnson, Suojin Wang, Marc Genton, Faming Liang, Mikyoung Jun, Huiyan Sang and Yanyuan Ma. Coincidental with the KAUST contract, the IAMCS also participated in a university-wide competition to select senior hires. Our group, called Applied Mathematics, Statistics and Computer Science (AMSCS), were winners of this competition, and we commenced searches in each of the 3 named departments. The Statistics hire was Valen Johnson, now Head of the Department of Statistics. The AMSCS program is funded by the Office of the Provost, which provides funding for a staff member to run the day-to-day details of IAMCS, along with a small amount of funding for activities such as workshops, invited speakers, etc. Through its own funds, the IAMCS sponsors or co-funds workshops, invited speakers, visitors and events. In the current 2014-2015 fiscal year, the IAMCS has supported the following workshops. • Workshop on fractional differential equations: inverse problems, modeling and numerical analysis • Workshop on spatial statistics • Workshop on inverse problems and spectral theory • Workshop on computational fluid dynamics IAMCS is also hosting a reception for Alain Goriely from the University of Oxford, who is giving a Department of Mathematics Frontiers in Mathematics Lecture Series. Dr. Goriely also was the Director of a KAUST-funded Center.

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Talks and Conferences funded by IAMCS

Date Title Organizer/Speaker 9/10/10 Taxonomy for the Automated Tuning of Matrix Algebra Software Elizabeth R. Jessup 10/13/10 Using Algebraic Multi-grid for Numerical Upscaling Panayot S. Vassilevski 10/18/10 On Steady and Unsteady Flows of Implicitly Constituted Incompressible Fluids Joseph Malek 10/21/10 Alignment of LC-MS Proteomics Datasets Using Internal Anchors Alan Dabney 11/4/10 Fast Algorithms for Analyzing Large Collections of Evolutionary Trees Tiffani Williams Adaptive Anisotropic Meshing and Level Set for Free Surface and Interface 11/17/10 Thierry Coupez Flow Problems Disease-Induced Juvenile Mortality and Transient and Asymptotic Population 11/18/10 Masami Fujiwara Dynamics of Chinook Salmon Spatiotemporal modeling of Mortality Risks using P-Splines: An Application 11/30/10 Lola Ugarte to Brain Cancer 12/2/10 Predicting Radiating Shock Experiments Ryan McClarren 1/20/11 Modeling of Magnetic Shape Memory Alloys Dimitris Lagoudas 1/28/11 ADI Method for Sylvester Equations Ren-Cang Li 2/2/11 Detecting Small Low Emission Sources on a Large Random Background Peter Kuchment Performance Characteristics of Hybrid MPI/Open MP Implementations of 2/3/11 NAS Parallel Benchmarks SP and BT on Large-Scale Cray XT and Blue Xingfu Wu Gene/P Supercomputers Estimation of the Drag Coefficient Using the Oceans Responses to a Hurricane: 2/17/11 Sarah Zedler A Data Assimilation Approach 2/17/11 Surveillance for Emerging Space-Time Clusters Renato Assuncao Guy Almes, John Keyser, 2/23-24/11 Visualization in Biomedial Computation Wolfgang Bangerth, Bani Mallick Integrated Second Generation Sequencing and Microarray Based Analyses to 3/2/11 Scott Dindot Identify Genetic Variants 3/24/11 First Steps of Coupling 2D and 3D Models for Lake Simulations Barbell Janssen 3/28/11 Discontinuous Petrov-Galerkin Method for Steady Transport Victor Calo 3/31/11 New Methods for Avian Distribution and Abundance Estimation Bret Collier Pathway Regulatory Analysis and Modeling of Drug Intervention Effects in the 4/4/11 Ivan Ivanov Context of Bayesian Networks Global Sub-Micrometer-Level Survey of the Mouse Brain Microstructures Using 4/7/11 Yoonsuck Choe the Knife-Edge Scanning Microscope 4/25/11 Multilevel Methods for Nonconforming FEM Systems Svetozar Margenov Coupling Water-Column Bio-Optics and Coral Reef Ecology to Predict Impacts 4/26/11 Daniel Roelke of Climate Change and Coastal Zone Development Modern C++ Design for Modern Computer Architectures: Meta Programming 5/2/11 Joel Falcou for Higher Performance Computing 5/20-21/11 Statistical Inverse Problems in the Biosciences Yanyuan Ma, Raymond Carroll 5/23-27/11 Applied Inverse Problems Conference Bill Rundell 5/31-31/11 3rd Annual Spring Symposium IAMCS Construction of High Order Schemes for the Compressible Euler and 8/26/11 Remi Abgrall Navier-Stokes Equations Massively Parallel Finite Element Simulations with Application to Convection 9/8/11 Timo Heister in the Earth’s Mantle 9/10-11/11 Ecosystem Modeling, Simulation and Assessment Workshop Daniel Roelke 9/22/11 Interrogating Genomes Through Next Generation Sequencing Scott Dindot 125

9/26/11 Statistical Methods for Exploring Metabolic Networks Erkki Somersalo 10/6/11 Stochastic Trojan Y-Chromosome Models for Eradication of Invasive Fish Xueying Wang 10/27/11 Composing Parallel Applications Using Paragraphs Timmie Smith Parallel Finite Elements Earthquake Rupture Simulations on Large-Scale 11/3/11 Xingfu Wu Multicore Supercomputers 11/17/11 Coupled Global-Regional Data Assimilation with an Ensemble-based Approach Istvan Szunyogh 12/7/11 Variance Reduction Methods in Stochastic Homogenization Frederic Legoll Joint High-dimensional Bayesian Variable and Covariance Selection with an 1/26/12 Anindya Bhadra Application to eQTL Analysis 2/16/12 Identifying Mechanistic Similarities in Drug Responses Ivan Ivanov Implicit-explicit Runge-Kutta Methods with Stabilized Finite Elements for 2/21/12 Alexandre Ern Advection-diffusion Equations 3/1/12 Research Topics in Quantitative Population Ecology Masami Fujiwara Sparsity Constraint in Electrical Impedance Tomography: 3/3/12 Matthias Gehre Complete Electrode Model 3/5/12 Robust Parameter Mesh-Free Preconditioner for a Boundary Control Elliptic Marcus Sarkis 3/6/12 Fekete-Gauss Spectral Elements with Application to Navier-Stokes flows Richard Pasquetti Computer Model Calibration with High and Low Fidelity Model Output for 3/8/12 William Kleiber Spatio-Temporal Data 3/19/12 A Bayesian Framework for the Solution of High-Dimensional Stochastic PDEs Nicholas J. Zarabas 3/22/12 The Effect of a Surface Tension on the Stress Field near a Curvilinear Crack Anna Zemlyanova 4/4/12 Joint Asymptotics and Inferences for Partly Linear Models Guang Cheng 4/5-6/12 Computational Biomedicine & Geophysics Workshop Jay Walton 4/6/12 Bootstraping Independent Component Analysis Zhuqing Yu 4/12/12 Nonstationary Cross-covariance Models for Multivariate Processes on a Globe Mikyoung Jun Optimal Design, Resonance and Bandgap Formation in Goupillaud-type 4/24/12 George Gazonas Elastic Media 5/6-8/12 4th Annual Spring Symposium IAMCS 5/8-9/12 Modeling and Simulation of Wave Propagation and Applications@KAUST Yalchin Efendiev, Victor Calo 7/19/12 Adaptive Wavelets for Uncertainty Quantification in Dynamical Systems Denis Dreano Efficient Estimation of Dynamics Density Functions with an Application 8/2/12 Abdulhakim Qahtan to Outlier Detection Computational Electromagnetics Laboratory at KAUST and Development of 8/9/12 Kostyantyn Sirenko Exact Absorbing Boundary Conditions There 9/20/12 Local Properties of Irregularly Observed Gaussian Fields Myoungji Lee 10/4/12 Visual Cortical Response Power Law and Perceptual Thresholding Yoonsuck Choe 10/12-13/12 Climate Science and Spatial Statistics Huiyan Sang, Mikyoung Jun 10/18/12 Environmental Effect on Egress Simulation Sam Rodriguez Understanding Soot Growth Turbulent Nonpremixed Glame via Direct 10/29/12 Fabrizio Bisetti Numerical Simulation and Lagrangian Statistics 11/1/12 The STAPL Parallel Graph Library Harshvardhan Adaptive Graph Regularized Nonnegative Matrix Factorization via 11/28/12 Jingyan Wang Feather Selection Joint Estimation of Multiple Bivariate Densities of Protein Backbone Angles 11/28/12 Mehdi Maadooliat Using an Adaptive Exponential Spline Family 12/10/12 An Axiomatic and Data Driven View on the EPK Paradox Maria Grith Transmission-Recovery Tradeoff in Mathematical Modeling of 2/7/13 Renata Ivanek Infectious Diseases 3/7/13 The Probability of a Salmonellosis Outbreak on a Grower-Finisher Pig Farm Glenn Lahodny 3/22/13 Parallel Programming with R Xingfu Wu A Framework for Scalable Parameter Estimation of Gene Circuuit Models Using 3/28/13 Xin Gao Structural Information 126

4/5/13 Intro: Parallel Programming With R Xingfu Wu 4/8/13 Modern Trends in High Performance Computing E.N. (Mootaz) Elnozahy 4/18/13 STAPL Nathan Thomas Scalable, Incremental Learning with MapReduce Parallelization for Cell 5/2/13 Chul Sung Detection in High-Resolution 3D 5/12-13/13 5th Annual Spring Symposium IAMCS TAMU Interdisciplinary Lecture Series- How Texas Plans for and 9/4/13 Brenner Brown Responds to Drought 11/15/13 Simulation and Statistics in Graphics John Keyser IAMCS Machine Learning & Applied Statistics Workshop Series- The Edward R. Dougherty 1/21/14 Impoverishment of Scientific Education IAMCS Machine Learning & Applied Statistics Workshop Series- Statistical 1/23/14 Matthias Katzfuss Inference for Massic Distributed Spatial Data using Low-Rank Models 2/4/14 IAMCS Machine Learning & Applied Statistics Workshop Series- Text Analytics Edward Jones Synergizing Electromagnetic and Seismic Techniques for Enhanced Reservoir 2/5/14 History Matching via Data Assimilation Techniques Klemens Katterbauer Workshop on Fractional Differential Equations: Inverse Problems, Modeling Meriem Laleg, Raytcho Lazarov, 2/6/14 and Numerical Analysis Bill Rundell IAMCS Machine Learning & Applied Statistics Workshop Series- Authoring 2/18/14 Mathew McLean Packages for the R Programming Language IAMCS Machine Learning & Applied Statistics Workshop Series- Tools for 2/25/14 Mathew McLean Reproducible Research and Dynamic Documents with R Binayak Mohanty 2/27/14 Arid Zone Hydrology under Climate Change Scenarios for the 21st Century Matthew McCabe IAMCS Machine Learning & Applied Statistics Workshop Series- Invitation to 3/20/14 Michael P. Bishop Multidisciplinary Research and the Geospatial Science and Technology Center IAMCS Machine Learning & Applied Statistics Workshop Series- 3/25/14 A Flexible Semiparametric Approach to Model, Measure and Improve Venkatesh Shankar Sales Agency Productivity IAMCS Machine Learning & Applied Statistics Workshop Series- Modeling and 4/1/14 Ramalingam Saravanan Predicting Atlantic Hurricane Activity IAMCS Machine Learning & Applied Statistics Workshop Series- Dimension 4/3/14 Yanyuan Ma Reduction: A Semiparametric Approach, Estimation, Inference, and Efficiency IAMCS Machine Learning & Applied Statistics Workshop Series- An Overview 4/8/14 Xinyu Zhang of Frequent Model Averaging IAMCS Machine Learning & Applied Statistics Workshop Series- Tensor 4/8/14 Anirban Bhattacharya Decompositions and Sparse Log-linear Models IAMCS Machine Learning & Applied Statistics Workshop Series- A Class of 4/15/14 Mikyoung Jun Matern-like Covariance functions for smooth processes on a sphere IAMCS Machine Learning & Applied Statistics Workshop Series- A Prediction 4/22/14 Maria-Pia Victoria-Feser Divergence Criterion for Model Selection IAMCS Machine Learning & Applied Statistics Workshop Series- 4/24/14 Threshold Generalized Principal Component Regression: Forecasting Mohsen Pourahmadi with Many Predictors 10/17-19/14 Inverse Problems and Spectral Theory G. Berkolaiko Mikyoung Jun, Matthias 1/29/15 Workshop on Spatial Statistics Katzfuss, Huiyan Sang Jean-Luc Guermond, Andrea 4/8/15 Computational Fluid Dynamics Bonito, Bojan Popov

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APPENDIX F.

Center for Statistical Bioinformatics

The Center was approved by the Board of Regents in March, 2007. Its mission was to serve as a focus for activities in Bioinformatics that were of a statistical nature. Given the great interest in Bioinformatics, including at least one White paper included in the final list, the mission of the Center remains critical. There is no budget for the Center, whose activities are supported by individual funds. The Center’s main activities are to host visitors and run seminars that are open to the entire university committee. We announce all talks via our web site, broadcast mailings, and through the Alliance for Bioinformatics, Computational Biology and Systems Biology. Our activities are done in coordination with the NCI-funded R25T Training Program in Biostatistics, Bioinformatics and Nutrition. We need some university support to make this center more active and competitive.

Current Members of the Center Bani K Mallick (Director) Raymond Carroll Alan Dabney David Dahl Aniruddha Datta Edward Dougherty Ruzong Fan Ivan Ivanov Faming Liang Jeff Hart Samiran Sinha Cliff Spiegelman

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APPENDIX G.

Statistics Gifts and Endowments

Original Name Description Endowment/Gift

Margaret Sheather Memorial $26,150 Award given to the best Master’s Project Ronald R Hocking Endowment $50,000 Conference - Hocking Lecturer Series Lecture Emanuel & Carol Parzen Innovation $28,285 Conference and Honorarium Award

Raymond Carroll Young Investigator $37,101 Conference and Honorarium Award

Jill & Stuart Harlin '83 Chair $1,000,000 (planned) Chair in Statistics

Roland H Acra '86 $25,000 Award given to the best Master’s Project in Analytics

Eva L. & Lee H Smith Endowment $25,000 Scholarship payment toward tuition

Ruth & Howard Newton Memorial $25,738 Scholarship payment toward tuition

STAT Former Student Fellowship $26,028 Scholarship payment toward tuition

Norbert Hartmann, Jr. $50,500 Scholarship payment toward tuition

Anant Kshirsager Endowment $100,000 Scholarship payment toward tuition

James C. Goodlett '67 $24,983 Scholarship payment toward tuition

George P. Mitchell ’40 Chair $1,000,000 Chair in Statistics

SAS Gift to M.S. Analytics $1,000,000 Gift to the Analytics Program

Norbert Hartman Legacy Gift $1,750,000 (planned) Gift to the Department 129

APPENDIX H.

Spring 2009 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Alyson G. Wilson Statistical Challenges from Science-Based Stockpile Stewardship January 22 Iowa State University Elvezio Ronchetti A New Robust and Accurate Test for Generalized Linear Models January 29 University of Geneva Olga Savchuck Choosing a Kernel for Cross-Validation February 3 TAMU Statistics Sushasini Subba Rao What to Do When the Standard Assumptions in a Multiple Linear February 10 TAMU Statistics Regression are Not Satisfied Akihiko Inoue Dynamics of Indifference Prices Derived from Optimal February 12 Hokkaido University Intertemporal Risk Allocations Lue Ping Zhao From Genes, to Gnome, and to Sequences-A Statistician’s February 19 Fred Hutchinson Cancer Perspective Research Center Joseph Tadjuidje Kamgaing Switching Regimes Autoregressive Driven Processes Versus Hidden February 26 University of Kaiserslautern Markov Models Madan L. Puri Conditional U-Statistics with Applications in Discriminant Analysis, March 5 University of Texas, Arlington ARMA Processes and Hidden Markov Models Petros Dellaportas Athens Univ. of Economics & Control Variates for Reversible MCMC Samplers March 12 Business Uwe Hassler Goethe Univ, Frankfurt am Testing for General Fractional Integration in the Time Domain March 26 Main Mohsen Pourahmadi Modeling Correlation in Longitudinal Data March 31 TAMU Statistics David S. Stoffer Spectral Magic April 2 University of Pittsburgh Kate Calder Kernal-Based Models for Space-Time Data April 9 Ohio State University Huiyang Sang Bayesian Hierarchial Models: Two Case Studies April 15 TAMU Statistics Hira L. Koul Model Diagnostics Via Khmaladze’s Martingale Transform April 16 Michigan State University Emanuel Parzen A Last Lecture 1949-2009: Quantiles are “Optimal” April 23 TAMU Statistics Pierre Pinson Regime –Switching Dynamics of Short-Term Wind Power April 30 Technical Univ. of Denmark Fluctuations Mandy Hering Comparing Accuracy of Spatial Forecasts June 30 Texas A&M University Kostas Fokianos On Poisson Autoregression July 28 University of Cyprus

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Fall 2009 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Deepak K. Agarwal Recommender System for Web Applications September 10 Yahoo Research Adin-Cristian Andrei A Novel Pseudo-Observations-Based Modeling Approach for September 17 University of Wisconsin, Madison Interval-Censored Data Anindya Roy University of Maryland, Predicting False Discovery Proportion Using Mixture Models September 24 Baltimore County David B. Dahl Distance-Based Probability Distribution on Set Partitions for September 30 Texas A&M University Bayesian Nonparametric Models Alexander Aue A Point Process Model for Transaction-Level Asset Prices October 1 University of California, Davis Zhaosong Lu An Augmented Lagrangian Approach for Sparse Principal October 8 Simon Fraser University Component Analysis Zhaohai Li Potential Impact of Population Structure on Population-Based October 15 George Washington University Case-Control Association Studies Samiran Sinha Analysis of Cohort Studies with Multivariate, Partially Observed October 20 Texas A&M University Disease Classification Data Victor De Oliveira University of Texas, San Optimal Predictive Inference in Log-Gaussian Random Fields October 22 Antonio Michael Akritas Fully Nonparametric Mixed Effects Models: Testing for the Fixed October 29 Pennsylvania State University Main Effect Hwan-Sik Choi Model Selection Testing for Diffusion Processes with Applications November 5 Texas A&M University to Interest Rate and Exchange Rate Models Sanat K. Sarkar Controlling Different Error Rates in Multiple Testing: Some November 12 Temple University Recent Developments Mikyoung Jun Nonstationary Covariance Models for Processes on a Sphere November 18 Texas A&M University Stephan Morgenthaler Ecole Polytechnique Federale Variance Stabilized Statistical Tests November 19 de Lausanne Samuel Kou Multi-Resolution Inference of Stochastic Models from Partially December 1 Harvard University Observed Data Wei-Biao Wu Simultaneous Inference of Time-Varying Linear Models December 3 University of Chicago

131

Spring 2010 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Brian Hartman From Argentina to Zimbabwe: Where Should I See My January 14 TAMU Grad Student Widgets? David E. Tyler Invariant Coordinate Selection: A New Method for Exploring January 21 State University of New Jersey Multivariate Data James G. Scott The Horseshoe Prior and Its Connection With Bayesian January 28 University of Texas at Austin Nonparametrics Wei-Biao Wu Simultaneous Inference of Time-Varying Linear Models February 4 University of Chicago Adarsh Joshi Objective Bayesian Model Selection for High-Dimensional February 9 TAMU Grad Student High-Throughput Data Ori Rosen Bayesian Mixtures of Autoregressive Models February 11 University of Texas, El Paso Ingrid Van Keilegom Univariate Frontier Estimation in the Presence of Measurement February 18 Université catholique de Louvain Error Arka P. Ghosh Optimal Control of a Stochastic Network Driven by a February 25 Iowa State University Fractional Brownian Motion Input Jeff Hart Recent Research March 2 Texas A&M University T. Siva Tian FUNER: A Novel Approach for the EEG/MEG Inverse March 4 University of Houston Problem Hira Koul Model Diagnostics via Khmaladze’s Martingale Transform March 11 Michigan State University Roger Koenker Beyond the Average Man: Additive Models for Conditional March 24 University of Illinois Quantiles Michael S. Smith Bayesian Skew Selection for Multivariate Models April 1 University of Melbourne, Australia Regina Liu (Hartley Lectures) Statistics is a Many-Splendored Thing: Mining Massive Text April 5 Rutgers University Data and Beyond Regina Liu (Hartley Lectures) Data Depth for Multivariate Spacings, Ordering, Tolerance April 6 Rutgers University Regions, etc. Regina Liu (Hartley Lectures) DD-Classifiers: New Nonparametric Classification Procedures April 7 Rutgers University Faming Liang An Overview of Markov Chain Monte Carlo Methods April 7 Texas A&M University Li-Ping Zhu Model-Free Dimension-Reduction for Ultrahigh Dimensional April 8 East China Normal University Data Piotr Fryzlewicz Thick-Pen Transformation for Time Series April 15 London Sch. of Econ & Political Sci. Ying Nian Wu From Wavelet Sparse Coding to Visual Pattern Modeling April 22 Univ of California, Los Angeles Jeremy Taylor Joint Longitudinal-Survival Models and their Application in April 29 University of Michigan Prostate Cancer

132

Fall 2010 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Tao Shi Statistical Modeling of Airs Level 3 Quantization Date September 9 Ohio State University Dan Glab Testing Lack-of-Fit of Generalized Linear Models via Laplace September 15 Texas A&M University Approximation Michael Stein An Extension of Power Law Generalized Covariance September 16 University of Chicago Functions to the Space-Time Setting Marc Genton A Sample of Current Research in Spatial Statistics September 21 Texas A&M University Li Gan A Simple Test of Private Information in the Insurance September 23 Texas A&M University, Markets with Heterogeneous Insurance Demand Economics Evarist Giné Some Aspects of Density Estimation: Sup-Norm Loss, September 30 University of Connecticut Adaptivity to Smoothness, Spatial Adaptivity Genevera I. Allen Modeling Transposable Data October 7 Baylor University/Rice University Huaiqing Wu A Prediction-Based Model Selection Approach October 14 Iowa State University Dale Zimmerman The Joys of Geocoding (from a Spatial Statistician’s October 21 University of Iowa Perspective) Yanyuan Ma Semiparametrics in Generalized Linear Latent Variable Model October 27 Texas A&M University and More Ji Zhu Extracting Communities from Networks October 28 University of Michigan Byungtae Seo Inconsistent MLS with Incomplete Data November 4 Texas Tech University Carlos M. Carvalho Dynamic Stock Selection Strategies: A Structures Factor November 11 University of Texas Model Framework Bo Li The Value of Multiproxy Reconstruction of Past Climate November 18 Purdue University Wolfgang Polonik Testing for Modality, Residual Empirical Process and December 2 University of California, Davis Weighted Sums for Time Varying Processes

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Spring 2011 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Ehsan S. Soofi Sample Information about the Parameter and Parameter and January 20 University of Wisconsin-Milwauke Prediction, and Predictability of Stochastic Process Nikolay Bliznyuk Nonlinear Latent Process Models for Integrating Spatio- January 27 Texas A&M University Temporal Exposure Data from Multiple Sources Renato Assunção Univ. Federal de Minas Gerais, Surveillance for Emerging Space-Time Clusters February 17 Brasil Xiao-Li Meng What’s the H in H-Likelihood: A Holy Grail or an Achilles’ February 24 Harvard University Heel? Boaz Nadler Detection of Signals in Noise, Matrix Perturbation and Weizmann Institute of Sci., March 3 Random Matrix Theory Israel Wolfgang Härdle Pricing of Asian Temperature Risk March 24 Humboldt-Universität zu Berlin Jeffrey D. Hart Brown Bag Lecture Series/ “A Hodgepodge of Statistics March 30 Texas A&M University Problems” Clifford Spiegelman A Nonparametric Approach Based on a Markov Like Property March 31 Texas A&M University for Classification Pradeep Ravikumar Dirty Statistical Models: M-Estimators and High-Dimensional April 7 University of Texas, Austin Analysis Arne Bathke Nonparametric Methods for Multivariate Data and Repeated April 14 University of Kentucky Measures Design Yuanjia Wang Analysis of Multilevel Genetic and Medical Studies by April 21 Columbia University Penalized Splines: Marginal versus Conditional Approach Deborah Nolan University of California, New Development in R for Information Visualization April 28 Berkeley

134

Fall 2011 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Christopher Field Bootstrapping Robust Hierarchical Models September 8 Dalhousie University David Hitchcock Limited-Information Modeling of Loggerhead Turtle September 15 University of South Carolina Population Size Michele Guindani Generalized Species Sampling Priors with Latent Beta September 22 MD Anderson Cancer Center Reinforcements Jean Opsomer Analytic Inference for Data from Complex Surveys September 29 Colorado State University Emanuel Parzen Classification of High Dimensional Data, Fundamental October 6 Texas A&M University Statistical Methods Karabi Nandy Optimal Designs for Non-Monotone Dose-Response Models October 13 Univ. of California, Los Angeles Peng Qiu Understanding Cellular Heterogeneity Using Single-Cell October 20 MD Anderson Cancer Center Cytometric Data Dongseok Choi Detecting Subclusters in Outliers October 27 Oregon Health & Sci. University Kai-Sheng Song Nonparametric Estimation of Roc Curve Via Bernstein November 3 University of North Texas Expansion and Non-Asymptotic Order Selection Peng Wei Network-Based Statistical Methods for Genetic and Genomic Univ. of Texas Sch. Public November 10 Data Health Marc A. Suchard Ridiculously Parallel, Serial Algorithms for Statistical Inference November 14 Univ. of California, Los Angeles Samuel Müeller Graphical Tools for Model Selection November 17 University of Sydney, Australia Bani K. Mallick Bayesian Inference and Uncertainty Quantification in Large December 1 Texas A&M University Scale Inverse Problems Len Stefanski Research Agenda 2012-2014 December 12 North Carolina State University

135

Spring 2012 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Scott Holan Bayesian Multiscale Multiple Imputation with Implications for January 19 University of Missouri Data Confidentiality Ke-Li Xu Powerful Tests for Structural Changes in Volatility February 2 Texas A&M University Mauro Gasparini Statistical Issues in the Analysis of Count Emg Data from a February 9 Politecnico di Torini, Italy Study on Obstetric Trauma During Delivery Xihong Lin Hypothesis Testing for High Dimensional Data: Studying Rare February 16 Harvard School of Public Health Variant Effects in Sequencing Association Studies Wilfredo Palma Pontificia Universidad Catolica Estimation and Prediction of Locally Stationary Time Series February 23 de Chile Emanuel Parzen Workshop on “History of Statistics” February 29 Texas A&M University Xinwei Deng Penalized Covariance Matrix Estimation Using A Matrix- March 1 Virginia Polytechnic Institute Logarithm Transformation and State University William Kleiber Computer Model Calibration With High and Low Fidelity National Center for Atmospheric March 8 Model Output for Spatial Temporal Data Center Scott Crawford Efficient Estimation in a Regression Model with Missing March 21 Texas A&M University Responses Haiyan Wang Nonparametric Variable Selection in High Dimensional Data March 22 Kansas State University for Classification Yuedong Wang Univ. of California, Santa Basis Selection from Multiple Libraries March 29 Barbara Richard Levine Bayesian Survival Trees for Clustered Observations, Applied April 5 San Diego State University to Tooth Prognosis Soutir Bandyopadhyay A Frequency Domain Empirical Likelihood Method for April 12 Lehigh University Irregularly Spaced Spatial Data Jaeil Ahn Bayesian Semiparametric Analysis for Two-Phase Studies of Univ. of Texas, MD Anderson April 19 Gene-Environment Interaction Cancer Center Lek-Heng Lim Principal Components of Cumulants April 26 University of Chicago Robert Serfling Multivariate Quantile and Outlyingness Functions April 27 University of Texas, Dallas

136

Fall 2012 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Kristin Lennox A Bayesian Measurement Error Model for Misaligned September 7 Lawrence Livermore National Radiographic Data Laboratory Dipanker Bandyopadhyay Semiparametric Spatial Models for Periodontal Disease Data September 14 University of Minnesota with Non-Random Missingness Stanislav Volgushev Empirical and Sequential Empirical Copula Processes Under September 21 Ruhr-Universität Bochum Serial Dependence and Weak Smoothness Conditions Marc Hallin Of Copulas, Quantiles, Ranks, and Spectra an L1-Approach to September 28 Princeton University & Université Spectral Analysis libre de Bruxelles Momiao Xiong University of Texas Health Genetic Studies of Complex Diseases in the Sequence Era October 5 Science Center at Houston Steven Rutkowski Job Opportunities and Descriptions of Statisticians at ESPN October 7 ESPN College Recruiter Caspar Ammann From Climate Science to Climate Science Applications – National Center for Atmospheric Uncertainty and Other Challenges in Making Climate Model October 12 Research Simulations Useful Val Johnson Why Should Someone be Bayesian? October 18 Texas A&M University Ping Li Bigdata: Probabilistic Methods for Efficient Search and October 19 Cornell University Statistical Learning in Extremely High-Dimensional Data Avishek Chakraborty Nonstationary Models for Uncertainty Quantification in November 2 Texas A&M University Physical Systems Alan Fieberson Job Opportunities at NASA, Research Fields and Various November 7 NASA Scientist Collaboration Lie Wang Tiger: A Tuning-Intensive Approach for Optimally Estimating November 9 Massachusetts Inst of Large Undirected Graphs Technology Jeffrey D. Hart Testing Equality of a Large Number of Densities November 16 Texas A&M University Kathryn Roeder Next Generation Sequencing and the Genetic Risk of Autism November 30 Carnegie Mellon University

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Spring 2013 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Ian McKeague Adaptive Resampling for Detecting the Presence of Significant January 18 Columbia University Predictors Anirban Bhattacharya Bayesian Shrinkage January 22 Duke University Ani Eloyan Likelihood Based Population Independent Component Analysis January 25 Johns Hopkins University Lingzhou Xue Regularized Learning of High-Dimensional Sparse Graphical January 29 Princeton University Models Pavel Krivitsky Modeling Dynamic Networks in Changing Populations Based February 5 Penn State University on Static Egocentrically-Sampled Data Matthew Reimherr Association Studies with Functional Phenotypes February 8 University of Chicago Matthias Katzfuss Low-Rank Spatial and Spatio-Temporal Models for Large February 12 Universität Heidelberg, Germany Datasets James Long Classification of Sparse, Irregularly Sampled Time Series and February 19 University of California, Berkeley Feature Measurement Error Andreas Artemiou Sufficient Dimension Reduction Through Inverse Regression February 22 Michigan Technological University and Machine Learning Michael Schweinberger Second-Generation Exponential-Family Models of Networks: March 1 Penn State University Scaling Up Chae Young Lim Clustering Cancer Mortality Curves of U.S. States Based on March 8 Michigan State University Change Points Murali Haran Dimension Reduction and Alleviation of Confounding for March 22 Penn State University Spatial Generalized Linear Mixed Models Yu Shen Statistical Challenges and Promises when Sampling Bias is March 25 UT M.D. Anderson Cancer Present Center Daniel B. Rowe Proper Statistical Modeling of Complex-Valued FMRI Data April 5 Marquette University Zhezhen Jin Variance Estimation for Regression Models April 12 Columbia University Daikwon Han Integrating Geographic Information Systems and Spatial Texas A&M Health Science Methods into Epidemiologic Research: Opportunities and April 19 Center Challenges Adrian E. Raftery Bayesian Reconstruction of Past Populations for Developing April 26 University of Washington and Developed Countries

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Fall 2013 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Ching-Kang Ing Orthogonal Greedy Algorithm and High-Dimensional Akaike’s August 30 Academia Sinica Information Criterion Jianhua Huang Some Examples of Regularized Matrix Decomposition September 6 Texas A&M University Mary C. Meyer Variable and Shape Selection in the Generalized Additive September 13 Colorado State University Guosheng Yin Heterogeneous Feature Screening in Ultrahigh Dimensional September 20 University of Hong Kong Data ♦ Working as a Statistician in Financial Services Industry and at Robert Cezeaux, Nathanial Litton September 25 Capital One Capital One Xin Qi Restricted Local Polynomial Fitting and Parameter Estimation September 27 Georgia State University in ODE and PDE ♦ Review of Dell Global Services Engineering Organization and Roy Parsons October 7 Dell Ph.D Internship Opportunities Dennis K.J. Lin Dimensional Analysis and Its Applications in Statistics October 11 Pennsylvania State University ♦ Yanyuan Ma Workshop on Semiparametric Efficiency October 17 Texas A&M University, Statistics Eric C. Chi Some Recent Developments and Applications of the MM October 18 Rice University Algorithm Chuanhua Liu Exact Prior-Free Probabilistic Inference: The Inferential Model October 25 Purdue University Approach Bing Li On an Additive Semi-Graphoid Model for Statistical Networks November 1 Pennsylvania State University with Application to Pathway Analysis Anthea Monod Estimating Thresholding Levels for Random Fields via Euler November 8 Technicon - Israel Institute of Characteristics Technology Michael Daniels A Bayesian Nonparametric Approach to Monotone Missing November 15 University of Texas at Austin Data in Longitudinal Studies with Informative Missingness Henrik Schmiediche Henrik Talks Tech: A Workshop on Computing Resources November 20 Texas A&M University, Statistics Clifford Spiegelman Texas A&M University, Statistics JFK Assassination: Chemistry, Metallurgy, and Statistics William A. Tobin November 22 Increase Doubt About Lone Gunman Theory Forensic Engineering International ♦Statistics Graduate Student Association (SGSA) Seminar/Event

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Spring 2014 Colloquium & Seminar Speakers

NAME TITLE OF ABSTRACT DATE Brad Efron Frequentist Accuracy of Bayesian Estimates January 24 Stanford University Yuval Benjamini Learning About the Visual Cortex From Predictive Models January 31 Stanford University Mario Peruggia Bayesian Synthesis and Clustered Bayesian Model Averaging February 7 Ohio State University Suojin Wang A New Nonparametric Stationarity Test of Time Series in February 14 Texas A&M University Time Domain Wenyi Wang DeMix: Deconvolution for Mixed Cancer Transcriptomes February 21 University of Texas, MD Anderson Using Raw Measured Data Cancer Center ♦ Anirban Bhattacharya ♦ Matthias Katzfuss Experiences During the Job Search Process February 25 ♦ James Long Texas A&M University Sujit Ghosh Nonparametric Models for Data Subject to Shape Constraints February 28 North Carolina State University Debdeep Pati Bayesian Model Based Shape Clustering March 7 Florida State University Rui Tuo A Theoretical Framework for Calibration in Computer Chinese Academy of Sciences Models: Parametrization, Estimation and Convergence March 21 Georgia Institute of Technology Properties Linglong Kong Spatially Varying Coefficient Model for Neuroimaging Data March 28 University of Alberta Steven MacEachern The Blended Paradigm: A Bayesian Approach to Handling April 4 Ohio State University Outliers and Misspecified Models Jiashun Jin Graphlet Screening for Rare and Weak Signals April 11 Carnegie Mellon University Stéphane Guerrier Wavelet Variance Based Estimation of Latent Time Series University of California, Santa April 25 Models Barbara Judea Pearl University of California, Los The Science of Cause and Effect May 9 Angeles ♦Statistics Graduate Student Association (SGSA) Seminar/Event

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Fall 2014 Colloquium & Seminar Speakers

SPEAKER TITLE OF ABSTRACT DATE Hao Chen Change-Point Detection for Multivariate and Object Data September 5 University of California, Davis William B. Tarinelli, Jr. Industry Recruiting: Advanced Analytics Development and September 10 ♦Travelers Insurance Internship Program Eric Vance LISA 2020: Creating a Network of Statistical Collaboration September 19 (LISA) Virginia Tech Laboratories Qiongxia Song Simultaneous Inference for the Mean of Functional Time September 26 University of Texas at Dallas Series Minsuk Shin, Shahina Rahman, Nan Zhang, Scott Goddard Secrets to Success September 26 ♦Texas A&M Statistics Val Johnson, Michael Longnecker, Jianhua Huang Town Hall Meeting October 2 ♦Texas A&M Statistics Ana-Maria Staicu Classical Testing in Functional Linear Models October 3 North Carolina State University Christopher Wikle Interaction-Based Parameterizations for Nonlinear Dynamic October 10 University of Missouri Spatio-Temporal Statistical Models Bayes for Big Ideas October 13 David B. Dunson (Hartley Lectures) Wasserstein Posteriors: Robust and Scalable Bayes October 14 Duke University Bayes for Big Tables and Networks October 15 Genevera Allen A General Framework for Mixed Graphical Models October 24 Rice University Jeffrey W. Miller Combinatorial Stochastic Processes for Variable-Dimension October 31 Duke University Models Gary Beach, Ian Wilson, Jared Industry Recruiting: Global New Ventures Exploration Harlow, Lucy Luo, Mike Davidson November 5 (GNVE) and Geosciences & Reservoir Engineering (GRE) ♦ConocoPhillips Trevor J. Hastie (2014 Parzen Prize) Sparse Linear Models November 6 Stanford University Lorenzo Trippa Bayesian Nonparametric Cross-Study Validation of Predictions November 7 Harvard University Methods Nathaniel Litton, Robert Cezeaux Industry Recruiting: Analytics Program Recruitment November 12 ♦Capital One Jae-Kwang Kim Propensity-Score-Adjustment Method for Nonignorable November 14 Duke University Nonresponse Nancy Reid (ADVANCE Speaker Serie Approximate Likelihoods November 17 University of Toronto “The Whole Woman Thing” November 18 Xiaoming Huo Fast Computing for Statistical Dependency November 21 Georgia Institute of Technology Sharon Durham, Matt Witten, Industry Recruiting: Presentation from Data Science & December 3 Lance Pate ♦Rackspace Analytics Leaders Arnab Maity Testing for Additivity in Nonparametric Regression December 5 North Carolina State University Jason D. Lee Teaching and Research Interests December 17 ● Stanford University ♦Statistics Graduate Student Association (SGSA) Seminar/Event ● Faculty Recruiting Candidate 141

APPENDIX I.

Department of Statistics Alumni Advisory Board

In 2008 the Department of Statistics began an Alumni Advisory Board. This small group of alumni provides guidance to the department on its current operations and future development. The current board members, as well as those who have served in the past, were selected based on their outstanding graduate record and on their continuing success in the field of statistics. Members of the Alumni Advisory Board are typically invited to campus once or twice a year to meet with the department head and offer input on the direction of departmental programs. The most recent board meeting was held on January 28, 2015. Agenda items discussed were the Distance Learning Program, the M.S. in Analytics program, the Graduate Program, and the Undergraduate Degree Proposal. Below please find resumes for the following Alumni Advisory Board members: Ersen Arseven, Christian Galindo, Marcy Johnson, Michael Kutner, Jeffrey Morris, and Scott Grimshaw.

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ERSEN ARSEVEN Ph.D. Statistical and Process Consultant Clinical and Non-Clinical Drug Development 243 South Boulevard, Nyack, New York 10960-4114 Voice: 845-358-4636 Email: [email protected]

Overview of experience and accomplishments

I am a Ph.D. Statistical and Process Consultant with more than 35 years of successful clinical and non-clinical drug development experience in eleven therapeutic areas with twelve NDAs. My Therapeutic area experience includes cardiovascular diseases, gastrointestinal disorders, infectious diseases, oncology, ophthalmology, pulmonary diseases, sleep disorders, vaccines, diagnostic agents, tuberculin diagnostic tests, medical devices and hospital products.

I developed my technical and management skills working at line and senior management positions in American and European multinational pharmaceutical companies with worldwide responsibility for Statistics, Data & Document Management, and Medical Systems for non-clinical and clinical drug development and registration.

I have developed a global outlook on the scientific, regulatory, and competitive market pressures facing the pharmaceutical industry. Consulting with top-tier companies in the pharmaceutical and information technology industries further enhanced the breadth and depth of my knowledge and experience, and has given me a wealth of practical and useful insight into the discovery and development of biopharmaceutical/biotechnology products.

I have excellent technical knowledge, and very good people and interpersonal skills.

I make use of innovative and pragmatic approaches for sound operational staging of development projects and clinical trials with optimal deployment of internal and external resources for faster development, approvals, and transition of new drugs to marketing. Some highlights of my record of results: • Excellent knowledge and experience in global development of drugs, biologicals, and contrast agents for diagnostic imaging. • Successfully prepared and obtained approval for twelve New Drug Applications (NDAs) for treatment of hypertension, glaucoma, cardiovascular, pulmonary and infectious diseases, prophylactic vaccines, and contrast agents for diagnostic use. • Carried out Due Diligence investigation for a venture capitalist interested in acquiring drug product under development by a small pharmaceutical company. Assessed the adequacy of the pre-clinical and clinical study results and the clinical development plan in terms of whether they provided evidence for efficacy and safety required by regulatory agencies. • For a premier Biotechnology company with a very promising compound in development, evaluated completeness of the company’s Drug Development Process (DDP), both in scope and depth, in conjunction with the management and technical environment. Identified significant gaps. Made concrete recommendations for closing identified gaps and laid out methods of implementation. • For the same company, preparation of Common Technical Document (CTD) as the primary evaluation tool, investigated how much progress the company had 2 made in filling gaps identified earlier. Scope of the analysis covered the development and implementation of required drug development infrastructure, technology platforms, applications, tools, and processes in Clinical Research, Non-Clinical Research, Pharmaceutical Sciences, Production, and in Project Management departments. • Directed multinational clinical development project to a successful completion by managing statistical, data management, and programming work of the client company and its numerous European and American Clinical Research Organization (CRO) development partners. • Led team of international scientists of Fortune 20 information technology company in assessing commercial potential of their new technologies – including product knowledge bases, data marts, and warehouse technologies – and consulting services for use in the drug development process. • Developed and implemented a uniform Biometrics Process that made use of “best industry practices” in a decentralized multinational CRO with five independent Business Centers. • Evaluated operations and infrastructure of two key departments of a mid-sized pharmaceutical company; realigned the organizational structure, standardized clinical data processing and programming, and defined proper technology and staff skill mix for efficient operation.

Professional Experience

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Statistical and Process Consulting May 1992-Present Provides innovative and sound approaches to enable global development, registration, and licensing of biopharmaceuticals, biologicals, diagnostic tests, and contrast agents. Services offered include: • Development of statistical design, analysis, presentation strategy, and methodologies. Implementation of strategy for a specific product development and registration. • Integration of scientific evidences for efficacy and safety summaries. Review and evaluation of clinical dossiers, pre-clinical safety and CMC sections, integrated summaries, clinical trial reports, protocols, and methodologies. • Due Diligence for licensing and investment decisions by companies and venture capitals. o Evaluation and validation of pre-clinical and clinical study results and methodologies reported in prospectus portfolios. o Assessment of the quality of submitted work and its acceptability by regulatory agencies to establish safety and efficacy. • Project and resource management for operational staging of global clinical development projects. • Management and organizational consulting for drug development process. • Development of knowledge bases for therapeutic areas and for products to leverage knowledge accumulated during the development phase to facilitate smooth transitioning of product from development team to marketing team for more effective market introductions.

Schering-Plough Research Institute, Kenilworth, NJ Statistics and Statistical Programming (02/2003-06/2005) Director Non-Clinical Statistics

Directed activities of groups of statisticians that provided statistical design and analysis services to: Discovery Research Division Chemical and Pharmaceutical Sciences Division Safety Sciences Division of the Research Institute Prepared and reviewed statistical components of Chemistry-Manufacturing-Control (CMC) and Safety Sections of regulatory submissions. In discussions with regulatory agencies, provided defense of statistical methodology and conclusions.

Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT Scientific Affairs Division (12/1990-05/1992) Group Director with Worldwide Responsibility

For worldwide company, as a member of the International Medical Committee, evaluated the medical and operational staging of global development projects. Managed the development and implementation of statistical design, analysis, and data management of global projects. Led the design and implementation of processes to produce submissions dossiers from standard components.

For U.S. operations unit, directed statistical design and analysis, data management, document processing, and archiving services for the R&D and Medical Divisions. Directed development and implementation of systems and office automation to enable effective functioning of Medical Affairs Division. Staff of 77 and budget of M$6.5.

Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT Medical Affairs Division (05/1988-12/1990) Director, Medical Data and Administrative Services

Directed the activities of seven departments in two divisions: Statistical Design and Analysis, Clinical Trial Information, Clinical Trial Support, Medical Systems, Medical Planning and Budgets, Project Management, and Medical Grants and Contracts. Directed development and implementation of systems and procedures to improve planning and control of clinical drug development project activities and costs. Set information technology direction. Prepared and monitored the Medical Affairs Division budget and expenses. Staff of 83 and budget of M$30.

Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT Medical Affairs Division (07/1984-05/1988) Director, Medical Data Services

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Established effective Statistical Design and Analysis, Data Management, Document Management, and Medical Systems Departments. Developed and implemented Biometric Process to enable global clinical development of our drugs ahead of competitors. Led international task force to develop worldwide clinical data management procedures and standards. Achieved and maintained a zero backlog in processing and analysis of clinical trial data through streamlining procedures, upgrading professional staff, and implementation of proper information technology. Directed four departments with staff of 65 and budget of M$4.5.

American Cyanamid Company, Pearl River, NY Medical Research Division (04/1982-07/1984) Group Leader, Non-Clinical Statistics

Managed group of Statisticians that provided statistical design and analysis services to: Biological Discovery, Analytical Services, Pharmacodynamics and Pharmacokinetics, Process Development, Formulation, Stability Testing, and Toxicology. Developed systems for Analysis of Toxicology Data and Quality Control of vaccine production.

Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT Medical Affairs Division (02/1978-03/1982) Manager, Statistical Evaluation

Established the Statistical Design and Analysis Department. Served as company expert for defense of statistical methodology and conclusions before regulatory agencies. Linked the activities of Clinical Research with R&D.

American Cyanamid Company, Pearl River, NY Medical Research Division (01/1975-02/1978) Research Statistician

Designed and analyzed clinical trials in anti-infectives, ocular hypertension, vaccines, and inhaled steroids. Designed and implemented biological screens in drug discovery to identify potential drugs in targeted therapeutic areas. From these screens, one anticancer compound, Mitoxantrone, was identified and successfully developed and marketed for treatment of leukemia. 5

Education Ph.D. 1974, Texas A&M University, College Station, Texas Major: Statistics, emphasis on multivariate analysis, general linear models, design of experiments, and Markov renewal processes. Minors: Operations Research and Mathematics. Dissertation title: Applications of Graph Theory to PERT Critical Path Analysis.

M.A. 1969, University of Pennsylvania, Philadelphia, Pennsylvania. Major: Economics

B.A. 1964, Ankara University, SBF, Ankara, Turkey. Major: Economics and Finance

Professional Societies American Association for the Advancement of Science American Statistical Association American Society for Quality Institute for Mathematical Statistics Biometrics Society Pharmaceutical Manufacturers Association, Biostatistics Steering Committee, 1986-1989 Editorial Board Member, Biopharmaceutical Report, 1999-2001

Honors and Awards • Appointed to the Alumni Advisory Board, Department of Statistics, Texas A&M University • Inducted into the Academy of Distinguished Former Students of the College of Science, Texas A&M University • Received H.O. Hartley Award for Distinguished Service to the Discipline of Statistics, Texas A&M, University Department of Statistics

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Publications and Technical Reports • "Stationary State Probabilities of a Markov Renewal Process and Optimum Scores Associated with the States." A. M. Kshirsagar and E. Arseven, Communication in Statistics, Volume 3 (10), 1974. • "Note on the Equivalency of Two Discrimination Procedures." A. M. Kshirsagar and E. Arseven, American Statistician, Volume 29 (1), 1975. • “An Elementary Derivation of the Non-Central Chi-Square Density Function.” Ersen Arseven, Metron, Volume 33 (1-2), 1975. • "Critical Path Analysis in Stochastic Networks: Statistical PERT." H. O. Hartley, R. L. Sielken, and E. Arseven, SCIMA, Volume 6 (3), 1977. • "Application of Graph Theory to PERT Critical Path Analysis." H. O. Hartley and E. Arseven, Technical Report No. 46, Office of Naval Research, Project NR047-700. • "Statistical Critical Path Analysis in Acyclic Stochastic Networks: Statistical PERT." H. O. Hartley, R. L. Sielken, and E. Arseven, Office of Naval Research, Contract N00014-68-A-0140, Project NR047-700. • Data Management. Medical Guide. Volume 1, Notes for Guidance on Operational Procedures within Boehringer- Ingelheim. E. Arseven, P. Reilly, A. Lawton, D. Piera, 1989.

Presentations 1. Lectures, Controversial Issues in Clinical Trials: Interim Analyses, Multi-Center Trials, Crossover Designs, Combination Drug Testing, Dose Tolerance and Response Studies. Pharmaceutical Manufacturers Association Workshops for New Clinical Statisticians in the Industry Washington, D. C., May 9-10, 1988 Washington, D. C., March 6-7, 1989 2. From Compartmentalization to Integration: Requirements of Global Drug Development. Boehringer-Ingelheim Worldwide Medical Directors' Meeting, Rudesheim, Germany, October 14-18, 1990. 3. Training Course in Non-Clinical Statistics. Course developer and leader. Pharmaceutical Manufacturers Association Education & Research Institute. Washington, D. C., January 9-11, 1991. 4. “Reengineering of the Clinical Drug Development Process,” Invited paper on Total Quality Management in Drug Development, American Statistical Association Winter Conference. Atlanta, Georgia, January 6-7, 1994. 5. “Have You Developed the Skills That Are Necessary for Your Success?” Group Discussion, American Statistical Association Winter Conference, Raleigh, North Carolina, January 5-8, 1995. 6. “Interim Analysis in Clinical Trials,” Corning Besselaar, Inc. Statisticians’ Forum, Princeton, New Jersey, November 13, 1996. 7. “Have You Developed the Skills Necessary for Your Success in the Pharmaceutical Industry?” Biopharmaceuticals Section Roundtable Discussion Program, Joint Statistical Meetings, Baltimore, Maryland, August 8-12, 1999. 8. "What Do Statistical Consultants Really Do?” Invited presentation to graduate students of Department of Statistics at Texas A&M University, College Station, Texas, October 14,2002. 9. “Using Historical Control Data in Evaluating Tumor Trends for Oncogenicity Studies.” Amrik Shah and Ersen Arseven. Harvard School of Public Health, Department of Biostatistics, Colloquium 2003-2003 Series, Boston, April 24, 2003.

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CHRISTIAN D. GALINDO Ph.D. and Marketing Analytics, Facebook 2750 El Prado Road, Burlingame, California 94010 Voice: 415-484-6262 Email: [email protected]

OBJECTIVE Executive-level position in consumer-based e-commerce, mobile, or social media, with a focus on business intelligence and analytics.

QUALIFICATION Quantitatively-focused senior professional with a doctorate in Statistics and a strong background in business intelligence, strategy, and analytics across several industries including E-commerce, Search, Online Marketing, and Biotechnology.

Professional strengths include • Reputation for strong analytics, objective business sense, and making data actionable. • Talent for clear and concise explanations of complex quantitative concepts. • Versatile background and skill set allowing for efficient collaboration across a broad range of corporate functional areas. •i Pass on for delivering accurate data and reporting to drive sound business decisions. • Strongly held belief in being customer-focused for long term company success.

EXPERIENCE Facebook Menlo Park, California 2014 – Present MARKETING ANALYTICS Build and lead the consumer marketing analytics practice

Leap Commerce San Francisco, California 2013 – 2014 VICE PRESIDENT – PRODUCT STRATEGY& ANALYTICS Lead the Product, Marketing, and Analytics efforts of an early stage technology startup providing a SaaS social recommendation and discovery solution. • Develop a holistic point-of-view around the use of earned media to provide a marketing-led e- commerce experience. • Create both a strategic roadmap and individual product feature requirements around a set of enterprise solutions that bring the power of word-of-mouth advertising down the purchase funnel from awareness and consideration to engagement and sales. •h Spear ead marketing efforts to support venture fundraising, partnerships, and business development collateral. • Oversee the algorithmic development of Leap’s recommendation engine.

Mode Media Brisbane, California 2011-2013 VICE PRESIDENT, ANALYTICS Own the Analytics function for the largest consumer lifestyle publishing network in the US and a Top 10 global web property. • Developed and managed a centralized Analytics organization across Mode Media post Ning acquisition. • Areas of analytics ownership include Advertising (Targeting, Measurement), Marketing (Channel, MarCom, Product, Market Research), Product (Ad Platform, Subscription Platform, O&O, Consumer & Publisher Products), and Business Intelligence (KPI Development & Reporting, Business Insights). • Nurtured a quantitatively-driven business culture, so that decisions affecting strategy, plans, programs, and customer experience were based on relevant data and insights. • Responsible for responding to brand advertising targeting and measurement needs, and for working closely with strategic data and research vendors to maintain and grow productive partnerships. • Business owner of reporting, analytics, and KPIs that demonstrate how content and social media matter to brands, consumers, publishers, and network creators; and how the interests of all constituents should be aligned for long-term success. • Assumed thought leadership role, both internally and within professional bodies such as the IAB, in defining Social Data and articulating its use within an advertising framework. • Continued to manage all facets of product, marketing, and business analytics for Ning.

Ning Palo Alto, California 2010-2011 DIRECTOR, ANALYTICS

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Oversaw the Data Engineering and Business Intelligence teams for the world’s largest social website platform, with over 100,000 subscribed networks and 60 million monthly visitors. Acquired by Mode Media in 2011. • Mentored, grew and led the Analytics team consisting of Data Engineers and Analysts. • Worked closely with technical teams to ensure products were developed and launched with properly engineered data, relevant tracking, performance metrics, and reporting in place. • Guided the evolution of the company by analyzing customer behavior including website performance, network trends, social engagement, marketing, and merchandising activity. • Partnered with Marketing to establish sound measurement practices including channel attribution, program measurement and marketing optimization. • Drove the development of a simplified and unified data framework that served as the backbone for the company's executive and operational dashboards.

Threadsy/Swaylo San Francisco, California 2010 HEAD OF ANALYTICS (LONG-TERM CONTRACT) Developed the analytics framework of an early-stage influence marketing start-up that used viral techniques to achieve a customer base of over six million people. Acquired by Facebook in 2012. • Oversaw business intelligence for the world's first integrated communications client – combining email, Twitter, social networks, and 40 other web services into a unified communications experience • Developed analytic framework to assess viral marketing performance and engagement of social network applications built on “gamification” techniques. • Helped drive development of highly viral Facebook applications, twice reaching AppData’s Top 20 and leading to Swaylo’s current customer base.

Shopping.com Brisbane, California 2005 – 2010 GLOBAL DIRECTOR, BUSINESS INTELLIGENCE Head of Business Intelligence and Analytics for a multinational subsidiary of eBay, Inc., with a portfolio of websites attracting 25 million monthly visitors and accounting for $1.5 billion in merchant sales annually. • Directed company vision and strategy for business and product analytics. • Translated business needs into actionable and relevant data requirements. Managed business intelligence as an enterprise product including tracking, collection, reporting, and analysis. • Developed and oversaw testing of new site features, and made recommendations for product optimization. Investigated website performance throughout product lifecycle. • Maintained systemic view of site analytics, monitoring changes in operational behavior due to new product initiatives, SEO/SEM marketing, distribution, and merchant deals. • Led pricing strategy to align financial interests of merchants and partners, optimize merchant ROI, increase network quality, and enhance user experience. Major projects included regular rate-card evaluations, seasonal pricing adjustments, the development of a dynamic CPC-based pricing methodology, and a refined revenue attribution process for a CPA business model. • Conceptualized data structure and reporting required to reinvigorate community-based shopping program that had been growing at 50 thousand members monthly.

LookSmart, Ltd. San Francisco, California 2002 – 2005 MANAGER, SEARCH ANALYSIS Formalized and executed a relevance assessment program across both the search engine and ad platforms for a syndicated search network serving a half billion ad impressions daily. • Managed analytics team in support of product strategies and marketing functions. Identified opportunities to improve relevance and revenue through algorithmic development and alternative sales and business development strategies. • Devised novel approaches for evaluating search engine performance, including generalized between- list distance metrics and distribution-free relevance measures. Informed testing methodology for such companies as MSN and Inktomi. • Drove the development of relevance scoring tools and optimized overall testing process. • Consolidated data analysis onto one platform and generalized code to allow for scenario-based modeling. Reduced testing timeframe and cost by 50%. • Developed standards for relevance data storage, use, and analysis across R&D, Engineering, and Architecture groups. Formulated automated relevance assessment methodology, allowing for regular, efficient, and inexpensive product release feedback.

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Coremetrics, Inc. Burlingame, California 2000 – 2002 PRINCIPAL CONSULTANT, CLIENT ENGAGEMENT Customer-facing role for the leading Software-as-a-Service web analytics and marketing optimization platform of its time. Founded consulting practice that is still part of the core service offerings. • Templatized and delivered consulting engagements designed to optimize client websites and online marketing efforts. Oversaw the development and interpretation of advanced statistical models including such techniques as discriminant analysis, factor analysis, cluster analysis, logistic and other nonlinear regression, CHAID, and CART. • Developed training material for both internal and external consumption. Proposed advanced product offerings based on industry needs and client feedback. • Managed client relationship with numerous multi-channel customers such as Walmart, Columbia House, and GMAC. Performed consulting engagements to guide online marketing efforts. • Served as solutions engineer during customer sales cycle. Responsible for mapping business objectives of potential clients to appropriate data collection and reporting.

Shockwave.com San Francisco, California 2000 MARKET RESEARCH MANAGER / DATABASE MARKETING ANALYST Managed consumer insights and marketing analytics for one of the Internet’s earliest video and gaming portals, with over 100 million registered members worldwide. • Functioned as statistical consultant and consumer behavior analyst while working with Content Production, Programming, Site Development, Engineering, Marketing, Sales, and Business Development. • Mined member database to research online behavior and attrition patterns. Implemented process for collection and analysis of member demographics. Developed email marketing segmentation schemes for a program with a monthly budget of $200,000. • Managed primary research, including usability testing, focus groups, individual user behavior studies. Implemented on-going customer satisfaction and loyalty studies. Maintained relations with secondary research and external traffic vendors.

Genentech, Inc South San Francisco, California 1998 – 2000 BIOSTATICIAN Statistician supporting all stages of the drug development life cycle for the world’s largest and most successful biotechnology company. • Supported nonclinical function through statistical consultation, experimental design, data analysis and interpretation, and in-house training.. Served as primary statistical point-of-contact for over 500 scientists and engineers in Research, Process Science, and Pharmacokinetics. • Assumed biostatistical responsibilities in clinical drug development. Designed study protocols and analysis plans, and monitored trials for statistical validity and compliance with federal regulations. • Developed and taught company-wide statistics courses, and created a statistical resource website.

National Cancer Institute Bethesda, Maryland Summer 1997 STATISTICIAN • Researched the estimation of disease penetrance, in particular testing a method for the determination of intra- family phenotypic independence conditional on genotype.

The RAND Corporation Santa Monica, California Summer 1996 STATISTICAL CONSULTANT • Analyzed Unites States Army logistics matters concerning overseas transportation of military equipment. Formulated benchmarking criteria for present and future performance evaluations.

OTHER EXPERIENCE The Deep End, 501(c)(3) San Francisco, California 2007-Present PRESIDENT • President and lead financial officer of San Francisco Bay Area non-profit that produces events showcasing local amateur electronic musicians and alternative artists, creates the annual large-scale Distrikt project at Burning Man, and provides financial support to other charitable organizations and artists sharing a similar vision.

EDUCATION Texas A&M University College Station, Texas • Doctor of Philosophy, Statistics 1998 149

Research Topic: Nonparametric inference, including mean functional estimation with missing data and confidence interval construction for local estimating equations • Bachelor of Science, Summa Cum Laude, Applied Mathematical Sciences 1993

PUBLICATIONS • Carroll, R. J. & Galindo, C. D. (1998). Measurement error, biases, and the validation of complex models for blood lead levels in children. Environmental Health Perspectives. 106, 6: 1535-1539. • Galindo, C. D. (1998). On nonparametric estimation of mean functionals. Statistics & Probability Letters. 39: 143- 149. • Galindo, C. D., Liang, H., Kauermann, G., Carroll, R. J. (1999). Bootstrap confidence intervals for local likelihood, local estimating equations, and varying coefficient models. January 2001.

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MARCELLA M. JOHNSON Director, Quantitative Research Department of Biostatistics, University of Texas MD Anderson Cancer Center 3322 N. Braeswood Blvd., Houston, Texas 77025 Voice: 713-794-4193 Email: [email protected]

EDUCATION Degree Granting Education: Texas A&M University, College Station, TX, 1988, MS, Statistics Texas A&M University, College Station, TX. 1986, BS, Applied Mathematical Sciences

EXPERIENCE/SERVICE Academic Appointments: • Director, Quantitative Research, Department of Biostatistics, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, September 2008 – Present • Associate Director, Quantitative Research, Department of Biostatistics, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, March 2006 to August 2008 • Principal Statistical Analyst, Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, April 2004 to February 2006 • Senior Statistical Analyst, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, May 2001 to March 2004. • Manager, Patient Outcome Registry, Cyberonics, Inc., Houston, Texas, March 1999 to April 2001. • Coordinating Manager, Biostatistics, Applied Logic Associates, Inc., Houston, Texas, October 1995 to February 1999. • Manager, Biostatistics, Applied Logic Associates, Inc., Houston, Texas, August 1995 to October 1995. • Senior Biostatistician, Applied Logic Associates, Inc., Houston, Texas, February 1994 to August 1995. • Biostatistician, Applied Logic Associates, Inc., Houston, Texas, April 1992 to February 1994. • Statistical Analyst, Physiological Research Group, KRUG Life Sciences, Inc., Houston, Texas, April 1990 to April 1992. • Senior Research Assistant and Assistant Project Manager, Coordinating Center for Clinical Trials, School of Public Health, University of Texas Health Science Center, Houston, Texas, May 1998 to April 1990. • Statistical Intern, Department of Biostatistics, Scott & White Memorial Hospital, Temple, Texas, August 1987 to May 1988.

Institutional Committee Activities: - The University of Texas MD Anderson Cancer Center, Institutional Review Board, Associate Member, April 2012 – present - The University of Texas MD Anderson Cancer Center, Clinical Research Committee, September 2005 – present - The University of Texas MD Anderson Cancer Center, Quality Improvement Oversight Committee, October 2007 – August 2010

Other Appointments/Responsibilities: - American Joint Committee on Cancer (AJCC) Melanoma Staging Committee (for development of the 7th Edition, Cancer Staging Manual), September 2005 – March 2009

Consultantships: - Cyberonics, Inc., Houston, Texas, January 2002- January 2006

RESEARCH Grants and Contracts: Funded Grants: • Statistician, 20% salary support, NIH/NCI, 2 P30 CA016672 38: Cancer Center Support Grant – Biostatistics Resource Group (PI: DePinho), 7/01/2013 - 6/30/2018, $635,606

PUBLICATIONS: Articles in Peer-Reviewed Journals: 1. Gayed I, Vu T, Johnson M, Macapinlac H, Podoloff D. Comparison of Bone and 2-Deoxy-2-[18F]Fluoro-D-Glucose Positron Emission Tomography in the Evaluation of Bony Metastases in Lung Cancer. Mol Imaging Biol. 2003 Jan- Feb;5(1):26-31. 2. Wierda WG, Johnson MM, Do KA, Manshouri T, Dey A, O'Brien S, Giles FJ, Kantarjian H, Thomas D, Faderl S, Lerner S, Keating M, Albitar M. Plasma Interleukin 8 Level Predicts for Survival in Chronic Lymphocytic Leukemia. Br J Haematol. 2003 Feb;120(3):452-6.

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3. Do KA, Johnson MM, Doherty DA, Lee JJ, Wu XF, Dong Q, Hong WK, Khuri FR, Fu KK, Spitz MR. Second Primary Tumors in Patients with Upper Aerodigestive Tract Cancers: Joint Effects of Smoking and Alcohol. Cancer Causes Control. 2003 Mar;14(2):131-8. 4. Rousseau DL, Ross MI, Johnson MM, Prieto VG, Lee JE, Mansfield PF, Gershenwald JE. Revised American Joint Committee on Cancer Staging Criteria Accurately Predict Sentinel Lymph Node Positivity in Clinically Node-Negative Melanoma Patients. Ann Surg Oncol. 2003 Jun;10(5):569-74. 5. Prieto VG, Argenyi ZB, Barnhill RL, Duray PH, Elenitsas R, From L, Guitart J, Horenstein MG, Ming ME, Piepkorn MW, Rabkin MS, Reed JA, Selim MA, Trotter MJ, Johnson MM, Shea CR. Are en face frozen sections accurate for diagnosing margin status in melanocytic lesions? Am J Clin Pathol. 2003 Aug;120(2):203-8. 6. Ellerhorst JA, Cooksley CD, Broemeling L, Johnson MM, Grimm EA. High Prevalence of Hypothyroidism Among Patients with Cutaneous Melanoma. Oncol Rep. 2003 Sep-Oct;10(5):1317-20. 7. Giles FJ, Vose JM, Do KA, Johnson MM, Manshouri T, Bociek G, Bierman PJ, O’Brien SM, Keating MJ, Kantarjian HM, Armitage JO, Albitar M. Circulating CD20 and CD52 in patients with non-Hodgkin’s Lymphoma or Hodgkin’s disease. Br J Haematol. 2003 Dec;123(5):850-857. 8. Raad I, Hanna HA, Alakech B, Chatzinikolaou I, Johnson MM, Tarrand J. Differential Time to Positivity: A Useful Method for Diagnosing Catheter-related Bloodstream Infections. Ann Intern Med. 2004 Jan 6;140(1):18-25. 9. Gayed I, Vu T, Iyer R, Johnson M, Macapinlac H, Swanston N, Podoloff D. The Role of 18F-FDG PET in Staging and Early Prediction of Response to Therapy of Recurrent Gastrointestinal Stromal Tumors, J Nucl Med. 2004; 45(1): 17-21. 10. Simeone AM, Li YJ, Broemeling LD, Johnson MM, Tuna M, Tari AM. Cyclooxygenase-2 is Essential for HER2/neu to Suppress N-(4-Hydroxyphenyl) retinamide Apoptotic Effects in Breast Cancer Cells. Cancer Res. 2004, Feb 15; 64(4): 1224-8. 11. Kim KB, Sanguino AM, Hodges C, Papadopoulos NE, Eton O, Camacho LH, Broemeling LD, Johnson MM, Ballo MT, Ross MI, Gershenwald JE, Lee JE, Mansfield PF, Prieto VG, Bedikian AY. Biochemotherapy in Patients with Metastatic Anorectal Mucosal Melanoma. Cancer. 2004 Apr 1;100(7):1478-83. 12. Yang WT, Whitman GJ, Johnson MM, Bolanos-Clark M, Kushwaha AC, Hunt KK, Dempsey PJ. Needle Localization for Excisional Biopsy of Breast Lesions: Comparison of Effect of Use of Full-field Digital Versus Screen-film Mammographic Guidance on Procedure Time. Radiology. 2004 Apr;231(1):277-81. 13. Wu X, Zhao H, Do KA, Johnson MM, Dong J, Hong WK, Spitz MR. Serum Levels Of Insulin Growth Factor (IGF-I) And IGF-Binding Protein Predict Risk Of Second Primary Tumors In Patients With Head And Neck Cancer, Clin Cancer Res. 2004 Jun 15;10:3988-95. 14. Giles FJ, Vose JM, Do KA, Johnson MM, Manshouri T, Bociek G, Bierman PJ, O'Brien SM, Kantarjian HM, Armitage JO, Albitar M. Clinical Relevance of Circulating Angiogenic Factors in Patients with Non-Hodgkin's Lymphoma or Hodgkin's Lymphoma. Leuk Res. 2004 Jun;28(6):595-604. 15. Ellerhorst JA, Naderi AA, Johnson MK, Pelletier P, Prieto VG, Diwan AH, Johnson MM, Gunn DC, Yekell S, Grimm EA. Expression of Thyrotropin-Releasing Hormone by Human Melanoma & Nevi. Clin Cancer Res. 2004 Aug 15;10(16):5531-6. 16. Albitar M, Do KA, Johnson MM, Giles FJ, Jilani I, O'Brien S, Cortes J, Thomas D, Rassenti LZ, Kipps TJ, Kantarjian HM, Keating M. Free Circulating Soluble CD52 as a Tumor Marker in Chronic Lymphocytic Leukemia and Its Implication in Therapy With Anti-CD52 Antibodies. Cancer. 2004 Sep 1;101(5):999-1008. 17. Wallace MJ, Jean JL, Gupta S, Eapen GA, Johnson MM, Ahrar K, Madoff DC, Morello FA, Murthy R, Hicks ME. Use of Inferior Vena Caval Filters and Survival in Patients with Malignancy. Cancer. 2004 Oct 15;101(8):1902-7. 18. Do KA, Johnson MM, Lee JJ, Wu XF, Dong Q, Hong WK, Khuri FR, Spitz MR. Longitudinal Study of Smoking Patterns in Relation to the Development of Smoking-Related Secondary Primary Tumors in Patients with Upper Aerodigestive Tract Malignancies. Cancer. 2004 Dec 15;101(12):2837-42. 19. Choi H, Charnsangavej C, Faria Sde C, Tamm EP, Benjamin RS, Johnson MM, Macapinlac HA, Podoloff DA. CT Evaluation of the Response of Gastrointestinal Stromal Tumors After Imatinib Mesylate Treatment: A Quantitative Analysis Correlated with FDG PET Findings. Am J Roentgenol. 2004 Dec; 183(6):1619-28. 20. Simeone AM, Deng CX, Kelloff GJ, Steele VE, Johnson MM, Tari AM. N-(4-Hydroxyphenyl) Retinamide Is More Potent Than Other Phenylretinamides in Inhibiting the Growth of BRCA1-Mutated Breast Cancer Cells. Carcinogenesis. 2005 May;26(5):1000-7. 21. Pawlik TM, Ross MI, Johnson MM, Schacherer CW, McClain DM, Mansfield PF, Lee JE, Cormier JN, Gershenwald JE. Predictors and Natural History of In-Transit Melanoma After Sentinel Lymphadenectomy. Ann Surg Oncol. 2005. 12(8):587-96. 22. Gupta S, Johnson MM, Murthy R, Ahrar K, Wallace MJ, Madoff DC, McRae SE, Hicks ME, Rao S, Vauthey JN, Ajani JA, Yao JC. Hepatic Arterial Embolization and Chemoembolization for the Treatment of Patients with Metastatic Neuroendocrine Tumors. Cancer. 2005 Oct 15;104(8):1590-602. 23. Faderl S, Do KA, Johnson MM, Keating M, O'brien S, Jilani I, Ferrajoli A, Ravandi-Kashani F, Aguilar C, Dey A, Thomas DA, Giles FJ, Kantarjian HM, Albitar M. Angiogenic Factors may have a Different Prognostic Role in Adult Acute Lymphoblastic Leukemia (ALL), Blood. 2005 Dec 15;106(13):4303-7. 24. Berger AJ, Davis DW, Tellez C, Prieto VG, Gershenwald JE, Johnson MM, Rimm DL, Bar-Eli M. Automated

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quantitative analysis of activator protein-2alpha subcellular expression in melanoma tissue microarrays correlates with survival prediction. Cancer Res. 2005 Dec 1;65(23):11185-92. 25. Feng J, Lenihan DJ, Johnson MM, Karri V, Reddy CVR. Cardiac Sequelae in Brooklyn After the September 11 Terrorist Attacks, Clin Cardiol. 2006 Jan;29(1):13-7. 26. Pawlik TM, Ross MI, Prieto VG, Ballo MT, Johnson MM, Mansfield PF, Lee JE, Cormier JN, Gershenwald JE. Assessment of the role of sentinel lymph node biopsy for primary cutaneous desmoplastic melanoma. Cancer. 2006 Feb 15;106(4):900-6. 27. Ludwick JJ, Rossmann SN, Johnson MM, Edmonds JL. The Bacteriostatic Properties of Ear Tubes Made of Absorbable Polylactic Acid, Int J Pediatr Otorhinolaryngol. 2006 Mar;70(3):407-10. 28. Simeone A, Colella S, Krahe R, Johnson MM, Mora E, Tari AM. N-(4-Hydroxyphenyl) retinamide and nitric oxide pro- drugs exhibit apoptotic and anti-invasive effects against bone metastatic breast cancer cells. Carcinogenesis. 2006 Mar;27(3):568-77. 29. Aloia T, Gershenwald JE, Ross MI, Lee JE, Johnson MM, Cormier JN, Ng C, Mansfield PF. Utility of Computed Tomography and Magnetic Resonance Staging Prior to Completion Lymphadenectomy in Patients with Sentinel Lymph Node-Positive Melanoma. J Clin Oncol. 2006 Jun 20;24(18):2858-65. 30. Ellerhorst JA, Ekmekcioglu S, Johnson MK, Cooke CP, Johnson MM, Grimm EA. Regulation of iNOS by the p44/42 Mitogen-Activated Protein Kinase Pathway in Human Melanoma. Oncogene. 2006 Jun 29;25(28):3956-62. 31. Ekmekcioglu S, Ellerhorst JA, Prieto VG, Johnson MM, Broemeling LD, Grimm EA. Tumor iNOS predicts poor survival for stage III melanoma patients. Int J Cancer. 2006 Aug 15;119(4):861-6. 32. Westney OL, Scott S, Wood CG, Eddings T, Johnson MM, Taylor JM, MCguire E, Pisters LL. Suburethral Sling at the Time of Radical Prostectomy in Patients at High risk for Postoperative Incontinence. BJU Int. 2006 Aug;98(2):308-13. 33. Gannon CJ, Rousseau DL, Ross MI, Johnson MM, Lee JE, Mansfield PF, Cormier JN, Prieto VG, Gershenwald JE. Accuracy of lymphatic mapping and sentinel lymph node biopsy after previous wide local excision in patients with primary melanoma. Cancer 2006 Dec 1;107(11):2647-52. 34. Prieto VG, Mourad-Zeidan AA, Melnikova V, Johnson MM, Lopez A, Diwan AH, Lazar AJF, Shen SS, Zhang PS, Reed JA, Gershenwald JE, Raz A, Bar-Eli M. Galectin-3 Expression Is Associated with Tumor Progression and Pattern of Sun Exposure in Melanoma. Clin Cancer Res. 2006 12: 6709-6715. 35. Albitar M, Vose JM, Johnson MM, Do KA, Day A, Jilani I, Kantarjian H, Keating M, O'Brien SM, Verstovsek S, Armitage JO, Giles FJ. Clinical relevance of soluble HLA-I and beta2-microglobulin levels in non-Hodgkin's lymphoma and Hodgkin's disease. Leuk Res. 2007 Feb;31(2):139-45. 36. Tellez CS, Davis DW, Praetor VG, Gershenwald JE, Johnson MM, McCarty M, Bar-Eli M. Quantitative Analysis of Melanocytic Tissue Array Reveals Inverse Correlation between Activator Protein-2alpha and Protease-Activated Receptor-1 Expression during Melanoma Progression. J Invest Dermatol. 2007 Feb;127(2):387-93. 37. Burjonroppa SC, Tong AT, Xiao LC, Johnson MM, Yusuf SW, Lenihan DJ. Cancer patients with markedly elevated B- type natriuretic peptide may not have volume overload. Am J Clin Oncol. 2007 Jun;30(3):287-93. 38. Chakravarti N, Lotan R, Diwan AH, Warneke CL, Johnson MM, Prieto VG. Decreased Expression of Retinoid Receptors in Melanoma: Entailment in Tumorigenesis and Prognosis. Clin Cancer Res. 2007. 13:4817-4824. 39. Mathew P, Thall PF, Bucana CD, Oh WK, Morris MJ, Jones DM, Johnson MM, Wen S, Pagliaro LC, Tannir NM, Tu SM, Meluch AA, Smith L, Cohen L, Kim SJ, Troncoso P, Fidler IJ, Logothetis CJ. Platelet-Derived Growth Factor Receptor Inhibition and Chemotherapy for Castration-Resistant Prostate Cancer with Bone Metastases, Clin Cancer Res. 2007. 13(19):5816-24. 40. Bedikian AY, Johnson MM, Warneke CL, Papadopoulos N, Hwu WJ, Kim K, Hwu P. Systemic Therapy for Unresectable Metastatic Melanoma: Impact of Biochemotherapy on Long-term Survival. J Immunotoxicol. 2008 Apr;5(2):201-7. 41. Simeone AM, McMurtry V, Nieves-Alicea R, Saavedra JE, Keefer LK, Johnson MM, Tari AM. TIMP-2 Mediates the Anti- Invasive Effects of the Nitric Oxide-Releasing Prodrug JS-K in Breast Cancer Cells. Breast Cancer Research, 2008;10(3):R44. Epub 2008 May 12. 42. Hoff AO, Toth BB, Altundag K, Johnson MM, Warneke CL, Hu M, Nooka A, Sayegh G, Guarneri V, Desrouleaux K, Cui J, Adamus A, Gagel RF, Hortobagyi GN. The Frequency and Risk Factors Associated with Osteonecrosis of the Jaw in Cancer Patients Treated with Intravenous Bisphosphonates. J Bone Miner Res. 2008 Jun;23(6):826-36. Epub 2008 Feb 5. 43. Bedikian AY, Johnson MM, Warneke CL, Papadopoulos NE, Kim K, Hwu WJ, McIntyre S, Hwu P. Prognostic Factors that Determine the Long-term Survival of Patients with Unresectable Metastatic Melanoma, Cancer Invest. 2008 Jul;26(6):624-33. 44. Gershenwald JE, Andtbacka RHI, Prieto VG, Johnson MM, Diwan AH, Lee JE, Mansfield PF, Cormier JN, Schacherer CW, Ross MI. Microscopic Tumor Burden in Sentinel Lymph Nodes Predicts Synchronous Nonsentinel Lymph Node Involvement in Patients with Melanoma. J Clin Oncol. 2008 Sep 10;26(26):4296-303. Epub 2008 Jul 7. 45. Kim KB, Eton O, Davis DW, Frazier ML, McConkey DJ, Diwan AH, Papadopoulos NE, Bedikian AY, Camacho LH, Ross MI, Cormier JN, Gershenwald JE, Lee JE, Mansfield PF, Billings LA, Ng CS, Charnsangavej C, Bar-Eli M, Johnson MM, Murgo AJ, Prieto VG. Phase II Trial of Imatinib Mesylate in patients with metastatic melanoma. Brit J Cancer. 2008 Sep 2;99(5):734-40. Epub 2008 Aug 19. 153

46. Braiteh F, Soriano AO, Garcia-Manero G, Hong D, Johnson MM, Silva LdeP, Yang H, Alexander S, Wolff J, Kurzrock R. Phase I Study of Epigenetic Modulation with 5-Azacytidine and Valproic Acid in Patients with Advanced Cancers. Clin Cancer Res. 2008 Oct 1;14(19):6296-301. 47. Greene VR, Johnson MM, Grimm EA, Ellerhorst JA. Frequencies of NRAS and BRAF Mutations Increase from the Radial to the Vertical Growth Phase in Cutaneous Melanoma, J Invest Dermatol. 2009 Jun;129(6):1483-8. 48. Zafar GI, Grimm EA, Wei W, Johnson MM, Ellerhorst JA. Genetic Deficiency of Complement Isoforms C4A or C4B Predicts Improved Survival of Metastatic Renal Cell Carcinoma. J Urol. 2009 Mar;181(3):1028-34. 49. Petersson F, Diwan AH, Ivan D, Gershenwald JE, Johnson MM, Harrell R, Prieto VG. Immunohistochemical Detection of Lymphovascular Invasion with D2-40 in Melanoma Correlates with Sentinel Lymph Node Status, Metastasis and Survival. J Cutan Pathol. 2009: 36: 1157–1163. 50. Tu SM, Lopez A, Leibovici D, Bilen MA, Evliyaoglu F, General RD, Aparicio A, Pagliaro LC, Guo CC, Kuban DA, Johnson MM, Logothetis CJ, Lin SH, PistersLL. Ductal Adenocarcinoma of the Prostate – Clinical Features and Implications after Local Therapy. Cancer. 2009 Jul 1;115(13):2872-80. 51. Tu SM, Jones D, Mathew P, Johnson MM, Wong FC, Logothetis C. Phase I Study Of Concurrent Weekly Docetaxel And Repeated 153sm-Lexidronam In Patients With Androgen-Independent Prostate Cancer. J Clin Oncol. 2009 Jul 10;27(20):3319-24. 52. Kim KB, Legha SS, Gonzalez R, Anderson CM, Johnson MM, Liu P, Papadopoulos NE, Eton O, Plager C, Buzaid AC, Prieto VG, Hwu WJ, Roe AM, Alvarado G, Hwu P, Ross MI, Gershenwald JE, Lee JE, Mansfield, PF, Benjamin RS, Bedikian AY. A Randomized Phase III Trial of Biochemotherapy versus Interferon-alpha-2b for Adjuvant Therapy in Patients at High Risk for Melanoma Recurrence. Melanoma Res. 2009 Feb;19(1):42-9. 53. Jonasch E, Corn P, Pagliaro L, Warneke CL, Johnson MM, Tamboli P, Ng C, Aparicio A, Ashe R, Wright JJ, Tannir N. Upfront Randomized phase II trial of sorafenib versus sorafenib and low-dose interferon alpha in patients with advanced renal cell carcinoma: Clinical and biomarker analysis. Cancer. 2010 Jan 1;116(1):57-65. 54. Soong SJ, Ding S, Coit D, Balch CM, Gershenwald JE, Thompson JF, Gimotty P; AJCC Melanoma Task Force. Predicting Survival Outcome of Localized Melanoma: An Electronic Prediction Tool Based on the AJCC Melanoma Database. Ann Surg Oncol. 2010 Aug;17(8):2006-14. Epub 2010 Apr 9. 55. Vadhan-Raj S, Trent J, Patel S, Zhou X, Johnson MM, Araujo D, Ludwig JA, O’Roark S, Gillenwater AM, Bueso-Ramos C, El-Naggar AK, Benjamin RS. Single-dose Palifermin Prevents Severe Oral Mucositis in Cancer Patients during Multi- cycle Chemotherapy: A Double-blind, Randomized Trial. Ann Int Med. 2010 Sep 21;153(6):358-67. 56. Ellerhorst JA, Greene VR, Ekmekcioglu S, Warneke CL, Johnson MM, Cooke CP, Wang LE, Prieto VG, Gershenwald JE, Wei Q, Grimm EA. Clinical Correlates of NRAS and BRAF Mutations in Primary Human Melanoma. Clin Cancer Res. 2010 Oct 25. [Epub ahead of print] 57. Bedikian AY, Johnson MM, Warneke CL, Papadopoulos NE, Kim KB, Hwu WJ, McIntyre S, Rohlfs M, Homsi J, Hwu P. Does Complete Response to Systemic Therapy in Patients with Stage IV Melanoma Translate into Long-term Survival? Melanoma Res. 2010 Nov 22. [Epub ahead of print] 58. Ayala-Ramirez M, Feng L, Johnson MM, Habra MA, Rich T, Busaidy N, Cote GJ, Perrier N, Patel S, Waguespack S, Jimenez C. Clinical Factors for Metastases and Overall Survival in Patients with Pheochromocytomas and Sympathetic Paragangliomas: Primary Tumor Size and Primary Tumor Type. J Clin Endocrinol Metab. 2010 Dec 29. [Epub ahead of print] 59. Thompson JF, Soong SJ, Balch CM, Gershenwald JE, Ding S, Coit DG, Flaherty KT, Gimotty PA, Johnson T, Johnson MM, Leong SP, Ross MI, Byrd DR, Cascinelli N, Cochran AJ, Eggermont AM, McMasters KM, Mihm MC Jr, Morton DL, Sondak VK. Prognostic Significance of Mitotic Rate in Localized Primary Cutaneous Melanoma: An Analysis of Patients in the Multi-Institutional American Joint Committee on Cancer Melanoma Staging Database. J Clin Oncol. 2011 Apr 25. [Epub ahead of print] 60. Berry DA,Ueno NT, Johnson MM, Lei X,Caputo J, Smith DA,Yancey LJ, Crump M, Stadtmauer EA, Biron P, Crown JP, Schmid P, Lotz JP, Rosti G, Bregni M, Demirer T. High-dose chemotherapy with autologous hematopoietic stem cell transplantation in metastatic breast cancer: Overview of six randomized trials, J Clin Oncol. 2011 Aug 20;29(24):3224-31. Epub 2011 Jul 18. 61. Berry DA, Ueno NT, Johnson MM, Lei X, Caputo J, Rodenhuis S, Peters WP, Leonard RC, Bearman SI, Tallman MS, Bergh J, Nitz UA, Gianni A, Basser RL, Zander AR, Coombes RC, Roché H, Tokuda Y, Schrama JG, Hortobagyi GN, Bregni M, Demirer T. High-dose chemotherapy with autologous stem cell support as adjuvant therapy in breast cancer: Overview of 15 randomized trials, J Clin Oncol. 2011 Aug 20;29(24):3214-23. Epub 2011 Jul 18. 62. Kim K, Kim KB, Prieto V, Joseph RW, Diwan AH, Gallick GE, Papadopoulos NE, Bedikian AY, Camacho LH, Hwu P, Ng CS, Wei W, Johnson MM, Wittemer SM, Vardeleon A, Reckeweg A, Colevas AD. A randomized phase II study of cilengitide (EMD 121974) in patients with metastatic melanoma. Melanoma Res. 2012 Aug;22(4):294-301. PMID: 22668797 [PubMed - indexed for MEDLINE] 63. Chakravarti N, Peddareddigari VGR, Warneke CL, Johnson MM, Overwijk MW, Hwu P, Prieto VG. Differential Expression of the G-protein-coupled Formyl Peptide Receptor in Melanoma Associates with Aggressive Phenotype, AmJ Dermatopathology, Am J Dermatopathol. 2013 Apr;35(2):184-90. PMID: 23147350 [PubMed - indexed for MEDLINE] 64. Bilen MA, Johnson MM, Mathew P, Pagliaro LC, Araujo JC, Aparicio A, Corn PG, Tanir N, Wong F, Fisch MJ, Logothetis C, Tu SM. Randomized phase 2 study of bone-targeted therapy containing strontium-89 in advanced castrate- 154

sensitive prostate cancer. Cancer. Cancer. 2015 Jan 1;121(1):69-76. doi: 10.1002/cncr.28971. Epub 2014 Aug 22. PMID: 25155428[PubMed - in process]

Abstracts: 1. Barrows LH, Stricklin MD, Siconolfi SF. The Relationship Between Bioelectrical Resistance and Fat-Free Mass Under Conditions of Different Frequency, Temperature, and Time. [Presented at the Aerospace Medical Association annual meeting in Cincinnati, OH, May, 1991]. 2. Lathers CM, Charles JB, Mukai CN, Riddle JM, Jacobs FO, Bennett BS, Lewis D, Fortney S, Frey MB, Stricklin MD, Schneider VS. Heart Rate Responses to Lower Body Negative Pressure (LBNP) During Seventeen Weeks of Bedrest. [Presented at the Federation of American Societies for Experimental Biology annual meeting in Anaheim, CA, April, 1992]. 3. Hayes JC, McBrine JJ, Roper ML, Stricklin MD, Siconolfi SF, Greenisen MC. Effects of Space Shuttle Flights on Skeletal Muscle Performance. [Presented at the Federation of American Societies for Experimental Biology annual meeting in Anaheim, CA, April, 1992]. 4. Yang WT, Whitman GJ, Johnson MM, Bolanos-Clark M, Aldefer J, Kushwaha AC. Needle Localization for Excisional Biopsy of Breast Lesions: Comparison of Full Field Digital versus Screen-film Mammographic Guidance on Procedural Time. [Presented at the 88th Annual Meeting of the Radiological Society of North America, December 1-6, 2002]. RADIOLOGICAL SOC, Source: RADIOLOGY Volume: 225 Pages: 417-417 Supplement: Suppl. S Published: NOV 2002. 5. Pawlik TM, Ross MI, Johnson MM, Bedrosian I, Schacherer CW, Mansfield PF, Lee JE, Cormier JN, Gershenwald, JE. Predictors and natural history of in-transit melanoma after sentinel lymphadenectomy [Presented at the 57th Annual Meeting of the Society of Surgical Oncology, New York, NY, March 18-21, 2004]. LIPPINCOTT WILLIAMS & WILKINS, Source: ANNALS OF SURGICAL ONCOLOGY Volume: 11 Issue: 2 Pages: S61-S61 Supplement: Suppl. S Published: FEB 2004. 6. Gershenwald JE, Prieto VG, Schacherer CW, Johnson MM, McClain DM, Mansfield PF, Lee JE, Ross MI. The impact of microscopic tumor burden in sentinel node-positive melanoma patients: Implications for future clinical trial design. [Presented at the Second International Melanoma Research Congress, Phoenix, AZ, November 13-16, 2004]. 7. Gannon CJ, Rousseau Jr DL, Ross MI, Johnson MM, Lee JF, Mansfield PF, Cormier JN, Prieto VG, Gershenwald JE. Sentinel lymph node biopsy after previous wide local excision accurately reflects the status of the regional nodal basin in patients with primary melanoma. [Presented at the 4th International Sentinel Node Conference, Los Angeles, CA, December 3-6, 2004]. 8. Aloia T, Gershenwald JE, Ross MI, Lee JE, Johnson MM, Cormier JN, Ng C, Mansfield PF. Utility of CT and MRI Staging in Patients with Sentinel Lymph Node-Positive Melanoma. [Presented at the 4th International Sentinel Node Conference, Los Angeles, CA, December 3-6, 2004]. 9. Bedikian AY, Johnson MM, Broemeling LD, Papadopoulos NE, Kim KB, Camacho LH, Hwu P. Prognostic Factors Determining Long Term Survival of Patients with Unresectable Stage III and Stage IV Metastatic Melanoma (MM) Treated with Combination therapy or IL-2 based Biochemotherapy (BCC). Journal of Clinical Oncology, 2005 ASCO Annual Meeting Proceedings. Vol 23, No. 16S, Part I of II (June 1 Supplement), 2005: 7544. 10. Prieto VG, Mourad-Zeidan AA, Johnson MM, Diwan AH, Lazar AJ, Shen SS, Reed JA, Bar-Eli M. Analysis of Galectin-3 Expression in Melanocytic Lesions by Tissue Array. Possible Involvement in Tumor Progression. [Presented at the United States and Canadian Academy of Pathology Annual Meeting, September 2005]. 11. Guray M, Sun M, Albarracin CT, Edelweiss M, Johnson MM, Esteva FJ, Yu D, Sahin AA. Significant loss of PTEN protein expression in lymph node metastases of primary breast cancer: An immunohistochemical study using tissue microarray. NATURE PUBLISHING GROUP. Source: LABORATORY INVESTIGATION Volume: 86, Pages: 29A- 29A Supplement: Suppl. 1 Meeting Abstract: 122 Published: JAN 2006. 12. Prieto VG, Diwan AH, Lazar AFJ, Johnson MM, Schacherer C, Gershenwald, JE. Histologic quantification of tumor size in sentinel lymph node metastases correlates with prognosis in patients with cutaneous malignant melanoma. NATURE PUBLISHING GROUP. Source: LABORATORY INVESTIGATION Volume: 86 Pages: 87A-87A Supplement: Suppl. 1 Meeting Abstract: 391 Published: JAN 2006. 13. P Mathew, PF Thall, MM Johnson, WK Oh, AA Meluch, MJ Morris, P Troncoso, CD Bucana, IJ Fidler, CJ Logothetis. Preliminary results of a randomized placebo-controlled double-blind trial of weekly docetaxel combined with imatinib in men with metastatic androgen-independent prostate cancer (AIPC) and bone metastases (BM). [Presented at the 2006 Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Source: JOURNAL OF CLINICAL ONCOLOGY Volume: 24 Issue: 18 Pages: 232S-232S Part: Part 1 Suppl. S Supplement: Part 1 Suppl. S Published: JUN 20 2006. 14. Moussallem C, Lopez A, Moore S, Gauthier AM, Johnson M, Ibrahim N. Fulvestrant (F) in metastatic breast cancer: standard dose (Std) vs loading dose (Ld). A retrospective study. [Presented at the 2006 Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Journal of Clinical Oncology, 2006 ASCO Annual Meeting Proceedings Part I. Vol 24, No. 18S (June 20 Supplement), 2006: 10575 15. Andtbacka RH, Gershenwald JE, Prieto VG, Johnson M, Diwan H, Lee JE, Mansfield PF, Schacherer CW, Ross MI. Microscopic tumor burden in sentinel lymph nodes (SLNs) best predicts nonsentinel lymph node (NSLN) involvement in 155

patients with melanoma. [Presented at the 2006 Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. AMER SOC CLINICAL ONCOLOGY, Source: JOURNAL OF CLINICAL ONCOLOGY Volume: 24 Issue: 18 Pages: 454S-454S Part: Part 1 Suppl. S Supplement: Part 1 Suppl. S Published: JUN 20 2006. 16. Lee JE, Wang Y, Vo Amy, Gershenwald JE, Ross MI, Johnson MM, McClain DM, Jin R. Association of HLA class II alleles with melanoma incidence. [Presented at the 14th SPORE Investigators’ Workshop, Baltimore, MD, July 2006] 17. Chun YS, Wang Y, Gershenwald JE, Ross MI, Johnson MM, Liu P, Schacherer CW, Reveille JD, Lee JE. HLA class II alleles predict recurrence and pattern of failure in early-stage melanoma patients. Abstract ASCO No. 8503. [Presented at the 2007 Annual Meeting of the American Society of Clinical Oncology, Chicago, IL, June 4-8, 2007]. [Journal of Clinical Oncology, 2007 ASCO Annual Meeting Proceedings Part I. Vol 25, No. 18S (June 20 Supplement), 2007: 8503]. 18. Kim KB, Diwan AH, Papadopoulos NE, Bedikian AY, Camacho LH, Hwu P, Johnson MM, Colevas DA, Prieto VG.A Randomized Phase II Study of Cilengitide (EMD 121974) in Patients with Metastatic Melanoma. American Society for Clinical Oncology, January 2007 [Journal of Clinical Oncology, 2007 ASCO Annual Meeting Proceedings Part I. Vol 25, No. 18S (June 20 Supplement), 2007: 8548]. 19. Berry DA, Ueno NT, Johnson MM, Lei X, Lopez V, Caputo J, Yancey LJ, Bregni M, Demirer T. High-dose chemotherapy with autologous stem-cell support versus standard-dose chemotherapy: meta-analysis of individual patient data from 15 randomized adjuvant breast cancer trials. [Presented at the 2007 meeting of the San Antonio Breast Cancer Symposium.] SPRINGER, Source: BREAST CANCER RESEARCH AND TREATMENT Volume: 106 Pages: S5- S5 Supplement: Suppl.1 Published: DEC 2007. 20. Gershenwald J, Thompson J , Warneke C, Ross M, Johnson M, McMasters K, Delman MK, Sabe l M, Noyes D, Kraybill W, Coit D, Leong S, Eggermont A. (Re)-Defining Indications For Sentinel Lymph Node Biopsy (SLNB) in Patients (Pts) With Thin Melanoma - Preliminary Results of an International Thin Melanoma Working Group. [Presented at the 2007 meeting of the International Sentinel Node Society, Sydney, Australia, February 18-20, 2008.] SPRINGER, Source: ANNALS OF SURGICAL ONCOLOGY Volume: 15 Pages: 4-4 Supplement: Suppl. 1 Published: FEB 2008. 21. Wang Y, Kesmodel SB, Vo AH, Liu H, Chun YS, Gershenwald JE, Cormier JN, Ross MI, Wang DY, McClain DM, Schacherer CW, Henderson L, Liu P, Johnson MM, Berry DA, Reveille JD, Lee JE. Association of the TGF-Beta1 codon 10 T polymorphism with improved outcomes in early-stage melanoma patients. [Presented at the 2008 annual meeting of the American Association of Cancer Research, San Diego, CA, April 12-16, 2008]. [AACR Meeting Abstracts, Apr 2008; 2008: 4690]. 22. Kebriaei P, Jones D, Johnson MM, Gutierrez K, Giralt S,de Lima M, Korbling M, Khouri IF, Popat U, Qazilbash MH, Alousi A, Ciurea S, Cooper L, Shpall E, Champlin R.Addition of Umbilical Cord Blood (UCB) Unit to Reduced Intensity Conditioning (RIC) Regimen to Augment Graft Versus Tumor (GVT) in Patients (pts) with Advanced Hematologic Malignancies. [Presented at the 2009 annual meeting of the International Umbilical Cord Blood Transplantation Symposium, Los Angeles, CA, June 5-6, 2009]. 23. Caudle A, Ross MI, Prieto VG, Warneke CL, Lee JE, Johnson MM, Gardner, Royal, Cormier, Lucci, Gershenwald JE. Mitotic Rate Predicts Sentinel Lymph Node Involvement in Cutaneous Melanoma: Impact of the 7th Edition AJCC Melanoma Staging System, [Presented at the 2010 annual meeting of the Society of Surgical Oncology, St. Louis, Missouri, March 3-7, 2010]. 24. Chakravarti N, Peddareddigari VGR, Warneke CL, Johnson MM, Hwu P, Prieto VG. Increased expression of formyl peptide receptor (FPR) and formyl peptide receptor like-1 (FPRL1) correlates with high-risk clinical/histologic features in melanoma. [Presented at the 2011 annual meeting of the American Association for Cancer Research, Orlando, Florida, April 2 – 6, 2011].

Book Chapters: 1. AJCC Cancer Staging Manual: 7th Edition (2010) Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A (Eds). Springer, New York, New York. (Melanoma Staging Chapter)

Letters to the Editor: 1. Choi H, Johnson MM. Reply. Am J Roentgenol. 2005 Nov; 185(5):1366-7.

Other - Posters: 1. Barrows LH, Stricklin MD, Wong WW, Klein PD, Inners, LD, Siconolfi SF. Comparison of Total Body Water Estimates from 18O and Bioelectrical Response Prediction Equations. [Poster presented at the Federation of American Societies for Experimental Biology annual meeting in Anaheim, CA, April, 1992]. 2. Bell M, Stricklin MD. A Macro to Facilitate the Visualization of Individual Patient Efficacy and Safety During an Investigational (Phase III) Clinical Trial. [Poster presented at the SAS® Users Group International annual meeting in Dallas, TX, April, 1994]. 3. Stricklin, MD. An Ophthalmic Clinical Trial with a Group Sequential Design and Multiple Comparisons. [Poster presented at the Society for Clinical Trials annual meeting in Houston, TX, May, 1994]. 4. Bell M, Stricklin MD, Munsell, MF. Electronic Documentation for Validation of Statistical Analysis Programming for Data from Clinical Trials. [Poster presented at the Society for Clinical Trials annual meeting in Seattle, WA, May, 1995]. 5. Moore, MD, Herson J, Gonen M. Analysis of Clinical Events Using Linearized Rates. [Poster presented at the American 156

Statistical Association annual meeting in Dallas, TX, August, 1998]. 6. Gayed I, Sureshbabu W, Iyer R, Macapinlac H, Johnson M, Podoloff DA. Positron Emission Tomography Versus Computerized Tomography for the Identification of Melanoma Metastases. [Poster presented at the 49th Annual Meeting of the Society of Nuclear Medicine, June 15-19, 2002]. SOC NUCLEAR MEDICINE, Source: JOURNAL OF NUCLEAR MEDICINE Volume: 43 Issue: 5 Pages: 294P-294P Supplement: Suppl. S Meeting Abstract: 1187 Published: MAY 2002. 7. Gayed IW, Vu TT, Macapinlac HA, Johnson MM, Delpassand ES, Wong F, Kim E, Podoloff DA. Comparison of Bone and F-18 FDG Scans in the Evaluation of Bony Metastases. [Poster presented at the 49th Annual Meeting of the Society of Nuclear Medicine, June 15-19, 2002]. 8. Gayed I, Boccalandero F, Sdringola S, Johnson M, Butler C, Gee-Johnson S, Swafford I. Comparison of Resting Echocardiography and Gated SPECT in the Evaluation of Wall Motion Abnormalities. [Poster presented at the 7th Annual Meeting of the American Society of Nuclear Cardiology, September 26-29, 2002]. 9. Wang XS, Johnson MM, Broemeling LD, Janjan N, Komaki R, Mendoza T, Cleeland CS. Longitudinal Model for Cancer- Related Symptoms During Radiotherapy Among Patients with Gastrointestinal and Lung Cancer. [Poster presented at the Annual Meeting of the International Society for Quality of Life Research, October 30 - November 2, 2002]. 10. Vadhan-Raj S, Skibber JM, Crane C, Bueso-Ramos CE, Rodriquez-Bigas MA, Feig BW, Lin EH, Ajani JA, Collard M, Johnson MM, Hamilton SR, JanJan N. Randomized, Double-Blind, Placebo-Controlled Trial of Epoetin Alfa (Procrit) in Patients with Rectal and Gastric Cancer Undergoing Chemo-Radiotherapy (CT/RT) Followed by Surgery: Early Termination of the Trial Due to Increase Incidence of Thromboembolic Events (TEE). Poster presented at the American Society of Hematology 46th Annual Meeting, San Diego, CA, December 4-7, 2004]. AMER SOC HEMATOLOGY, Source: BLOOD Volume: 104 Issue: 11 Pages: 797A-797A Part: Part 1 Meeting Abstract: 2915 Published: NOV 16 2004. 11. Pawlik TM, Ross MI, Johnson MM, Prieto VG, Schacherer CW, McClain DM, Mansfield PF, Lee JE, Cormier JN, Gershenwald JE. Sentinel lymph node biopsy for primary cutaneous desmoplastic melanoma: Is there a role? [Poster presented at the 4th International Sentinel Node Conference, Los Angeles, CA, December 3-6, 2004]. 12. Sun X, Wang E, Jones DM, Shen H, Johnson MM, Issa JP, Amin H, Ginsberg CF, Kantarjian HM, Andreeff M, Kornblau SM, Glassman AB, Arlinghaus RB. SOX4 Gene Expression in Human Leukemia. [Poster presented at the American Association for Cancer Research Annual Meeting, Washington, D.C., April 1- 5, 2006]. 13. Hoff AO, Toth BB, Altundag K, Guarneri V, Adamus A, Nooka AK, Sayegh GG, Johnson MM, Gagel RF, Hortobagyi GN. Osteonecrosis of the Jaw in Patients Receiving Intravenous Bisphosphonate Therapy. [Poster presented at the 2006 Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Source: JOURNAL OF CLINICAL ONCOLOGY Volume: 24 Issue: 18 Pages: 475S-475S Part: Part 1 Suppl. S Supplement: Part 1 Suppl. S Meeting Abstract: 8528 Published: JUN 20 2006. 14. Gershenwald JE, Morton DL, Thompson JF, Kirkwood JM, Soong S, Balch CM, Eggermont AM, Sondak VK, Johnson MM, Warneke C, Collaborators of the AJCC/UICC Melanoma Task Force. Staging and prognostic factors for stage IV melanoma: Initial results of an American Joint Committee on Cancer (AJCC) international evidence-based assessment of 4895 melanoma patients. Poster presented at the 44th Annual Meeting of the American Society of Clinical Oncology, May 2008 [J Clin Oncol 26: 2008 (May 20 suppl; abstr 9035)]. 15. Ekmekcioglu S, Johnson MM, Gershenwald JE, Prieto VG, Grimm EA. iNOS Expression in Tumor Cells and Tumor Associated Macrophages in Melanoma. [Poster presented at Chemical and Biological Aspects of Inflammation and Cancer, October 14-17, 2008. 16. Albarracin CT, Sigauke E, Whitman G, Yang WT, Resetkova E, Johnson MM, Nguyen CV, Sneige N. Atypical and Columnar Cell Lesions in Breast Needle Biopsies for Indeterminate Microcalcifications: Predictors of Higher Risk Findings Requiring Surgical Excision. [Poster presented at the 2008 meeting of the San Antonio Breast Cancer Symposium.] AMER ASSOC CANCER RESEARCH, Volume: 69 Issue: 2 Pages: 206S-206S Supplement: Suppl. S Published: JAN 15 2009. 17. Berry DA, Ueno NT, Johnson MM, Lei X, Smith DA, Caputo J, Yancey LJ, Bregni M, Demirer T. High-dose chemotherapy with autologous stem-cell support versus standard-dose chemotherapy: meta-analysis of individual patient data from 6 randomized metastatic breast cancer trials. [Poster presented at the 2008 meeting of the San Antonio Breast Cancer Symposium.] AMER ASSOC CANCER RESEARCH, Source: CANCER RESEARCH Volume: 69 Issue: 2 Pages: 381S-381S Supplement: Suppl. S Published: JAN 15 2009. 18. Atkins MB, Long GV, Warneke CL, Carlino MS, DeRose E, Johnson MM, Brown PT, Lee MY, Kefford RF, Gershenwald JE. Unraveling the Prognostic Heterogeneity in Patients with Advanced Melanoma Between Australia and the United States: Preliminary Report of the PHAMOUS Study. Poster presented at American Society Clinical Oncology Annual Meeting, June 2010 [J Clin Oncol 28:15s, 2010 (suppl; abstr 8516)]. 19. Carlino MS, Atkins MB, Warneke CL, Long GV, DeRose ER, Johnson MM, Brown PT, Lee MY, Gardner J, Hamilton A, Alvarado G, Kefford R, Gershenwald JE. Differences between Australia (OZ) and the United States (US) in the patterns, prognosis, and treatment of melanoma CNS metastases: analysis from the PHAMOUS (prognostic heterogeneity in patients with advanced melanoma between OZ and the US) study. Poster presented at Society for Melanoma Research, 7th International Melanoma Congress, Sydney, Australia, November 2010. 20. Long GV, Atkins MB, Warneke CL, Carlino MS, DeRose E, Johnson MM, Brown PT, Roberson F, Gardner J, Alvarado G, Lee MY, Kefford RF, Gershenwald JE.. Unraveling the Prognostic Heterogeneity in Patients with Advanced 157

Melanoma (MM) Between Australia (OZ) and the United States (US): The PHAMOUS STUDY. Poster presented at Society for Melanoma Research, 7th International Melanoma Congress, Sydney, Australia, November 2010. 21. Vadhan-Raj S, Hagemeister F, Fayad LE, Zhou X, O’Roark SS, Ames K, Rodriguez MA, Fanale MA, Pro B, MM Johnson, McLaughlin P, Bueso-Ramos CE, Younes A, Kwak L, Romaguera JE. Randomized, double-blind, placebo- controlled, dose and schedule-finding study of AMG 531 in chemotherapy-induced thrombocytopenia (CIT): Results of a phase I/II study. Poster presented at 2010 ASH Annual Meeting, Blood (ASH Annual Meeting Abstracts) 2010 116: Abstract 1544). 22. Chakravarti N, Ivan D, Ross MI, Ilagan JL, Warneke CL, Kim K, Papadopoulos NE, Cain S, Gershenwald JE, Johnson MM, Bedikian AY, Royal RE, Cormier JN, Hanna EY, Lee JE, Prieto VG, en Hwu WJ. Biomarker study in patients with resectable AJCC stage IIIc or stage IV (M1a) melanoma treated in a randomized phase II neoadjuvant trial. Poster presented at 2013 American Society Clinical Oncology Annual Meeting (abstract 9047). 23. Ky B, Warneke CL, Lenihan D, Cheema PS, Moore DF, Campbell MG, C Yeshwant, Adams PT, Krone R, Carver JR, Nasta S, Svoboda J, Schuster S, Reddy N, Patel S, Rieber A, Johnson M, Fisch MJ. Clinical Risk Prediction in Anthracycline Cardiotoxicity. Poster presented at the 2014 American Society of Clinical Oncology Annual Meeting (abstract 9624). 24. Stevens PL, Lenihan DJ, Ky B, Warneke CL, Johnson MM, Abramson VG, Mayer IA, Adams PT, Campbell MG, Cheema PS, Moore DF, Yeshwant C, Carver JR, Fisch M Prediction and early detection of anthracycline-related cardiotoxicity using cardiac biomarkers. Poster presented at the 2014 American Society of Clinical Oncology Annual Meeting (abstract 9644).

TEACHING: Training Programs: - Introduction to Statistics. Presented through the MD Anderson Office of Protocol Research – Quality Assurance as part of their orientation program, “Clinical Research Training - History of Research and IRB, Informed Consent Process & Documents & Introduction to Statistics.” October 2002; January 2003; February 2003; February 2004; May 2004; June 2004; July 2004; June 2005, August 2007 - Data Analysis: Summarizing and Presenting Data. Presented through the MD Anderson Office of Trainee Support Services as part of their Core Curriculum program. March 2002; April 2004; March 2005; July 2005, July 2006 - Statistics in Clinical Trials. Presented through the MD Anderson Office of Research Education and Regulatory Management. April 2009

PROFESSIONAL MEMBERSHIP/ACTIVITIES: Local/State: - Houston Area Chapter of the American Statistical Association, Member - National and International: - American Statistical Association, Member - International Biometric Society, Member

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MICHAEL H. KUTNER Rollins Professor Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health 1518 Clifton Road, NE Atlanta, Georgia 30322 Voice: 404-712-9708 Email: [email protected]

EDUCATION Ph.D. 1971 Texas A & M University, College Station, Texas, in statistics. Doctoral research in the area of variance component estimation. M.S. 1962 Virginia Polytechnic Institute and State University, Blacksburg, Virginia, in statistics. B.S. 1960 Central Connecticut State College, New Britain, Connecticut, in mathematics.

PROFESSIONAL EMPLOYMENT • 2009 - Present Rollins Professor, Department of Biostatistics and Bioinformatics, Emory University, Rollins School of Public Health, Atlanta, Georgia. • 2004 - 2009 Rollins Professor and Chair, Department of Biostatistics and Bioinformatics, Emory University, Rollins School of Public Health, Atlanta, Georgia. • 2002 - 2003 Interim Chair, Department of Biostatistics, Emory University, Rollins School of Public • Health, Atlanta, Georgia. • 2001 - Present Director, Biostatistics Consulting Center, Department of Biostatistics, Emory University, Rollins School of Public Health, Atlanta, Georgia. • 2000 - 2003 Research Professor, Department of Biostatistics, Emory University, Rollins School of • Public Health, Atlanta, Georgia. • 1994 - 1999 Chairman, Department of Biostatistics and Epidemiology, The Cleveland Clinic • Foundation, Cleveland, Ohio. • 1991 - 1993 Professor, Division of Biostatistics and Associate Dean for Academic Affairs, School of Public Health, Emory University, Atlanta, Georgia. • 1990 - 1991 Director, Division of Biostatistics and Associate Dean for Academic Affairs, School of Public Health, Emory University, Atlanta, Georgia. • 1988 - 1990 Professor and Director, Division of Biostatistics, Department of Epidemiology and • Biostatistics, Emory University, Atlanta, Georgia. • 1986 - 1988 Professor and Acting Chairman, Department of Statistics and Biometry, Emory • University, Atlanta, Georgia. • 1981 - 1985 Professor of Statistics and Biometry, Emory University, Atlanta, Georgia. • 1975 - 1980 Associate Professor of Statistics and Biometry, Emory University, Atlanta, Georgia. • 1971 - 1975 Assistant Professor of Statistics and Biometry, Emory University, Atlanta, Georgia. • 1970 - 1971 Assistant Professor Statistics, Institute of Statistics, Texas A & M University; teaching graduate statistics and research connected with dissertation. • 1962 - 1967 Assistant Professor of Mathematics, College of William & Mary, Williamsburg, Virginia; teaching senior-graduate statistics and numerical analysis, differential equations, calculus. • 1964 - 1965 Dow-Badishe Chemical Company, Williamsburg, Virginia; consulting and teaching experimental design and analysis. • 1963 - 1967 NASA, Langley Air Force Base, Newport News, Virginia; part-time teaching and consulting.

PROFESSIONAL AWARDS/HONORS • 2012 – Cited as one of Texas A&M’s most distinguished alumni in book entitled, Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., Springer, Edited by Alan Agresti & Xiao-Li Meng • October 2012 – Mike Kutner Junior Faculty Poster Session named in my honor, Southern Regional Council on Statistics, Summer Research Conference • August 2011 – Recipient of the Wilfred J. Dixon Award for Excellence in Statistical Consulting, American Statistical Association, • March 2011 – Recipient of the Charles R. Hatcher, Jr., M.D., Award for Excellence in Public Health, Woodruff Health Sciences Center • November 2010 – Invited delegate of the People to People “Statistical Science Delegation” that visited China under the leadership of the President and Executive Director of the American Statistical Association. Visited Beijing (Renmin University and National Bureau of Statistics), Xi’an (Xi’an University of Finance and Economics and Northwest University) and Shanghai (East China Normal University and Fudan University).

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The purpose of the trip was to explore possible faculty and student exchange programs between our two countries. The Biostatistics Department has recruited doctoral students from both Renmin and Fudan University. • November 2009 – Inducted as member of ASPH/Pfizer Public Health Academy of Distinguished Teachers • 2009 – Recipient of Mu Sigma Rho National Statistical Honor Society Statistical Education Award for lifetime devotion to the discipline of teaching statistics • May 2008 – Recipient of the Thomas F. Sellers, Jr. Award for exemplifying the ideals of public health and serving as a role model and mentor to his colleagues • 2008 – Appointed to External Advisory Committee by the Department of Statistics, Texas A&M University • 2008-2009 – Inducted as President of the Southern Regional Council on Statistics (SRCOS) • 2008-2013 – Appointed Member of the Clinical Research Advisory Committee of the Shriner’s Hospitals • August 2006 – Recipient of Georgia Chapter, ASA, distinguished service award • October 2006 – Elected President-Elect, SRCOS (2007-2008) • March 2004 – Named Endowed Rollins Professor and Chair of Biostatistics • September 2002 – Recipient of the 2002 Southern Region Council on Statistics (SRCOS) Paul Minton Award for distinguished service to the statistical profession • September 1999 – Elected member of International Statistical Institute • June 1997 – Excellence in Research Award co-authorship on “Reducing Frailty and Falls in Older Persons: An Investigation of Tai Chi and Computerized Balance Training.” Journal of American Geriatric Society, 44:489- 497, 1996. Selected as the best paper of the decade. • May 1997 – Inducted into inaugural class of the “Academy of Distinguished Graduates,” College of Science, Texas A&M University • Aug 6, 1996 – Recipient of the Founders Award, American Statistical Association. • Dec 2, 1995 – Certificate of Appreciation in recognition of dedicated service to the American Statistical Association as member of the Board of Directors, 1993-1995. • Aug 14, 1995 – Best Invited Paper, Section on Teaching of Statistics in the Health Sciences, 1995 Joint Statistical Meetings, Orlando, Florida. (with Ralph O'Brien.) • July 1995 – NSF funded participant Academe/Industry Collaboration Project, Cal Poly, San Luis Obispo, California. • 1990-1991 – Inaugural President, NIH/GCRC Statisticians Group • September 1991 – Recipient of Chapter Service Recognition Award, Atlanta Chapter, American Statistical Association. • August 1984 – Elected Fellow of the American Statistical Association. • 1984 – Recipient of H. O. Hartley Award, Texas A&M University • Summer 1973 – NSF funded participant Regional Conference on Multivariate Statistical Analysis, Tuscaloosa, Alabama. • 1969-1970 – NIH Trainee Fellowship, Texas A&M University • 1969 – Graduate Research and Teaching Assistant, Texas A&M University. • 1967-1968 – NSF Faculty Fellowship. • 1962 – Elected Pi Mu Epsilon (Honorary Math Society). • 1960-1962 – Teaching Assistantship, Virginia Polytechnic Institute and State University.

EMORY PHILANTHROPIC GIFTS • Donated 1994 Atlanta Olympic Street banner to the Dobbs University Center • Established the Michael H. Kutner Alumnus Award given annually to recognize a former department graduate student for Distinguished Service to the Field • Established the Michael H. Kutner Outstanding Graduate Student Award given annually to a doctoral student in the Department of Biostatistics and Bioinformatics • Donated to the Department of Biostatistics and Bioinformatics paintings, artwork and potted plants for the entire 3rd floor and a portion of the 2nd floor • Donated all of the wine for the Department’s 50th Anniversary Celebration on October 17, 2014 • Donated funds to support the development of an Emory Faculty Club

BOOKS 1. Michael H. Kutner, Christopher J. Nachtsheim and John Neter, Applied Linear Regression Models, 4th edition, McGraw-Hill/Richard D. Irwin, Inc., Chicago, Illinois, 2004. (under revision) 2. Michael H. Kutner, Christopher J. Nachtsheim, John Neter and William Li, Applied Linear Statistical Models, 5th edition, McGraw-Hill/ Richard D. Irwin, Inc., Chicago, Illinois, 2005. (under revision)

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3. Christopher J. Nachtsheim and Michael H. Kutner, Introduction to Business Statistics, (under preparation)

BOOK CHAPTERS, PROCEEDINGS AND TECHNICAL REPORTS

Book Chapters: 1. Nixon DW, Moffitt SD, Olkowski Z, Ansley J, Kutner MH, Lawson DH, Heymsfield SB, Lynn MJ and Rudman D. “Parenteral, Nutritional Supplementation in Recent Advances in Clinical Nutrition, Volume 1. Howard, Alan and Baird, Ian McLean (eds). John Libbey and Company, Ltd, Londonm 1981. 2. Nixon DW, Lawson DH, Kutner MH, Moffitt SD, Ansley J, Heymsfield SB, Lynn MJ, Wesley M, Yancey R and Rudman D. “Effect of Total Parenteral Nutrition on Survival in Advanced Colon Cancer.” Cancer Detection and Prevention. HE Nieburgs (ed). Marcel Dekker, Inc, New York, 1982. 3. Waring GO III, Refractive Keratotomy for Myopia and Astigmatism, Mosby Year Book 1992; Chapter 13: Lynn MJ, Waring GO III and Kutner MH, “Predictability of Refractive Keratotomy,” pp. 341-380. Chapter 22: Nizam A, Lynn MJ, Kutner MH and Waring GO III, “Bilateral Results of Radial Keratotomy,” pp. 849-862. Chapter 24: Waring GO III, Lynn MJ and Kutner MH, “Stability of Refraction after Refractive Keratotomy,” pp. 937-968. 4. Peck R, Haugh LD and Goodman A. Statistical Case Studies: A Collaboration Between Academe and Industry. Society for Industrial and Applied Mathematics, 1998; Chapter 16: Kutner MH, Easley KA, Jones SC and Bryce GR, “Cerebral Blood Flow Cycling: Anesthesia and Arterial Blood Pressure,” pp. 203-216.

Proceedings: 1. Kutner MH, Brown AC and Miller K. “A Critique: Hair Sulfur Analysis for Evaluation of Normal and Abnormal Hair.” Proceedings of First Human Hair Symposium, 1974. 2. Tan M, Xiong X and Kutner MH. “Sequential Conditional Probability Ratio Test, Reverse Stochastic Curtailing and Stochastic Curtailing.” ASA Biopharmaceutical Section Proceedings, 1996.

Technical Reports: 1. Kutner MH. "Maximum Likelihood Analysis of Balanced Incomplete Block Models." Technical Report #7, NASA (July 1971).

DISSERTATIONS DIRECTED • 1981, Raymond P. Bain, “Comparison of the Multivariate Analysis of Variance and the Univariate Analysis of Variance for the Group by Time Repeated Measures Design.” • 1979, Gamil H. Absood, “Distributions of Functions of Gaussian Random Variables with Applications to Structural Regression Models.” • 1977, Jesse Meneses, “On Univariate and Multivariate Statistical Analyses of Repeated Measures and Applications to a Maintenance Study of Heroin Addicts.” • 1976, Robert Mosteller, “Regional Discriminant Analysis: Assessment of Breast Cancer Risk.” • 1974, Brent Blumenstein, “Maximum Likelihood Estimation of Linear Path Regression Models.” • 1972, Edward L. Frome, “Nonlinear Regression and Spectral Estimation in Biomedical Data Analysis.” • 1972, Guy C. Davis, Jr., “The Use of Mathematical Models in the Analysis of Indicator-Dilution Curves.”

MASTERS THESIS DIRECTED

1975 Russell Roegner, “Some Statistical Considerations of Venereal Disease Morbidity.” COURSES TAUGHT AT EMORY • Linear Models (Graybill); Design and Analysis of Experiments (Winer); Multivariate Methods (Morrison); Introduction to Theoretical Statistics I & II (Mood, Graybill & Boes); Introduction to Probability (Parzen); Analysis of Variance and Regression (Neter, Wasserman & Kutner); Statistical Methods (Snedecor and Cochran); Biostatistics for Medical Students (Colton); Logistic Regression and Survival Analysis (Collett); Experimental Design and Analysis for the Biological Sciences (Altman); Introduction to Biostatistics (Freedman, et al); Biost atistical Consulting (Derr); Clinical Trials (Friedman, Furberg & DeMets). • 2011: Developed & taught BIOS 560R: Basic Fundamentals for Conducting a Clinical Trial, 12 students; Course Evaluation: 4.3/5 for Course: 4.4/5 for the Instructor

COMMITTEE MEMBERSHIPS/ACTIVITIES • 2013, Served as Co-Master of Ceremonies, Dinner Banquet, 50th Anniversary Celebration, Texas A&M Department of Statistics, May 17th. • 2012, Appointed as Co-Chair for Planning, 50th Anniversary Celebration, Texas A&M, Department of Statistics • 2011, Member, Selection Committee for Mu Sigma Rho Excellence in Teaching Award

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Emory University 2013 - 2014 Chair Planning Committee in the department to celebrate the 50th anniversary conference Oct 17-18, 2014. 2011 Chair, Search Committee, WCI Biostatistics Shared Resource 2011- 2015 Member and Chair, Emory Faculty Life Course Committee 2009 Charter Committee Member, Center for Health in Aging 2006 - 2009 Executive Committee, Computational & Life Sciences Initiative 2006 – 2009 Chair, Brogan Lecture Committee 2006 – 2009 Director, Biostatistics, Epidemiology and Research Design Program, ACTSI 2006 – 2009 Member, ACTSI Executive Committee 2006 – 2007 Chair, Search Committee, EOH Chair 2004 – 2009 Member, WHSC Research Advisory Committee 2004 Organized, planned and raised funds for the dinner celebration of the retirement for Dr. Donna Brogan, October 22, 2004. 2004 Organized, planned and raised funds for the 40th Anniversary celebration of the Department of Biostatistics, October 22, 2004. Luncheon speakers: President Jim Wagner, Dean Jim Curran and Dr. Fadlo Khuri. 2004 Established the Donna J. Brogan Lecture series in the Department of Biostatistics. 2003 – 2005 Chair, Search Committee, Department of Biostatistics Faculty Search 2002 – 2009 Member, Chairs Council, Rollins School of Public Health 2002 – 2004 Chair, Strategic Planning Committee for Biostatistics Consulting Center Initiative 2002 – 2008 Clinical Trials Office Advisory Committee 2000 – 2006 Center for Health in Aging Advisory Board 2000 – 2001 Search Committee, Associate Faculty Recruitment 1992 – 1993 Chair, Curriculum Committee for MPH Program 1992 – 1993 Chair, Appointment, Promotions and Tenure Committee, SPH 1991 – 1993 University Accreditation Committee, SPH Representative 1990 – 1993 Member, Steering Committee, Lovastatin Restenosis Trial 1989 – 1992 Member, Academic Computing Advisory Committee 1991 – 1993 Chairman, Woodruff Fellowship Committee, School of Public Health 1990 – 1993 Member, Executive Committee, SPH 1990 – 1992 Chairman, Admissions Committee, Division of Biostatistics 1990 – 1992 Member, Council of Division Directors, SPH 1974 – 1993 Ex-officio Member, Advisory Committee, Clinical Research Center 1974 – 1993 Chief Biostatistician, Emory General Clinical Research Center (GCRC) 1989 – 1990 NIH/GCRC Statisticians Group Development Team Member 1986 – 1990 Chairman, Medical School Workstations Committee 1983 – 1986 Member, Ad hoc Promotions Committee 1980 – 1981 Member, Task Force: Curriculum Study and Revision 1976 - 1979/ 1981 – 1986 Elected Member Executive Committee of Graduate School 1972 – 1976 Member Medical School Study Group 1971 – 1983 Doctoral Written Exam Committee, Chair

The Cleveland Clinic Foundation

Department of Biostatistics and Epidemiology 1994 – 1999 Management Advisory Committee, Chair 1994 – 1999 Space Committee, Chair 1994 – 1999 Member, Operations Group 1994 – 1995 Strategic Planning Task Force, Chair 1994 – 1999 Search Committee, Chair 1994 – 1995 Member, Committee to Review Chargeback System of Department

Research Institute 1994 – 1996 Member, Research Division Committee 1994 – 1996 Case Western Reserve University/Cleveland Clinic Foundation Working Group Member 1994 – 1999 Institutional Review Board consultant

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PUBLISHED PAPERS

1. Frome EL, Kutner MH and Beuchamp JJ. “Regression Analysis of Poisson Distributed Data.” Journal of the American Statistical Association, 68:935-940, 1973. 2. Kutner MH. “Hypothesis Testing in Linear Models (Eisenhart Model 1).” The American Statistician, 28(3):98-100, 1974. 3. Kutner MH. “Hypothesis Tests in Linear Models.” The American Statistician, 29(3):133-134, 1975. 4. Hocking RR and Kutner MH. “Some Analytical and Numerical Comparisons of Estimators for the Mixed A.O.V. Model.” Biometrics, 3(1):19-27, 1975. 5. Michael RP, Bonsall RW and Kutner MH. “Volatile Fatty Acids, ‘Copulins,’ in Human Vaginal Secretions.” Psychoneuroendocrinology, 1:153-163, 1975. 6. Gerron GG, Ansley JD, Isaacs JE, Kutner, MH and Rudman D. “Technical Pitfalls in Measurement of Venous Plasma NH3 Concentration.” Clinical Chemistry, 22:663-666, 1976. 7. Davis G and Kutner MH. “The Lagged Normal Family of Probability Density Functions Applied to Indicator-Dilution Curves.” Biometrics, 32(3):669-675, 1976. 8. Rudman D, Fleischer AS and Kutner MH. “Concentration of 3', 5' Cyclic Adenosine Monophosphate in Ventricular Cerebrospinal Fluid of Patients with Prolonged Coma After Head Trauma or Intracranial Hemorrhage.” New England Journal of Medicine, 295(12):635- 638, 1976. 9. Wolf SL, Nahai F, Brown DM, Jordan N and Kutner MH. “Objective Determinations of Sensibility in the Upper Extremity. I: Median Nerve Sensory Conductive Velocities; II: Application of Cutaneous Stimuli in Control Subjects; III: Application of Cutaneous Stimuli in Patients with Peripheral Nerve Lesions.” Physical Therapy. 57:1121-1137, 1977. 10. Sung YF, Kutner MH, Cerine FC and Frederickson EL. “Comparisons of the Effects of Acupuncture and Codeine on Postoperative Dental Pain.” Anesthesia and Analgesia, 56:473-478, 1977. 11. Rudman D, Fleischer AS, Kutner MH and Raggio JF. “Suprahypophyseal Hypogonadism and Hypothyroidism During Prolonged Coma After Head Trauma.” Journal of Clinical Endocrinology and Metabolism, 45:747-754, 1977. 12. Kaplan JA, Cannerella C, Jones EL, Kutner MH, Hatcher CR and Dunbar RW. “Autologous Blood Transfusion During Cardiac Surgery.” The Journal of Thoracic and Cardiovascular Surgery, 74:4-10, 1977. 13. Rudman D, Kutner MH, Fleming GA, Harris RC, Kennedy EE, Bethel RA and Priest JH. “Effect of 10 Day Courses of Human Growth Hormone on Height of Short Children.” Journal of Clinical Endocrinology and Metabolism, 46:28-35, 1978. 14. Ansley JD, Isaacs JW, Rikkers LF, Kutner MH, Nordinger BM and Rudman D. “Quantitative Tests of Nitrogen Metabolism in Cirrhosis: Relation to Other Manifestations of Liver Disease.” Gastroenterology, 75(4):570-579, 1978. 15. Rudman D, Davis GT, Priest JH, Patterson JH, Kutner MH, Heymsfield SB and Bethel RA. “Prevalence of Growth Hormone Deficiency in Children with Cleft Lip or Palate.” Journal of Pediatrics, 93(3):378-382, 1978. 16. Rudman D and Kutner MH. “Melanotropic Peptides Increase Permeability of Plasma/ Cerebrospinal Fluid Barrier.”American Journal of Physiology, 234(3):327-332, 1978. 17. Wolf SL, Gersh MR and Kutner MH. “Relationship of Selected Clinical Variables to Current Delivered During Transcutaneous Electrical Nerve Stimulation.” Physical Therapy, 58(12):1478-1485, 1978. 18. Rikkers LF, Rudman D, Galambos JT, Millikan WJ, Kutner MH, Smith RB, Salam AA, Sones PJ and Warren D. “A Randomized, Controlled Trial of the Distal Splenorenal Shunt.” Annals of Surgery, 188(3):271-282, 1978. 19. Kutner NG and Kutner MH. “Race and Sex as Variables Affecting Reaction to Disability.” Archives of Physical Medicine and Rehabilitation, 60:62-66, 1979. 20. Rudman D, Kutner MH, Blackston RD, Jansen RD and Patterson JH. “Normal Variant Short Stature: Subclassification Based on Responses to Exogenous Human Growth Hormone.” Journal of Clinical Endocrinology and Metabolism, 49:92-99, 1979. 21. Nixon DW, Murphy GF, Sewell GW, Kutner MH and Lynn MH. “Relationship Between Survival and Histologic Type in Small Cell Anaplastic Carcinoma of the Lung.” Cancer, 44:1045-1049, 1979. 22. Heymsfield SB, Fulenwider JT, Nordlinger BM, Barlow R, Sones PJ and Kutner MH. “Accurate Measurement of Liver, Kidney, and Spleen Volume and Mass by Computerized Axial Tomography.” Annals of Internal Medicine, 90:185-187, 1979. 23. Rudman D, Kutner MH, Goldsmith MA and Blackston RD. “Predicting the Response of Growth Hormone-Deficient Children to Long Term Treatment with Human Growth Hormone.” Journal of Clinical

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Endocrinology and Metabolism 48:472-477, 1979. 24. Faraj BA, Fulenwider JT, Rypins EB, Nordlinger BM, Ivey GL, Jansen RD, Ali FM, Camp VM, Kutner MH, Schmidt F and Rudman D. “Tyramine Kinetics and Metabolism in Cirrhosis.” Journal of Clinical Investigation, 64:413-420, 1979. 25. Heymsfield SB, Olafson RP, Kutner MH and Nixon DW. “A Radiographic Method of Quantifying Protein-Calorie Undernutrition.” American Journal of Clinical Nutrition, 32:693-702, 1979. 26. Wolf SL, Basmajian J, Russe C and Kutner MH. “Normative Data on Low Back Mobility and Activity Levels: Implications for Neuromuscular Reeducation.” American Journal of Physical Medicine, 58(5):217- 227, 1979. 27. Rudman D, Kutner MH, Goldsmith MA, Blackston RD and Bain RP. “Serum and Urine Polyamines in Normal and Short Children.” Journal of Clinical Investigation, 64:1661-1668, 1979. 28. Fine RM, Chawla RK, Kutner MH and Rudman D. “Accumulation of Urinary Cancer- Related Glycoprotein, EDC1, in Psoriasis.” The Journal of Investigative Dermatology, 73:264-265, 1979. 29. Nordlinger BM, Fulenwider JT, Ivey GL, Faraj BA, Ali FM, Kutner MH, Henderson JM and Rudman D. “Tyrosine Metabolism in Cirrhosis.” Journal of Laboratory and Clinical Medicine, 94:832-840, 1979. 30. Nixon DW, Heymsfield SB, Cohen AE, Kutner MH, Ansley JD, Lawson DH and Rudman D. “Protein- Calorie Undernutrition in Hospitalized Cancer Patients.” American Journal of Medicine, 60:683-690, 1980. 31. Rudman D, Kutner MH, Chawla RK and Goldsmith RA. “Abnormal Polyamine Metabolism in Hereditary Muscular Dystrophies.” Journal of Clinical Investigation, 65:95-102, 1980. 32. Rudman D, Goldsmith M, Kutner M and Blackston D. “Effect of Growth Hormone and Oxandrolone Singly and Together on Growth Rate in Girls with X Chromosome Abnormalities.” Journal of Pediatrics, 96(1):132-134, 1980. 33. Nordlinger BM, Nordlinger DF, Fulenwider JT, Millikan WJ, Sones PJ, Kutner MH, Steele, R, Bain R and Warren WD. “Angiography in Portal Hypertension: Clinical Significance in Surgery.” The American Journal of Surgery, 139:132-141, 1980. 34. Smith III RB, Warren WD, Salam AA, Millikan WJ, Ansley JD, Kutner MH and Bain RP. “Dacron Interposi-tion Shunts for Portal Hypertension: An Analysis of Morbidity Correlates.” Annals of Surgery, 192:9-17, 1980. 35. Rudman D, Dedonis JL, Fountain MT, Chandler JB, Gerron GG, Fleming GA and Kutner MH. “Hypocitraturia in Patients with Gastrointestinal Malabsorption.” New England Journal of Medicine, 303:657-661, 1980. 36. Felner JM, Blumenstein BA, Schlant RC, Carter AD, Alimurung BN, Johnson MJ, Sherman SW, Klicpera MW, Kutner MH and Drucker LW. "Sources of Variability in Echocardiographic Measurements." The American Journal of Cardiology, 45:995-1004,1980. 37. Brogan DR and Kutner MH. “Comparative Analyses of Pretest-Posttest Research Designs.” The American Statistician, 34:229-232, 1980. 38. Henderson JM, Stein SF, Kutner M, Wiles MB, Ansley JD & Rudman D. “Analysis of Twenty-three Plasma Proteins in Ascites: The Depletion of Fibrinogen and Plasminogen.” Annals of Surgery, 192:739- 742, 1980. 39. Rudman D, Kutner MH, Goldsmith MA, Kenny J, Jennings H and Bain RP. “Further Observations on Four Subgroups of Normal Variant Short Stature.” Journal of Clinical Endocrinology and Metabolism, 51:1378-1384, 1980. 40. Goldsmith MA, Bhatia SS, Kanto WP, Kutner MH and Rudman D. “Calcium Gluconate and Neonatal Hypercalciuria.” American Journal of Diseases of Children, 135:538-543, 1981. 41. Bhatia SJS, Moffitt SD, Goldsmith MA, Bain RP, Kutner MH and Rudman D. “A Method of Screening for Growth Hormone Deficiency Using Anthropometrics.” American Journal of Clinical Nutrition, 34:281-288, 1981. 42. Rypins EB, Fajman W, Sarper R, Henderson MJ, Kutner MH, Tarcan YA, Galambos JT and Warren WD. “Radionuclide Angiography of the Liver and Spleen: A Noninvasive Method for Assessing Portal Venous/Total Hepatic Blood Flow Ratio and Portasystemic Shunt Patency.” American Journal of Surgery, 574-579, 1981. 43. Nixon DW, Lawson D, Kutner M, Ansley J, Schwarz M, Heymsfield S, Chawla R, Cartwright TH and Rudman D. “Hyperalimentation of the Cancer Patient with Protein- Caloric Undernutrition.” Cancer Research, 41:2038-2045, 1981. 44. Nixon DW, Lawson DH, Kutner MH, Moffitt SD, Ansley J, Heymsfield SB, Lynn MJ, Wesley M, Yancey R and Rudman D. “Effect of Total Parenteral Nutrition on Survival in Advanced Colon Cancer.” Cancer Detection and Prevention, 4:421-427, 1981. 45. Nixon DW, Moffitt S, Lawson DH, Ansley J, Lynn MJ, Kutner MH, Heymsfield SB, Wesley M, Chawla R and Rudman D. “Total Parenteral Nutrition as an Adjunct to Chemotherapy of Metastatic Colorectal Cancer.” Cancer Treatment Reports, 65:121-128, 1981. 46. Rudman D, Kutner MH, Rogers CM, Lubin MF, Fleming GA and Bain RP. “Impaired Growth 164

Hormone Secretion in the Adult Population: Relation to Age and Adiposity.” Journal of Clinical Investigation, 67:1361-1369, 1981. 47. Henderson JM, Heymsfield SB, Horowitz J and Kutner MH. “Liver and Spleen Volume Measured by Computerized Axial Tomography: Assessment of Reproducibility and the Changes Found following a Selective Distal Splenorenal Shunt.” Radiology, 14:525-527, 1981. 48. Rudman D, Kutner MH, Blackston RD, Cushman RA, Bain RP and Henderson JA. “Children with Normal Variant Short Stature: Treatment with Human Growth Hormone for Six Months.” New England Journal of Medicine, 305:123-131, 1981. 49. Lawson DH, Nixon DW, Kutner MH, Heymsfield SB, Rudman D, Moffitt SD, Ansley J and Chawla RK. “Enteral vs. Parenteral Nutrition Support in Cancer Patients.” Cancer Treatment Reports, 65:101-106, 1981. 50. 50. Rypins EB, Henderson JM, Fajman W, Sarper R, Kutner M and Warren WD. “Portal Venous- Total Hepatic Flow Ratio by Radionuclide Angiography.” Journal of Surgical Research, 31:463-468, 1981. 51. 51. Rudman D, Kutner M, Ansley J, Jansen R, Chipponi J and Bain RP. “Hypotyrosinemia, Hypocystinemia, and Failure to Retain Nitrogen During Total Parenteral Nutrition of Cirrhotic Patients.” Gastroenterology, 891:1025-1035, 1981. 52. Rudman D, Kutner MH, Redd SC, Waters WC, Gerron GG and Bleier J. “Hypocitraturia in Calcium Nephrolithiasis.” Journal of Clinical Endocrinology and Metabolism, 55:1052 - 1057, 1982. 53. Gonnella C, Paris SV and Kutner MH. "Reliability in Evaluating Passive Intervertebral Motion." Physical Therapy, 62:436-444, 1982. 54. Fitzgerald T, McGowan D, Kutner MH and Wenger NK. “Demographic Determinants of Success in the Vocational Rehabilitation of Cardiac Patients.” Journal of Rehabilitation, 33 - 38, 1982. 55. Warren WD, Millikan WJ, Henderson JM, Wright L, Kutner MH, Smith RR, Fulenwider JJ, Salam AA and Galambos JR. “Ten Years Portal Hypertensive Surgery at Emory.” Annals of Surgery, 195:530-542, 1982. 56. Henderson JM, Kutner MH and Bain RP. “First-order Clearance of Plasma Galactose: The Effect of Liver Disease.” Gastroenterology, 83:1090-1096, 1982. 57. Henderson JM, Millikan WJ, Wright L, Kutner MH and Warren WD. “Quantitative Estimation of Metabolic and Hemodynamic Hepatic Function: The Effects of Shunt Surgery.” Surgical Gastroenterology, 1:77-85, 1982. 58. Millikan Jr WJ, Henderson JM, Warren WD, Riepe SP, Kutner MH, Wright-Bacon L, Epstein C and Parks RB. “Total Parenteral Nutrition with F080 in Cirrhotics with Subclinical Encephalopathy.” Annals of Surgery, 197:48-58, 1983. 59. Jennings RH, Galloway JR, Brooke MN, Kutner MH, Rudman D, Vogel RL, Wardlaw CF and Gerron GG. “Effects of Allopurinol in Duchene’s Muscular Dystrophy.” Archives of Neurology, 40:294 - 299, 1983. 60. Millikan Jr WJ, Henderson JM, Warren WD, Riepe SP, Davis RC, Hersh T, Wright-Bacon L, Long M and Kutner MH. “Maintenance of Nutritional Competence After Gastric Partitioning for Morbid Obesity.” The American Journal of Surgery, 146:619-625, 1983. 61. Faraj BA, Camp VM, Caplan DB, Ahmann PA and Kutner MH. “Abnormal Regulation of Pyridoxal 5'- Phosphate in Reye's Syndrome.” Clinical Chemistry, 29:1832-1833, 1983. 62. Henderson JM, Millikan Jr WJ, Wright-Bacon L, Kutner MH and Warren WD. “Hemodynamic Differences Between Alcoholic and Nonalcoholic Cirrhotics Following Distal Splenorenal Shunt – Effect on Survival?” Annals of Surgery, 198:325-334, 1983. 63. Rudman D, Berry CJ, Riedeburg CH, Hollins BM, Kutner MH, Lynn MJ and Chawla RK. “Effects of Opioid Peptides and Opiate Alkaloids on Insulin Secretion in the Rabbit.” Endocrinology, 112:1702-1710, 1983. 64. Rudman D, Hollins BM, Kutner MH, Moffitt SD and Lynn MJ. “Three Types of a- Melanocyte- Stimulating Hormone: Bioactivities and Half-Lives.” American Journal of Physiology, 245(Endocrinology Metabolism 8):E47- E54, 1983. 65. Faraj BA, Gottlieb GR, Camp VM, Kutner MH and Lolies P. “Development of a Sensitive Radioassay of Histamine for In Vitro Allergy Testing.” Journal of Nuclear Medicine, 25:56 -63, 1984. 66. Faraj BA, Caplan DB, Newman SL, Ahmann PA, Camp VM and Kutner MH. “Hypercatecholaminemia in Reye's Syndrome.” Pediatrics, 73:482-488, 1984. 67. Chawla RK, Lewis FW, Kutner MH, Bate DM, Roy RGB and Rudman D. “Plasma Cysteine, Cystine, and Glutathione in Cirrhosis.” Gastroenterology, 87:770 - 776, 1984. 68. Kutner NG, Fair PL and Kutner MH. “Assessing Depression and Anxiety in Chronic Dialysis Patients.” Journal of Psychosomatic Research, 29:23-31, 1985. 69. Chawla RK, Berry C, Kutner MH and Rudman D. “Plasma Concentration of Transsulfuration Pathway Product During Nasal Enteral and Intravenous Hyperalimentation of Malnourished Patients.” American Journal of Clinical Nutrition, 42:577-584, 1985. 70. Millikan WJ, Henderson JM, Galloway JR, Warren WD, Matthews DE, McGhee A and Kutner MH. “In Vivo Measurement of Leucine Metabolism with Stable Isotopes in Normal and Cirrhotic Subjects Fed 165

Conventional and Branched-Chain Amino Acid Enriched Diets.” Surgery, 98:405-413, 1985. 71. Millikan WJ, Warren WD, Henderson JM, Smith RB, Salam AA, Galambos JT, Kutner MH and Keen JH. “The Emory Prospective Randomized Trial: Selective versus Nonselective Shunt to Control Variceal Bleeding”: Annals of Surgery, 201(6):712-722, 1985. 72. Faraj BA, Newman SL, Caplan DB, Ahmann PA, Kutner M, Ali FJ and Lindahl J. “Platelet Monoamine Oxidose Activity in Reye's Syndrome.” Journal of Pediatric Gastroenterology and Nutrition, 4:532 - 536, 1985. 73. Epstein CM, Humphires LL, Alvarado C, Kutner MH and Ragab AS. “Sequential Quantitative EEG Analysis in Acute Lymphocytic Leukemia of Children.” Clinical EEG, 16(4):208-212, 1985. 74. Rudman D, Kutner MH and Chawla RK. “The Short Child with Subnormal Plasma Somatomedin C.” Pediatric Research, 19(10):975 - 980, 1985. 75. Rudman D, Chawla RK and Kutner MH. “Heterogeneity of Growth Hormone in the Nocturnal Serum of Children." Pediatric Research, 19(10):981-985, 1985. 76. El-Khishen MA, Henderson JM, Millikan Jr WJ, Kutner MH and Warren WD. “Splenectomy is Contraindicated for Thrombocytopenia Secondary to Portal Hypertension.” Surgery, Gynecology and Obstetrics, 160:237-238, 1985. 77. Faraj BA, Camp VM, Murray DR, Kutner M, Hearn J and Nixon D. “Plasma L-Dopa in the Diagnosis of Malignant Melanoma.” Clinical Chemistry, 32:159 - 161, 1986. 78. Brogan D and Kutner MH. “Graduate Service Statistics Courses.” The American Statistician, 40(3):252-254, 1986. 79. Ezzat FA, Abu-Elmagd KM, Aly IY, Aly MA, Fathy OM, El-Barbary MH, Bahgat OO, Salam AA and Kutner MH. “Distal Splenorenal Shunt for Management of Variceal Bleeding in Patients with Schistosomal Hepatic Fibrosis.” Annals of Surgery, 204:566 - 573, 1986. 80. Affarah HB, Hall WD, Heymsfield SB, Kutner M, Wells JO and Tuttle EP. “High Carbohydrate Diet: Antinatriuretic and Blood Pressure Response in Normal Men.” American Journal of Clinical Nutrition, 44:341 -348, 1986. 81. Warren WD, Henderson JM, Millikan WJ, Galambos JT, Brooks WS, Riepe SP, Salam AA and Kutner MH. “Distal Splenorenal Shunt Versus Endoscopic Sclerotherapy for Long-term Management of Variceal Bleeding.” Annals of Surgery, 203:454 - 462, 1986. 82. Henderson JM, Codner MA, Hollins B, Kutner MH and Merrill AH. “The Fasting B6 Vitamer Profile and Response to a Pyridoxine Load in Normal and Cirrhotic Subjects.” Hepatology, 6(3):464 - 471, 1986. 83. Sarper RM, Burdette EC, Crowgey SR, Malveaux EJ and Kutner M. “Technetium 99m Pertechnetate Measurement of Renal Blood Flow Distribution.” American Journal of Physiologic Imaging, 1:129 - 133, 1986. 84. Faraj BA, Caplan DB, Camp VM, Pilzer E and Kutner M. “Low Levels of Pyridoxal 5'- Phosphate in Patients with Cystic Fibrosis.” Pediatrics, 78(2):278 - 282, 1986. 85. Warren WD, Millikan WJ, Henderson JM, Abu-Elmagd KM, Galloway JR, Shires GT, Richards WO, Salam AA and Kutner MH. “Splenopancreatic Disconnection: Improved Selectivity of Distal Splenorenal Shunt.” Annals of Surgery, 204(4):346 - 355, 1986. 86. Kutner NG, Brogan DR and Kutner MH. “End-Stage Renal Disease Treatment Modality and Patient's Quality of Life.” American Journal of Nephrology, 6:396-402, 1986. 87. Rudman D and Kutner MH. “Effect of bh-Endorphin on Release of Insulin by Rabbit Pancreas in Response to Four Secretagogues: Comparison with Somatostatin and Epinephrine.” Hormone Metabolism Research, 18:365-368, 1986. 88. Noe B, Henderson JM and Kutner MH. “Alternative Methods Evaluated for Assaying Low Concentrations of Galactose in Plasma.” Clinical Chemistry, 33:420, 1987. 89. Faraj BA, Lenton JD, Kutner M, Camp VM, Stammers TW, Lee SR, Lolies PA and Chandora “Prevalence of Low Monoamine Oxidase Function in Alcoholism.” Alcoholism: Clinical and Experimental Research, Volume 11(5):464-467, 1987. 90. Kutner NG and Kutner MH. “Ethnic and Residence Differences Among Poor Families: A Research Note.” Journal of Comparative Family Studies, 18(3):463-470, 1987. 91. Lumsden AB, Henderson JM and Kutner MH. “Endotoxin Levels Measured by a Chromogenic Assay in Portal, Hepatic and Peripheral Venous Blood in Patients with Cirrhosis.” Hepatology, 8(2):232 - 236, 1988. 92. Smith TF, Muldoon MF, Bain RP, Wells EL, Tiller TL, Kutner MH, Schiffman G and PandyJP. “Clinical Results of a Prospective, Double-Blind, Placebo-Controlled Trial of Intravenous g-Globulin in Children with Chronic Chest Symptoms.” Monographs in Allergy, 23:168 - 176. (Karger, Basel 1988). 93. Flores L, Pais R, Buchanan I, Arnelle D, Camp VM, Kutner M, Faraj BA, Eckman J and Ragab “Pyridoxal 5'-Phosphate Levels in Children with Sickle Cell Disease.” The American Journal of Pediatric Hematology/Oncology, 10(3):236-240, 1988. 94. Pearson TC, Henderson JM, DePuey G, Kutner M & Warren WD. “Cardiac Index & Left Ventricular Function Changes in Cirrhosis Measured by Radionuclide Angiocardiography.” Digestive Surgery, 5:151-155, 166

1988. 95. Nixon DW, Kutner MH, Heymsfield SB, Foltz AJ, Carty C, Seitz S, Casper K, Evans WK, Jeejeebhoy KN, Daly JM, Heber DM, Poppendiek H and Hoffman FA. “Resting Energy Expenditure in Lung and Colon Cancer.” Metabolism, 37:1059 - 1064, 1988. 96. Bonkovsky HL, Hartle DK, Mellen BG, Kutner M & Galambos J. “Plasma Concentrations of Immunoreactive Atrial Natriuretic Peptide in Hospitalized Cirrhotic & Noncirrhotic Patients: Evidence for a Role of Deficient Atrial Natriuretic Peptide in Pathogenesis of Cirrhotic Ascites.” Amer. J. of Gastroenterology, 83:531-535, 1988. 97. Chawla RK, Wolf DC, Kutner MH and Bonkovsky HL. “Choline May be an Essential Nutrient in Malnourished Patients with Cirrhosis.” Gastroenterology, 97:1514 - 1520, 1989. 98. Alvarado GS, Findley HW, Chan WC, Hnath RS, Abdel-Mageed A, Pais RC, Kutner MH and Ragab AH. “Natural Killer Cells in Children with Malignant Solid Tumors: Effect of Recombinant Interferon-a and Interleukin-2 on Natural Killer Cell Function Against Tumor Cell Lines.” Cancer, 63(1):83 - 89, 1989. 99. Epstein CM, Trotter CJ, Averbook A, Freeman S, Kutner MH and Elsas LJ. “EEG Mean Frequencies are Sensitive Indices of Phenylalanine Effects on Normal Brain.” Electroencephalography and Clinical Neurophysiology, 72:133 - 139, 1989. 100. Lynn MJ, Waring GO, Nizam A, Kutner MH, et al. “Symmetry of Refractive and Visual Acuity Outcome in the Prospective Evaluation of Radial Keratotomy (PERK) Study.” Refractive Corneal Surgery, 5:75 - 81, 1989. 101. Miller LR, Soffer O, Nassar VH and Kutner MH. “Acquired Renal Systic Disease in End- Stage Renal Disease: An Autopsy Study of 155 Cases.” American Journal of Nephrology, 9:322 - 328, 1989. 102. Henderson JM, Scott SS, Merrill AH, Hollins B and Kutner MH. “Vitamin B6 Repletion in Cirrhosis with Oral Pyridoxine: Failure to Improve Amino Acid Metabolism.” Hepatology, 9:582 - 588, 1989. 103. Faraj BA, Camp VM, Davis DC, Lenton JD & Kutner M. "Evaluation of Plasma Salsolinol Sulfate in Chronic Alcoholics as Compared to Non-alcoholics." Alcoholism: Clinical and Experimental Research, 13:155-163, 1989. 104. 104. Henderson JM, Millikan WJ, Hooks M, Noe B, Kutner MH and Warren WD. “Increased Galactose Clearance After Liver Transplantation: A Measure of Increased Blood Flow Through a Denervated Liver?” Hepatology, 10:288-291, 1989. 105. Henderson JM, Warren WD, Millikan WJ, Galloway JR, Kawasaki S and Kutner MH. “Distal Splenorenal Shunt with Splenopancreatic Disconnection.” Annals of Surgery, 210:332-341, 1989. 106. Slovis CM, Negus RA, Amerson SM and Kutner MH. “Bedside Cerebrospinal Fluid Glucose.” Annals of Emergency Medicine, 18:931 - 933, 1989. 107. Maroni BJ, Haesemeyer RW, Kutner MH and Mitch WE. “Kinetics of System A Amino Acid Uptake by Muscle: Effects of Insulin and Acute Uremia.” American Journal of Physiology: Renal Fluid an Electrolyte Physiology, 258:F1304-F1310, 1990. 108. Waring GO, Lynn MJ, Fielding B, et al (PERK Study Group). "Results of the Prospective Evaluation of Radial Keratotomy (PERK) Study 4 Years After Surgery for Myopia." Journal of the American Medical Association, 263(8):1083-1091, 1990. 109. Henderson JM, Kutner MH, Millikan WJ, Galambos JJ, Riepe SP, Brooks S, Bryan C and Warren WD. “Endoscopic Variceal Sclerosis Compared to Distal Splenorenal Shunt to Prevent Recurrent Variceal Bleeding in Cirrhosis.” Annals of Internal Medicine, 112(4):262 - 269, 1990. 110. Newby FD, DiGirolamo M, Cotsonis GA and Kutner MH. “Model of Spontaneous Obesity in Aging Male Wistor Rats.” American Journal of Physiology, 259:R1117- R1125, 1990. 111. Waring GO, Lynn MJ, Stahlman ER, Kutner MH, Culbertson W, Laibson PR, Lindstrom RP, McDonald MB, Myers WD, Obstbaum SA, Rowsey JJ, Smith RE and the Prospective Evaluation of Radial Keratotomy Study Group. “Stability of Refraction During Four Years After Radial Keratotomy in the Prospective Evaluation of Radial Keratotomy Study.” American Journal of Ophthalmology, 111:133 - 144, 1991. 112. Faraj BA, Camp VM and Kutner M. “Interrelationship Between Activation of Dopaminergic Pathways and Cerebrospinal Fluid Concentration of Dopamine Tetrahydroisoquinoline Metabolite Sulsolinol in Humans: Preliminary Findings.” Alcoholism: Clinical and Experimental Research, 15(1):86 - 89, 1991. 113. Zumpe D, Bonsall RW, Kutner MH and Michael RP. “Medroxyprogesterone Acetate, Aggression, & Sexual Behavior in Male Cynomolgus Monkeys (Macaca fascicularis).” Hormones and Behavior, 25:394 - 409, 1991. 114. Henderson JM, Mackay GJ, Lumsden AB, Hussein MA, Brouillard R & Kutner MH. “The Effect of Liver Dene-rvation on Hepatic Hemodynamics During Hypovolemic Shock in Swine.” Hepatology, 15(1):130-133, 1992. 115. Henderson JM, Mackay GJ, Hooks M, Chezmar JL, Galloway JR, Dodson, TF and Kutner MH. “High Cardiac Output of Advanced Liver Disease Persists After Orthotopic Liver Transplantation.” Hepatology, 15(2):258 - 262, 1992. 116. Hooks MA, Perlino CA, Henderson JM, Millikan WJ Jr and Kutner MH. “Prevalence of Invasive 167

Cytomegalovirus Disease with Administration of Muromonab CD-3 in Patients Undergoing Orthotopic Liver Transplantation.” Annals of Pharmacotherapy, 26:617 - 620, 1992. 117. Henderson JM, Gilmore GT, Mackay GJ, Galloway JR, Dodson TF and Kutner MH. “Hemodynamics During Liver Transplantation: The Interactions Between Cardiac Output and Portal Venous and Hepatic Arterial Flows.” Hepatology, 16:715-718, 1992. 118. Smith TF, Sanchez-Legrand F, McKean LP, Kutner MH, Cragoe Jr EJ and Eaton DC. “Role of Sodium in Mediator Release From Human Basophils.” Journal of Allergy and Clinical Immunology, 89:978-986, 1992. 119. Henderson JM, Gilmore GT, Hooks MA, Galloway JR, Dodson TF, Hood MM, Kutner MH and Boyer TD. “Selective Shunt in the Management of Variceal Bleeding in the Era of Liver Transplantation.” Annals of Surgery, 216:248-255, 1992. 120. Spina GP, Henderson JM, Rikkers LF, Teres J, Burroughs AK, Conn HO, Pagliaro L, Santambrogio R, Ascione A, Bordas JM, Scott BW, Buchi KM, Burnett DA, Cormier RA, Galambos JT, Kutner MH, Millikan WJ, Opocher E, Pisani A, Riepe SP, Visa J, and Warren WD. “Distal spleno-renal shunt versus endoscopic sclerotherapy in the prevention of variceal rebleeding. A meta-analysis of 4 randomized clinical trials.” Journal of Hepatology, 16:338-345, 1992. 121. Newcom SR, Ward M, Napoli VM and Kutner M. “Treatment of Human Immunodeficiency Virus- Associated Hodgkin Disease. Is There a Clue Regarding the Cause of Hodgkin Disease?” Cancer, 71:3138- 3145, 1993. 122. Henderson JM, Mackay GJ, Kutner MH and Noe B. “Volumetric and Functional Liver Blood Flow are Both Increased in the Human Transplanted Liver.” Journal of Hepatology, 17:204-207, 1993. 123. Faraj BA, Camp VM, Davis DC, Kutner M, Cotsonis GA and Holloway T. “Elevated Concentrations of Dopamine Sulfate in Plasma of Cocaine Abusers.” Biochemical Pharmacology, 46:1453-1457, 1993. 124. Green RC, Green J, Harrison JM and Kutner MH. “Screening for Cognitive Impairment in Older Individuals. Validation Study of a Computer-Based Test.” Archives of Neurology, 51:779 - 786, 1994. 125. King SB III, Lembo NJ, Weintraub WS, Kosinski AS, Barnhart HX, Kutner MH, Alazraki NP, Guyton RA & Zhao XQ for the Emory Angioplasty Versus Surgery Trial (EAST). “A Randomized Trial Comparing Coronary Angioplasty with Coronary Bypass Surgery.” New England Journal of Medicine, 331:1044 - 1050, 1994. 126. Boyer TD, Kokenes DD, Hertzler G, Kutner MH and Henderson JM. “Effect of Distal Splenorenal Shunt on Survival of Patients with Primary Biliary Cirrhosis.” Hepatology, 20:1482 - 1486, 1994. 127. Kutner MH. “The Computer Analysis of Factorial Experiments with Nested Factors.” vited response to Dallal, G.E. (1992), The American Statistician, 46, 240. The American Statistician, 48:147, 1994. 128. Weintraub WS, Boccuzzi SJ, Klein JL, Kosinski AS, King SB 3rd, Ivanhoe R, Cedarholm JC, Stillabower ME, Talley JD, DeMaio SJ, et al. “Lack of effect of lovastatin on restenosis after coronary angioplasty. Lovastatin Restenosis Trial Study Group”. New England Journal of Medicine, 331:1331 - 1337, 1994. 129. King SB III, Lembo NJ, Weintraub WS, Kosinski AS, Barnhart HX, Kutner MH for the EAST Investigators. “Emory Angioplasty Versus Surgery Trial (EAST): Design, Recruitment, and Baseline Description of Patients.” The American Journal of Cardiology, 75:42C - 59C, 1995. 130. Ellis SG, Miller DP, Brown KJ, Omoigui N, Howell GL, Grierson J, Kutner M & Topol EJ. “In-hospital Cost of Percutaneous Coronary Revascularization: Critical Determinants & Implications.” Circulation, 92:741- 747, 1995. 131. Robinson K, Mayer E, Miller DP, Green R, Gupta A, Kottke-Merchant K, Savon S, Selhub J, Nissen S, Topol E, Kutner M and Jacobsen DW. “Hyperhomocysteinemia and Vitamin B6 Deficiency: Common and Independent Reversible Risk Factors for Coronary Artery Disease.” Circulation, 92:2825 - 2830, 1995. 132. Wolf SL, Barnhart HX, Kutner NG, McNeely E, Coogler C, Xu T and the Atlanta FICSIT Group. “Reducing Frailty and Falls in Older Persons: An Investigation of Tai Chi and Computerized Balance Training.” Journal of American Geriatric Society, 44:489-497, 1996. 133. Qu Y, Tan M and Kutner MH. “Random Effects Models in Latent Class Analysis for Evaluating Accuracy of Diagnostic Tests.” Biometrics, 52:797 - 810, 1996. 134. Robinson K, Gupta A, Dennis V, Arheart K, Chaudhary D, Green R, Vigo P, Mayer EL, Selhub J, Kutner M and Jacobsen DW. “Hyperhomocysteinemia Confers an Independent Increased Risk of Atherosclerosis in End-Stage Renal Disease and Is Closely Linked to Plasma Folate and Pyridoxine Concentrations.” Circulation, 94:2743-2748, 1996. 135. Tan M, Qu Y and Kutner MH. “Model Diagnostics for Marginal Regression Analysis of Correlated Binary Data." Communications in Statistics Series B, 26:539 - 558, 1997. 136. The EPILOG Investigators. Platelet Glycoprotein IIb/IIIa Receptor Blockade and Low-Dose Heparin During Percutaneous Coronary Revascularization. New England Journal of Medicine, 336(24):1689-1696, 1997. 137. Tan M, Xiong X and Kutner MH. “Clinical Trial Designs Based on Sequential Conditional Probability Ratio Tests and Reverse Stochastic Curtailing.” Biometrics, 54:684-697, 1998. 168

138. Kressig RW, Wolf SL, Sattin RW, O’Grady M, Greenspan A, Curns A and Kutner MH. “Associations of Demographic, Functional, and Behavioral Characteristics with Activity- Related Fear of Falling Among Older Adults Transitioning to Frailty.” Journal of American Geriatrics Society, 49(11):1456-1462, 2001. 139. Wolf, S.L., Sattin. R.W., O’Grady, M., Freret, N., Ricci, L., Greenspan. A.I., Xu, T. and Kutner, M.H. “A Study Design to Investigate the Effect of Intense Tai Chi in Reducing Falls among Older Adults Transitioning to Frailty.” Controlled Clinical Trials, 22(6):689-704, 2001. 140. Xiong, X., Tan, M. and Kutner, M.H. “Computational Methods for Evaluating Sequential Tests and Post- test Estimation via the Sufficienncy Principle.” Statistica Sinica, 12(4):1027-1041, 2002. 141. Gassman, JL, Greene, T, Wright, Jr, JT, Agodoa, L, Bakris, G, Beck, GJ, Douglas, J, Jamerson, K, Lewis, J, Kutner, M, Randall, OS, Wang, S-R & AASK Group. “Design and Statistical Aspects of the African American Study of Kidney Disease and Hypertension (AASK).” J Am Soc Nephrol, 14: S154 - S165, 2003. 142. Kapasi, Z.F., Ouslander, J.G., Schnelle, J.F., Kutner, M., and Fahey, J.L. “Effects of an Exercise Intervention on Immunologic Parameters in Frail Elderly Nursing Home Residents.” Journal of Gerontology: Medical Sciences, 58A (7): 636 - 643, 2003. 143. Wolf, S.L., Sattin, R.W., Kutner, M., O’Grady, M., Greenspan, A.I., and Gregor, R.J. “Intense Tai Chi Exercise Training and Fall Occurrences in Older, Transitionally Frail Adults: A Randomized Control Trail.” Journal of the American Geriatric Association, 51:1693 - 1701, 2003. 144. Johnson, T.M., Jones, K., Williford, W., Kutner, M., Issa, M., and Lepor, H. “Changes in Nocturia from Medical Treatment of Benign Prostatic Hyperplasia: Secondary Analysis of the Department of Veterans Affairs Cooperative Study Trial.” Journal of Urology, 170: 145 - 148, 2003. 145. Van De Water, M.S., Kutner, M., Parmelee, P.A., Johnson, T. “Which long-term care residents should be asked to complete a customer satisfaction survey?” Journal Am Med Dir Assoc. 4:257 - 263, 2003. 146. Kressig, R.W., Gregor, R.J., Oliver, A., Waddell, D., Smith, W., O’Grady, M., Curns, A.T., Kutner, M., Wolf, S.L. “Temporal and Spatial Features of Gait in Older Adults Transitioning to Frailty.” Journal of Gait and Posture, 20:30 - 35, 2004. 147. Endeshaw, Y., Johnson, T., Kutner, M., Ouslander, J., and Bliwise, D. “Sleep-Disordered Breathing and Nocturia in Older Adults.” Journal of the American Geriatrics Society, 52:957-960, 2004. 148. Pisoni, R.L., Gillespie, B.W, Dickinson, D.M., Chen, K., Kutner, M.H., and Wolfe, R.A. “The Dialysis Outcomes and Practice Patterns Study (DOPPS): Design, Data Elements, and Methodology. American Journal of Kidney Disease, 44 (5 Suppl 2):7 - 15, 2004. 149. Greco, K.E., Deaton, C., Kutner, M., Schnelle J.F., and Ouslander, J.G. “Psychoactive Medications and Actigraphically Scored Sleep Quality in Frail Nursing Home Patients”. J American Medical Directors Association, 5(4):223 - 227, 2004. 150. Sattin, R., Easley, K., Wolf, S., Chen, Y. and Kutner, M. Reduction in Fear of Falling Through Intense Tai Chi Exercise Training in Older, Transitionally Frail Adults, Journal of the American Geriatrics Society, 53(7):1168 -1178, 2005. 151. Ouslander, J.G., Griffiths, P., McConnell, E., Riolo, L., Kutner, M. and Schnelle, J. “Functional Incidental Training: A Randomized, Controlled, Crossover Trial in Veterans Affairs in Nursing Homes.” Journal of the American Geriatrics Society, 53(7):1091 - 1100, 2005. 152. Kitayama, N., Vaccarino, V., Kutner, M., Weiss, P. and Bremner, D. “Magnetic Resonance Imaging (MRI) Measurement of Hippocampal Volume in Posttraumatic Stress Disorder: A Metanalysis.” Journal of Affective Disorders, 88(1):79 - 86, 2005. 153. Henderson, J.M., Boyer, T.D., Kutner, M.H., Galloway, J.R., Rikkers, L.F., Jeffers, L.J., Abu-Elmagd, K., Connor, J.: DIVERT Study Group. “Distal Slenorenal Shunt versus Transjugular Intrahepatic Portal Systematic Shunt for Variceal Bleeding: A Randomized Trial.” Gastroenterology, 130(6):1643 - 1651, 2006. 154. Wolf, S.L., O’Grady, M., Easley, K.A., Guo, Y., Kressig, R.W., and Kutner, M.H. “The influence of intense tai chi training on physical performance and hemodynamic outcomes in transitionally frail adults.” Journals of Gerontology: Medical Sciences Series A – Biological Sciences & Medical Sciences, 61(2): 184 - 189, 2006. 155. Puskas, J.D., Kilgo, P.D., Kutner, M., Pusca, S.V., Lattouf, O., and Guyton, R.A. “Off-pump techniques disproportionately benefit women and narrow the gender disparity in outcomes after coronary artery bypass surgery.” Circulation, 116 (11): 1192 - 1199, 2007. 156. Endeshaw, Y.W., Unruh, M., Kutner, M., Ouslander, J., Newman, A., and Bliwise, D. “Sleep disordered breathing and frailty-Gender differences.”Journal of the American Geriatrics Society, 56(4): S187 - S187, 2008. 157. Boyer, T.D., Henderson, J.M., Heerey, A.M., Arrigain, S., Konig, V., Connor, J., Abu- Elmagd, K., Galloway, J., Rikkers, L.F., Jeffers, L., DIVERT Study Group. “Cost of preventing variceal rebleeding with transjugular intrahepatic portal systemic shunt and distal splenorenal shunt.” Journal of Hepatology, 48 (3): 407- 414, 2008. 158. Lucey, M.R., Connor, J.T., Boyer, T.D., Henderson, J.M., Rikkers, L.F., DIVERT Study Group. “Alcohol consumption by cirrhotic subjects: patterns of use and effects on liver function.” American Journal Gastroenterol, 103 (7): 1698 - 1706, 2008. 159. Endeshaw, Y.W., White, W.B., Kutner, M., Ouslander, J.G., and Bliwise, D.L. “Sleep- disordered breathing 169

and 24-hour blood pressure pattern among older adults.” Journal of Gerontology Series A: Biological Sciences and Medical Sciences, 64:280 - 285, 2009. 160. Weinberg, J.M., Appel, L.J., Bakris, G., Gassman, J.J., Greene, T., Kendrick, C.A., Wang, X., Lash, J., Lewis, J.A., Pogue, V., Thornley-Brown, D., Phillips, R.A., African American Study of Hypertension and Kidney Disease Collaborative Research Group. “Risk of hyperkalemia in nondiabetic patients with chronic kidney disease receiving antihypertensive therapy.” Arch Internal Medicine, 169: 1587 - 1594, 2009. 161. Contreras, G., Hu, B., Astor, B.C., Greene, T., Erlinger, T., Kusek, J.W., Lipkowitz, M., Lewis, J.A., Randall, O.S., Herbert, L., Wright, J.T., Jr., Kendrick, C.A., Gassman, J., Bakris, G., Kopple, J.D., Appel, L.J., “African-American Study of Kidney Disease, and Hypertension Study Group.” Journal of American Society of Nephrology, 21: 2131 - 2142, 2010. 162. Ji, S., Long, Q., Newport, D.J., Na, H., Knight, B., Zach, E.B., Morris, N.J., Kutner, M., Stowe, Z.N., “Validity of depression rating scales during pregnancy and the postpartum period: impact of trimester and parity.” Journal of Psychiatric Research, 45: 213 - 219, 2011. 163. Kauh J, Chanel-Vos C, Escuin D, Fanucchi MP, Harvey RD, Saba N, Shin DM, Gal A, Pan L, Kutner M, Ramalingam SS, Bender L, Marcus A, Giannakakou P, Khuri FR. “Farnesyl transferase expression determines clinical response to the docetaxel-lonafarnib combination in patients with advanced malignancies.” Cancer, 2011 Mar 1. doi: 10.1002/cncr.26004. [Epub ahead of print]. 164. Josephson CD, Castillejo MI, Caliendo AM, Waller EK, Zimring J, Easley KA, Kutner M, Hillyer CD, Roback JD. “Prevention of transfusion-transmitted cytomegalovirus in low-birth weight infants ≤15 (00 g) using cytomegalovirus -seronegative and leukoreduced transfusions.” Transfus Med Rev. 25:125-132, 2011. 165. Terry, PD, Goyal, A, Phillips, LS, Superak, HM, Kutner, MH “Design and rationale of a randomized controlled trial of melatonin supplementation in men and women with the metabolic syndrome” Open Access Journal of Clinical Trials 2013:5 51-59. 166. Goyal, A, Terry, PD, Superak, HM, Nell-Dybdahl, CL, Chowdhury, R,. Phillips, LS, Kutner, MH “Supplementation to treat the metabolic syndrome: a randomized controlled trial” Journal of Diabetology & Metabolic Syndrome in press

CITATIONS AND ACKNOWLEDGMENTS • Tabulation of Hermite Polynominals (Table 2) in Pearson, ES and Hartley HO, Biometrika Tables for Statisticians, Volume II, 1972. • Morgan SL and Deming SN. Simplex Optimization of Analytical Chemical Methods.” Analytical Chemistry, 46:1178-1180, 1974. • Michael RP, Bonsall RW and Warner P. “Human Vaginal Secretions: Volatile Fatty Acid Content.” Science, 186:1217-1219, 1974. • 1974 AMSTAT paper cited in Biomedical Computer Programs (BMDP Manual) and SAS User's Guide. • Zumpe D and Michael RP. “Effects of Ejaculations by Males on the Sexual Invitations of Female Rhesus Monkeys (Macaca mulatta).” Behavior, LX: 260-277, 1977. • Bonsall RW, Zumpe D and Michael RP. “Menstrual Cycle Influences on Operant Behavior of Female Rhesus Monkeys.” Journal of Comparative and Physiological Psychology, 92:846-855, 1978. • Michael RP and Zumpe D. “Potency in Male Rhesus Monkeys: Effects of Continuously Receptive Females.” Science, 200:451-453, 1978. • Wolf SL, Ariel GB, Saar D, Penny MA and Railey P. “The Effect of Muscle Stimulation during Resistive Training on Performance Parameters.” The American Journal of Sports Medicine, 14:18-23, 1986. • Kutner NG, Brogan D, Fielding B and Hall WD. “Older Renal Dialysis Patients and Quality of Life.” Dialysis and Transplantation, 20(4):171-175, 1991.

LETTERS TO EDITOR 1. Kutner MH. “Improving Refereeing Policies.” The American Statistician, 29(2):110, 1975. 2. Brown AC, Olkowski ZL, McLaren JR and Kutner MH. “Alopecia Areata and Vitiligo Associated with Down's Syndrome.” Archives of Dermatology, 113:1296, 1977. 3. Rudman D, Kutner MH, Blackston RD and Patterson JH. “Normal Variant Short Stature.” New England Journal of Medicine, 305(19):1153-1154, November, 1981. 4. Ingram C, Frederickson E and Kutner MH. “Inappropriateness of Statistical Methods Used in Evaluating Postanesthetic Hepatic Injury.” Anesthesia and Analgesia, 61(8):728, August, 1982. 5. Henderson JM and Kutner MH. “Galactose Clearance as a Measure of Hepatic Blood Flow.” Gastroenterology, 85:986-988, September, 1983. 6. Henderson JM and Kutner MH. “An Analysis of Survival and Treatment Failure Following Abdominoperineal and Sphincter-saving Resection in Dukes' B and C Rectal Carcinoma: A Report of the NSABP Clinical Trials.” Annals of Surgery, 206(4):224-226, August, 1987.

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7. Henderson JM, Kutner MH and Warren WD. “Do Surgeons Led by Surgeons Operate Better Than Internist-led Surgeons?” Gastroenterology, 93(3):666-667, September, 1987. 8. Henderson JM, Kutner MH and Warren WD. “Sclerotherapy vs. Distal Splenorenal Shunt in the Elective Treatment of Variceal Hemorrhage: A Randomized Controlled Trial.” Hepatology, 8(2):441-442, 1987. 9. Henderson JM, Kutner MH and Noe B. “Galactose Clearance and Liver Blood Flow.” Gastroenterology, 95(4):1157-1158, 1988. 10. Kutner MH, Rao JS. “Prediction of Hospital Mortality Rates.” Annals of Internal Medicine, 127(9):846- 847, 1997.

PRESENTATIONS, SEMINARS AND SHORT COURSES August 2015 Invited panelist at the ASA Joint Statistical Meeting in Seattle, to discuss how to be an effective collaborating statistician Oct 30, 2014 Invited seminar speaker at the University of North Carolina, Wilmington, NC on the analysis of fixed effects models with missing data in some cells April 30, 2014 Invited panelist to discuss teaching of introductory statistics courses to non-statistics majors at Georgia ASA Chapter meeting June 2, 2014 Invited speaker at the 50th Anniversary at the SRCOS SRC in Galveston, TX, June 1-4, 2014 meeting to discuss the role that SRCOS has played in developing academic programs in statistics/biostatistics in the South. Aug 2, 2014 Invited speaker at the ASA Joint Statistical Meetings in Boston, MA, August 2 - 7, 2014 to discuss the growth of statistics academic programs in the South and its association with ASA. June 6, 2011 Keynote Dinner Speaker, Southern Regional Council on Statistics Summer Research Conference: “Recollections and Reflections.” June 5, 2011 Organizer and Panel Discussant, Southern Regional Council on Statistics Summer Research Conference, “Teaching Introductory Statistics/Biostatistics Courses for Non-Majors.” July 2010-13 Two 2-hour lectures each year to Summer Institute for Training in Biostatistics (SIBS) program attendees on research projects/designs August 5, 2009 Invited Panel Discussant, JSM 2009, Mu Sigma Rho Session. August 3, 2009 Invited panel session JSM, Title: “Directing a Biostatistics Core in Biomedical Research.” April 2-3, 2009 Keynote Speaker, “Innovations in Design, Analysis, and Dissemination: Frontiers in Biostatistical Methods.” Cerner-Kansas University Medical College – ASA Biostatistics Symposium, Kansas City, KS. Jan 16-17, 2009 Short Course: Design and Analysis of Clinical Studies, Shriner’s Hospitals, Clearwater Beach, FL June 20, 2007 “How to Design a Research Study”, Summer Interns, Division of Geriatrics, Atlanta, GA April 24, 2007 “Analysis of Fixed Effects ANOVA Models with Missing Cells”, Medical College of GA, Augusta, GA April 20, 2007 “Analysis of Fixed Effects ANOVA Models with Missing Cells”, The Hocking Lecture, Texas A&M June 20, 2006 “How to Design a Research Study”, Summer Interns, Division of Geriatrics, Atlanta, GA April 21, 2006 “Analysis of Fixed Effects ANOVA Models with Missing Cells”, Department of Mathematical Sciences, Bowling Green University, Bowling Green, OH Nov 30, 2005 “Past, Present and Future of Biostatistics”, Georgia Chapter, ASA, Atlanta, GA Oct 20, 2005 “Statistical Collaboration and Consulting Within the Health Sciences”, Division of Pulmonary Medicine, Emory University, Atlanta, GA Oct 6, 2005 “Intense Tai Chi Exercise Training and Fall Occurrences in Older, Transitionally Frail Adults: Trial Designs and Outcomes” University of Texas Southwestern Medical School, Dallas, TX Aug 29, 2004 Invited Speaker: “Outliers and Their Effects on the Scientific Literature”, Winship Cancer Institute, Atlanta, GA Aug 11, 2004 Invited Speaker: “Statistical Consulting within the Medical Sciences”, Joint Statistical Meeting, Toronto, Canada Jun 16, 2004, July 1, 2003 “Reading the Medical Literature”, AFAR Summer Research Students, Center for Health in Aging”, Wesley Woods Health Center, Atlanta, GA Nov 19, 2002 “Biostatistical Considerations in Rehabilitation Research”, Rehabilitation Residents and Fellows, Rehabilitation Medicine Department, Emory University Oct 30, 2002 “Biostatistical Collaboration: the Good, the Bad and the Ugly”, Center for Research on Symptoms, Symptom Interactions, and Health Outcomes, Emory University Nell Hodgson Woodruff School of Nursing Oct 16, 2002 “A Unified Regression Approach for Fixed Effects ANOVA Models with Missing Cells”, Department of Biostatistics, Emory University Sept 17, 2002 “Biostatistical Support”, Clinical Trials Office Symposium April 2, 2002 Invited Speaker: “Outliers”, Southeastern Family Medicine and Primary Care Research Conference, Savannah, Georgia (Mercer School of Medicine). Dec 12, 2001 Invited Seminar: “Outliers and Their Effects.” VA Rehab R & D, Atlanta, Georgia. May 11, 2001 Invited Workshop Speaker: “Interpretation of Diagnostic Tests.” Southeastern Family Medicine and Primary Care Research Conference, Savannah, Georgia. March 28, 2001 Invited Seminar: “Observational versus Experimental Studies: That is the Question.” VA Rehab R & D, Atlanta, Georgia. Aug12-13, 2000 Invited 2 Day Short Course: “Logistic Regression Analysis.” Joint Statistical Meeting, Indianapolis, Indiana (with C. Nachtsheim) March 8, 2000 Invited Seminar: “Design and Statistical Aspects of the African American Study of Kidney Disease and 171

Hypertension.” VA Rehab R & D, Atlanta, Georgia. Nov 3, 1999 ½ Day Workshop: “Logistic Regression Modeling.” Cleveland Chapter, American Statistical Association. July 13, 1999 Invited Seminar: “Design and Statistical Analysis of the African American Study of Kidney Disease and Hypertension.” Department of Biostatistics, University of Michigan. May 19, 1999 Invited Seminar: “Hypothesis Testing for Fixed Effects ANOVA Models with Missing Cells.” Department of Biostatistics, University of Pennsylvania. March 3, 1999 Invited Speaker: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing Cells.” Cleveland Chapter, American Statistical Association. Dec 14, 1998 Contributed Paper: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing Cells.” International Biometrics Conference, Cape Town, South Africa. Oct 29, 1998 Invited Speaker: “Linear Regression and Correlation.” Concepts and Methods in Biostatistics, CME Course, The Cleveland Clinic Oct 21, 1998 Hosted Quantitative Literacy Program. Presented “Overview of the Department of Biostatistics and Epidemiology.” Aug 27, 1998 Contributed Paper: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing Cells.” International Society for Clinical Biostatistics Conference, Dundee, Scotland. July 24, 1998 Invited Seminar: “The Design and Statistical Aspects of the African American Study of Kidney Disease and Hypertension.” University of Alabama Birmingham, Birmingham, Alabama. April 29, 1998 Invited Speaker: “Academic Institution Issues in Industry-Sponsored Clinical Trials.” Drug Information Association, New Orleans, Louisiana. April 20, 1998 Invited Seminar: “A Unified Approach to Analyzing Fixed Effects ANOVA Models.” University of North Carolina, Chapel Hill, North Carolina. March 27, 1998 Invited Seminar: “The Design and Statistical Aspects of the African American Study of Kidney Disease and Hypertension.” Medical University of South Carolina, Charleston, South Carolina. Mar18-20, 1998 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta, Georgia (with Ray Greenberg). Dec 3, 1997 Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at the Cleveland Clinic”, The Cleveland Clinic Foundation. Nov 1, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. San Antonio Chapter, ASA, San Antonio, Texas. Oct 31, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course Central Arkansas Chapter, ASA, Little Rock, Arkansas. Oct 29, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. South Florida Chapter, ASA, West Palm Beach, Florida. July 28, 1997 Poster Session: “Design and Statistical Aspects of the African American Study of Kidney Diseases and Hypertension.” Kutner M, Agadoa L, Gassman J, Glassock R, Greene T, Olutade B, Randall O. Twelfth International Conference on Hypertension in Blacks, London, England. June 21, 1997 Invited Speaker: “Linear Regression and Correlation: Concepts and Methods in Biostatistics Course. Cleveland Clinic Foundation. June 10, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Oregon Chapter, ASA, Portland, Oregon. June 9, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Sacramento Chapter, ASA, Sacramento, California. June 6, 1997 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Albuquerque Chapter, ASA, Albuquerque, New Mexico. June 5, 1997 Invited Speaker: “A Unified Approach to Analyzing Data f rom Fixed Effects ANOVA Models.” Department of Statistics, Los Alamos National Laboratory. Mar19-21, 1997 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta, Georgia (with Ray Greenberg). Nov 7, 1996 Invited Speaker: “A Unified Approach to Analyzing Data From Fixed Effects ANOVA Models.” Department of Statistics, University of Florida, Gainesville, Florida. August 7, 1996 Invited Talk: “Academe/Industry Collaboration Project.” Industry and Academic Department Heads, Joint Statistical Meeting, Chicago, Illinois. June 5, 1996 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Central Indiana Chapter, ASA and University of Indiana School of Medicine, Indianapolis, Indiana. June 4, 1996 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Central Illinois Chapter, ASA and University of Southern Illinois School of Medicine, Springfield, Illinois. June 3, 1996 Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Chicago Chapter, ASA, Chicago Illinois. May 24, 1996 Invited Speaker: “Logistic Regression Modeling.” Auburn University and Alabama Chapter, ASA, Auburn, Alabama. Mar 27-29, 1996 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta, Georgia (with Ray Greenberg). Feb 6, 1996 Invited Speaker: “Biostatistics at The Cleveland Clinic Foundation.” Department of Statistics, Brigham Young University, Provo, Utah. Nov 29, 1995 Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at The Cleveland Clinic.” The

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Cleveland Clinic Foundation, Cleveland, Ohio. Nov 16, 1995 Invited Speaker: “Biostatistics at the Cleveland Clinic Foundation.” Twelfth Annual Ohio Statistics Conference, Columbus, Ohio. Oct 17, 1995 Invited Speaker: “Linear Regression and Correlation: Concepts and Methods in Biostatistics Course.” Cleveland Clinic Foundation. Sept 13, 1995 Contributed Paper Session: “Special Care Units for ADRD Residents: Multidimensional Analysis of Outcomes”: (Presented by Nancy G. Kutner.) XI International Conference, Alzheimer's Disease and Related Disorders, Buenos Aires, Argentina. Aug 14, 1995 Invited Speaker: “Biostatistics Training for Established Physicians.” Invited Session sponsored by the Section on Teaching of Statistics in the Health Sciences, Joint Statistical Meeting, Orlando, Florida. Jun 26-28, 1995 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta Georgia. (with Ray Greenberg.) June 5-7, 1995 Keynote Speaker: “The Use of Diagnostic Tests.” First International Applied Statistics in Medicine Conference held in conjunction with the Third International Applied Statistics in Industry Conference, Dallas, Texas. Workshop Presentation: "Principles of Biostatistics in Clinical Research.” May 5, 1995 Invited Speaker: “A Unified Approach to Analyzing Data f rom Fixed Effects ANOVA Models.” M.D. Anderson Cancer, Houston, Texas. May 4, 1995 Invited Speaker: “Biostatistics at the Cleveland Clinic Foundation. Statistics Department, Texas A&M University, College Station, Texas. Mar 1-3, 1995 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta, Georgia. (with Ray Greenberg.) Dec 12, 1994 Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at The Cleveland Clinic.” The Cleveland Clinic Foundation, Cleveland, Ohio. Oct 16, 1994 Short Course: “Issues in Regression Analysis Using Statistical Packages.” Societyfor Medical Decision Making, Cleveland, Ohio. Sept 16, 1994 Invited Speaker: “Principles of Biostatistics in Clinical Research.” Gastroenterology Staff and Fellows: Research Conference, The Cleveland Clinic Foundation, Cleveland, Ohio. August 16, 1994 Invited Session Discussant: “Short Courses: Challenges, Issues and Educational Value.” 1994 Joint Statistical Meetings, Toronto, Ontario, Canada. June 12, 1994 Invited Speaker: “Interpretation of Diagnostic Tests.” Intensive Review of Internal Medicine Course, The Cleveland Clinic Foundation, Cleveland, Ohio. June 6-7, 1994 Invited Speaker: “Comparing More Than Two Means: Analysis of Variance” and “Linear Regression and Correlation.” Biostatistics in Medicine Course, The Cleveland Clinic Foundation, Cleveland, Ohio. June 1, 1994 Invited Speaker: “Some Interesting Regression Modeling Examples.” Cleveland Chapter, American Statistical Association, Cleveland, Ohio. April 26, 1994 Invited Speaker: “Estimating and Testing in ANOVA Models with Some Empty Cells (Eisenhart Model I).” Ohio State University, Department of Statistics, Columbus, Ohio Ap ril 21, 1994 Invited Speaker: “Estimating and Testing in ANOVA Models with Some Empty Cells (Eisenhart Model I).” Cincinnati Chapter, American Statistical Association and Department of Mathematics and Statistics, Miami University, Oxford, Ohio. Mar 14-16, 1994 Short Course: “Regression Modeling for Epidemiologic Research.” National Institute for Occupational Safety and Health, Cincinnati, Ohio. (with Ray Greenberg.) March 9-11, 1994 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention, Atlanta, Georgia. (with Ray Greenberg.) January 19, 1994 Presented Departmental Overview to Northeast Ohio Quantitative Literacy Program, The Cleveland Clinic Foundation, Cleveland, Ohio. Sept 12-14, 1993 Research Institute Retreat: “Outliers and Their Effects,” Salt Fork State Park, Ohio. April 10, 1992 Seminar: “Interpretation of Survival in Clinical Trials.” Pediatric Allergy Journal Club. Nov 1991 Seminar: “Common Methods of Analyzing Response Data in Clinical Trials.” Pediatric Allergy Journal Club. Aug 18-23, 1991 Short Courses: “Advanced Multivariate Methods.” International Course in Epidemiology and Research Methodology, Vouliagmeni Beach, Greece. (with Ray Greenberg.) April 1991 Journal Club Speaker. “Diagnostic Tests: An Introduction to Probability.” Department of Pediatrics. Oct 5-6, 1990 Invited Speaker: “Statistical Applications in the Medical and Health Services Field.” John Neter Recognition Weekend. Athens, Georgia. July 16-27, 1990 “EPI 732: Statistical Methods.” The University of Michigan Graduate Summer Session in Epidemiology. (With Ray Greenberg.) April 5, 1990 Invited Speaker: “ANOVA Models with Empty Cells.” Virginia Polytechnic Institute and State University. Mar 1990-June 1991 Series of monthly biostatistics seminars to fellows and faculty in Division of Pediatric Hematology/Oncology. Jan 8-16, 1990 Indo-U.S. Workshop: “Biostatistics and Epidemiological Methods in Ophthalmology.” New Delhi, India. Oct 11, 1989 Seminar: “Outliers.” Clinical Research Center. 1989 Panel Discussant: “Statistics Programs in Georgia.” Atlanta Chapter, American Statistical Association. July 18-23, 1988 “Cross-classified Fixed Effects ANOVA Models with Missing Cells.” XIVth International Biometric Conference. Namur, Belgium. December 1987 “ANOVA Models in the Case of Missing Cells.” Atlanta Chapter, American Statistical Association. Jan 3-5, 1987 “A Unified Approach to the Analysis of Balanced and Unbalanced Fixed Effects Data.” American Statistical

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Association Winter Conference. 1986 – 1992 Series of Ten Week Short Courses (2 hours/week): “Regression Modeling in Epidemiologic Research.” Centers for Disease Control. Sept.-Nov. 1985 Ten Week Short Course (2 hours/week): “Mathematical Modeling in Epidemiologic Research: Logistic Regression.” Centers for Disease Control. Aug 5-8, 1985 “Graduate Service Statistics Courses: What, to Whom and by Whom?” Annual Meeting of the American Statistical Association. Las Vegas, Nevada. April 25, 1985 Seminar: “Prediction and Normal Limits in Clinical Research.” The Atlanta Cancer Surveillance Center. 1984 Ten Week Short Course (2 hours/week): “Multivariable Statistical Techniques: Principles and Applications.” Centers for Disease Control. June 13, 1984 Seminar: “Biometrical Considerations in Designing a Clinical Study.” Clinical Research Center. May 1984 Tutorial on Unbalanced Analysis of Variance. Special Colloquium. University of Georgia. May 24, 1982 “Nonlinear Regression: A Tutorial.” Atlanta Chapter, American Statistical Association. Nov 1-6, 1981 “Experimental Designs in Rehabilitation Research.” Course Organizer and Presenter. American Congress of iRehabilitat on Medicine Meeting. San Diego, California. Aug 10-13, 1981 “Using a University-Based Clinical Research Facility to Train Statistics Graduate Students in Statistical Consultation.” Invited paper, Annual ASA Meeting. Detroit, Michigan.

1980 “Single Subject Designs and Group Comparison Designs.” Designs for Rehabilitation Research Conference. Atlanta, Georgia. Nov 14, 1979 Seminar: “The Significance of Significance Testing.” Clinical Research Center, Emory University, Atlanta, Georgia. 1978 Seminar: “Analysis of Time Series Data.” Centers for Disease Control, Atlanta, Georgia. 1978 Seminar: “Analysis of Variance and Covariance.” Centers for Disease Control, Atlanta, Georgia. 1978 “Periodic Regression Analysis: A Demographic Model Building Technique.” Annual Population Association of American Meeting. Atlanta, Georgia. March 1978 “Seasonal Variation in Fertility Using Periodic Regression Analysis.” Annual Southern Sociological Society Meeting. New Orleans, Louisiana. (With C.W. Warren, R.P. Briggs and C.W. Tyler.) November 1977 “The Analysis of Multiple Variable Dependencies in Chronic Disease Etiology.” Invited paper, American Public Health Association Meeting. Washington, D.C. (With B.A. Blumenstein.) Ap r 14-15, 1977 “Analysis of Variance Incorporating Trend Analysis with Unbalanced Data.” Tenth Annual Symposium on the Interface of Computer Science and Statistics. National Bureau of Standards. Mar 8-10, 1976 “Path Analysis: Some Biometrical Examples.” Regional Biometrics Meeting. College Station, Texas. (With B.A. Blumenstein.) March 20, 1975 Seminar: “Variance Component Estimation.” Concordia University. Montreal, Canada. 1974 Seminar: “Nonorthogonal Data Analysis.” Kansas State University. Aug 26-29, 1974 “Hypothesis Testing in Unbalanced Crossed Classified Fixed Effects Models.” Annual ASA Meeting. St. Louis, Missouri. Ap ril 6, 1974 Dinner Speaker. Atlanta Chapter ASA Meeting. October 1973 “A Critique: Hair Sulfur Analysis for Evaluation of Normal and Abnormal Hair.” First Human Hair Symposium, Atlanta, Georgia. Aug 14-17, 1972 “Comparative Studies of Variance Components for the Balanced Incomplete Block Design Under an Eisenhart Model II.” Annual ASA Meeting. Montreal, Canada. Jun 11-16, 1972 “Maximum Likelihood Analysis of Mixed Linear Models: The Balanced Incomplete Block Model.” SREB Summer Research Conference in Statistics. Mountain Lake, Virginia. February 1971 “Estimation of Variance Components Via Maximum Likelihood.” Emory University. Atlanta, Georgia. Dec 27-30, 1970 “Quasi-Maximum Likelihood Estimates of Variance Components.” The Allied Social Science Association Meeting. Detroit, Michigan. May 1962 “A Statistical Analysis of a Crop Rotation Experiment.” Virginia Academy of Sciences Meeting.

MEMBERSHIP IN PROFESSIONAL ORGANIZATIONS

American Statistical Association (Member since 1962) 2013-2015 Appointed to Dixon Awards Committee, American Statistical Association 2015 Chair, W.J. Dixon Awards Committee, American Statistical Association 2003 – 2008 Member, Finance Committee 2001 Chair, Local Assistance Committee, Joint Statistical Meeting 2000 - 2001 Nomination Committee Member (President and Vice President) 1998 - 2000 Elected Council of Sections Representative, Section on Statistical Consulting 1994 Joint Program Committee: Section on Teaching of Statistics in the Health Sciences 1994 Organized, Chaired and Discussed Invited Paper Session Joint Statistical Meetings 1993 - 1995 Board Member, District Representative 1990 - 1991 Member, Local Arrangements Committee, Joint Statistical Meetings 174

1988-1990 Member, Publications Committee, Vice-Chair 1988 Member, Ad Hoc Committee on Transition Costs for Editors of ASA Publications 1988-1989 Committee on the ASA Sesquicentennial; Chair of Finance Subcommittee 1987-1989 Winter Conference Evaluator Institutional 1987-1994 Membership Representative Winter 1987 Conference Coordinator 1985-1986 Chair, Nominating Committee for District Governor Chair of Council of Governors and ASA Board Representative 1984-1986: Member, Ad Hoc Committee on ASA Policy on Grants and Contracts 1985-1986 Executive Committee, Council of Chapters, District 5 Governor 1984-1986 President, Atlanta Chapter ASA 1981-1983 Board Member, District 5 Representative 1981-1983 Member, Budget Committee of Board 1983 Chair, Budget Committee of Board 1980 Organized and Chaired, Invited Session at National ASA Meeting 1978-1980 Associate Editor, The American Statistician 1979-1982 Vice-Chair, Ad Hoc Committee of Sections and Subsections 1979-1982 Vice Chair, Committee to Revise the ASA Constitution 1977-1978 Member, Ad Hoc Committee on Chapters Outside U.S. and Canada 1975-1976 Member, Ad Hoc Committee on Membership, Dues and Publications 1975 Vice-Chair, Executive Committee of Local Arrangements National ASA Meeting 1974 Chair, Nominating Committee for District 5 Representative 1975; 1977-80 Chair, Nominating Committee, Atlanta Chapter ASA 1977-1979 Chair, Committee on Chapter, District and Regional Activities 1974-1976 Member, Committee on Chapter, District and Regional Activities 1973-1974 President, Atlanta Chapter ASA 1972-1973 Secretary/Vice President, Atlanta Chapter ASA

American Statistical Association Elected Office American Statistical Association - Board of Directors, 1981-1983, 1993-1995 Management Review Committee Member Board Planning Teams: Outreach, Chair; Activities for non-Ph.D. members Council of Chapters Governing Board: Chair, Fellows Committee

Biometrics Society (Member since 1971) 2010, Chaired IMS Special Lecture Session 1994, Served on Local Arrangements Committee for the Biometrics Spring Meeting, Eastern North American Region, Cleveland, Ohio 1986, Local Arrangements Chair, 1986 Regional Meeting (ENAR) 1981-1983, Member, Regional Advisory Board (ENAR)

Virginia Academy of Sciences (Member 1960-1967) 1966-1967 Vice President, Statistics Section

Southern Regional Council on Statistics (Member 1986-1993; 2000-) 2012 Local Arrangements Chair, Jekyll Island, Georgia 2010-2011 Past-President and Member of Program Committee for 2011 SRC 2009 Co-Program Chair, Summer Research Conference, Jekyll Island, Georgia 2008-2009 President 2006-2007 President-Elect 1992-1994 Executive Committee, Secretary 1988-1990 Member, Summer Research Conference Planning Committee 1989 Program Chair, Summer Research Conference 1989-1993 Chair, Awards Committee 1986-1993 Institutional Representative

Society for Clinical Trials (Member since 1994) th 2009 Invited Session Organized and Speaker at Annual Meeting, May 4 2004 Organized and Chaired Invited Session at Annual Meeting, May 26th 2004 Program Committee 175

CONSULTING AND/OR ADVISING 2011-2014 St. Jude Medical 2008-2009 Eagle Pharmaceuticals 1993-1995 Scientific Review Committee, American Cancer Society - "Colon Polyp Prevention Study" 1992-1993 Chief Statistician, Statistical Protocol Review Group, National Institute for Occupational Safety and Health 1991-1994 CytRx Corporation 1991-1994 Theragenics Corporation 1991-1994 Porex Pharmaceuticals 1990-1994 Solvay Pharmaceuticals 1990-1995 Technical Advisory Committee, American Cancer Society – “A Clinical Study of a Calorie Controlled/Low Fat Diet in Prevention of Breast Cancer Recurrence” 1990-1991 Bard Urological 1989-1990 Norwich-Eaton Pharmaceuticals 1986-1989 Labthermics Technologies, Inc. 1983 Middle South Utilities 1983-1987 Veterans Administration, Operations Committee Member 1980 DeKalb County School System 1979-1980 Mary Ann Oakley, Attorney (Age Discrimination Case) 1974- Centers for Disease Control and Prevention 1976-1980 Georgia Power Company (Environmental Studies Division) 1976 National Heart and Lung Institute

REFEREEING (STATISTICAL JOURNALS) Journal of the American Statistical Association, The American Statistician, Biometrics, Technometrics, Communications in Statistics, Journal of Statistical Computation and Simulation, Journal of Official Statistics

JOURNAL EDITORSHIP Statistical Editor, Annals of Epidemiology (2003-2008)

OUTSIDE PROFESSIONAL ACTIVITIES

Data and Safety Monitoring Boards • Member, Data and Safety Monitoring Committee, Winship Cancer Institute, 2011-present • Member, Data and Safety Monitoring Committee for NIDDK U01 grant: “Treatment of Chronic Disease Mineral Bone Disorder” • Home-Based AIDS Core Project, Chair, DSMB, Uganda/CDC • Multicenter Selective Lymphadenectomy Trial (MSLT) funded by the National Cancer Institute • HALT-C Trial funded by National Institute of Diabetes, Digestive and Kidney Diseases • Chair, Data Safety Monitoring Committee, “A Peer-led, Medical Disease Self-management Program for Mental Health Consumers” (PI: B. Druss)

Advisory Committees/Special NIH Panel Reviewer • Special Reviewer NIH/NCI Grants • Special Reviewer NIH/NIAID Training Grants • Alumni Advisory Committee, Texas A & M, Department of Statistics • Advisory Committee, Lung Cancer SCORE Grant, Winship Cancer Institute • Advisory Committee, Exploratory Nursing Research Center, Emory University School of Nursing • Dialysis Outcomes and Practice Patterns Study Advisory Board Member, AMGEN. • Advisory Board, Department of Mathematical Sciences, Clemson University • Review Biostatistics and Bioinformatics Programs, Northwestern University School of Medicine

GRANT SUPPORT (2011-2014)

• 5 P30 AI50409-15 (Curran), 08/01/98-01/01/15 0.60 calendar months NIH $1,357,566, Centers for AIDS Research • 3P01CA116676-05S1 (Khuri), 06/20/06-05/31/12 0.24 calendar months NIH $4,420,995, Targeting Cell Signaling in Lung Cancer to Enhance Therapeutic Efficacy 176

• 5 P50 MH077083-04 (Mayberg), 07/14/06-06/30/11 0.60 calendar months NIH $1,202,123, Predictors of Antidepressant Treatment Response: The Emory Cidar • 5 P01 HD32571-19 (English), 04/20/95-03/31/17 0.60 calendar months NIH/NICHD $3,402,250, Spinal Circuits and the Musculoskeletal System • 5 P50 MH077928-04 (Stowe), 09/01/07-07/31/12 0.60 calendar months NIH/NIMH $4,098,570, Perinatal Stress and Gene Influences: Pathways to Infant Vulnerability • 5 P01 HL086773-03 (Roback), 07/01/08-08/31/13 0.96 calendar months NIH $1,249,686, Mechanisms and Interventions Addressing Serious Hazards of Transfusion and Cellular Therapies • 5 R21 AT004220-02 (Kutner), 07/01/09-06/30/12 0.60 calendar months NIH $152,756, Melatonin Supplementation and the Metabolic Syndrome • 3 R21 AT00450901-A2S1 (Abramson), 09/30/09-09/29/11 0.48 calendar months NIH $162,875, Melatonin and Nighttime Blood Pressure in African Americans • 1 R34 AI091437-01 (Omer), 09/23/10-08/31/12 0.36 calendar months NIH $174,916, Effects of Maternal Influenza Immunization: A Field Trial in Guatemala • 1 P01 HL101398-01 (Sheps), 09/01/10-05/31/15 0.60 calendar months NIH/NHLBI $1,425,790, Mental Stress Ischemia: Mechanisms and Prognosis

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JEFFREY S. MORRIS Department of Biostatistics, University of Texas M.D. Anderson Cancer Center P.O. Box 301402, Houston, Texas 77230-1402 Voice: 713-563-4284 Email: [email protected]

EDUCATION Ph.D., Statistics, Texas A&M University, August 2000. Advisors: Raymond J. Carroll and Naisyin Wang M.S., Statistics, Texas A&M University, December 1997. B.S., Mathematics Education, Messiah College, May 1993.

PROFESSIONAL EXPERIENCE - February 2011-: Deputy Chair, Department of Biostatistics, University of Texas MD Anderson Cancer Center - September 2010- : Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center - August 2010-February 2011: Long Term Visiting Fellow, Statistical and Applied Mathematical Sciences Institute (SAMSI), Analysis of Object Data - September 2005-August 2010: Associate Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center. - May 2001-July 2001: Visiting Fellow, University of Kent at Canterbury. - August 2000-August 2005: Assistant Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center. - June 1998-August 2000: Research Assistant, Texas A&M University. - January 1998-May 1998: Assistant Lecturer, Texas A&M University. - May 1997-July 1997: Intern, Hoechst Marion Roussel, Kansas City, MO. - August 1995-December 1997: Teaching Assistant, Texas A&M University - August 1993-August 1995: Teacher, Northside Christian School, St. Petersburg, FL - January 1993-July 1993: Computer Programmer, IBM, Mechanicsburg, PA.

HONORS - Myrto Lefkopoulou Distinguished Lectureship, Harvard University, 2011 - Fellow, American Statistical Association, 2011 - H. O. Hartley Award, Texas A&M University Department of Statistics, 2009 - American Statistical Association Noether Young Scholar Award, 2005 - Thomson-ESI Hot Paper in the Field of Computer Science, July 2005 - MD Anderson Cancer Center E.N. Cobb Faculty Scholar Award, 2004 - Best Presentation, 4th Critical Assessment of Microarray Data Analysis, 2003 - Mitchell Prize for Outstanding Bayesian Application Paper, 2003 - JASA Applications and Case Studies Editor’s Invited Paper, 2003 - Best Abstract, 1st Annual Proteomics Data Mining Conference, 2002 - Travel Award for Young Researchers, Biometrics Section of ASA, 2001 - Texas A&M College of Science Dean’s Graduate Fellowship, 1995 - Texas A&M University Graduate Merit Fellowship, 1995

RESEARCH GRANTS AND CONTRACTS Current: • National Cancer Institute, (CA-096520), T32, Training Program in Biostatistics for Cancer Research, Funded Through 2018. (Co-PI, Marina Vannucci PI). • National Cancer Institute, (CA-160736), R01, Integrative Methods for High-Dimensional Genomics Data, Funded through 2015. (Co-PI, Veera Baladandayuthapani PI). • National Cancer Institute (CA-016672), P30, Cancer Center Support Grant, 2000-present (Statistician, Ron DePinho PI). Funded through 2018. • National Institute on Drug Abuse (DA-032581), R01, Beyond Cue Reactivity: ERPs,Sensitivity to Natural Rewards, and Smoking Cessation, Funded through 2015. (Co-Investigator, Francesco Versace PI). • National Cancer Institute, (CA-137213), R01, 15-LOX-1 effects on colitis and colon cancer, Funded through 2011. (Statistician, Imad Shureiqi PI). • National Cancer Institute, (CA-142969), R01, Molecular targeting of PPAR-delta in colon cancer, funded through 2015. (Co-Investigator, Imad Shureiqi, PI)

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• National Cancer Institute, (CA-130821), P01, Cellular and Molecular Mechanisms of Gastrointestinal Cancers, Funded through 2014. (Co-Investigator, Lopa Misra PI). • National Cancer Institute, (CA-158676), R21, Determinants of Efficacy to the Akt Inhibitor Perifosine in Metastatic Colorectal Cancer, Funded through 2013. (Statistician, Cathy Eng PI). • National Cancer Institute, (CA-045809), U10, UT MD Anderson Cancer Center Community Clinical Oncology Research Base, Funded through 2017. (Biostatistics Core Director, Michael Fisch PI). • National Cancer Institute, (CA172670), R01, Stress Signaling Pathways and Resistance in Colorectal Cancer, Funded through 2017 (Co-Investigator, Scott Kopetz PI). • National Cancer Institute, (CA170035), R21, Integrating plasma IGF-1 into novel classification of hepatocellular carcinoma, Funded through 2014. (Co-Investigator, Ahmed Kaseb PI) • Cancer Prevention & Research Institute of Texas (CPRIT), (RP101207), P04, CERCIT: Comparative Effectiveness Research of Cancer in Texas, Funded through 2013 (Collaborator, Linda Elting PI). • National Institute on Minority Health and Health Disparities, (MD-007056), R01, Environmental and Genetic Factors for Pancreatic Cancer Among Blacks, Funded through 2017. (Statistician, Donghui Li, PI)

Completed: • National Cancer Institute (CA-107304), R01, Adaptive Methods for Biomedical Functional Data, 2004-2013 (PI). • National Cancer Institute (CA-098380), R01, Molecular Epidemiology of Pancreatic Cancer, 2004-2011 (Statistician, Donghui Li PI). • National Cancer Institute, (CA-136980), K23, SrC Inhibition in Colorectal Cancer, Funded through 2013. (Statistician, Scott Kopetz PI). • National Cancer Institute, (CA-142969), R01, Molecular Targeting of PPAR-delta in colon cancer, (Statistician, Imad Shureiqi, PI), Funded through 2011. • National Institute for Alcohol Abuse (AA-016157), R01, Brain Biomarkers of Alcoholism and Abstinence, 2006- 2011 (co-PI, Howard Gutstein PI). • National Institute on Drug Abuse (DA-0154604), R01, From Drug Use to Addiction: Unearthing the Switches, 2002-2007 (Collaborator, Howard Gutstein PI). • National Institute for Alcohol Abuse (AA-1388602), R56, Proteomic Approaches to Alcoholism, 2005-2008 (Collaborator, Howard Gutstein PI). • National Cancer Institute (CN-005126), N01, A Phase I/II Study of Celecoxib in Genotype-Positive, Phenotype- Negative Children with FAR, 2000-2007 (Statistician, Patrick Lynch PI). • American Cancer Society (RSG-04-020-01-CNE), 15-Lipoxygenase-1 and Mechanisms of Colorectal Tumorigenesis, 2004-2007 (Statistician, Imad Shureiqi PI). • National Cancer Institute (CA-104278), R01, Molecular Targeting of 15-Lipoxygenase-1 Colon Cancer, 2004-2008 (Statistician, Imad Shureiqi PI) • National Cancer Institute (CA-106577), R01, 5-LOX-1 and Clinical Chemoprevention of Colon Tumors (Collaborator, Imad Shureiqi PI). 2005-2009. • National Cancer Institute (CA-139767), R13, Conference on “Statistical Methods for Complex Biological Data”, 2009-2010 (PI).

Patents: 1. Morris JS and Gutstein H, inventors: Method and Computer-Program Product for Detecting and Quantifying Protein Spots, Patent Number US 8,031,925, Issue Date 10/4/2011.

PUBLICATIONS (Note: * indicates corresponding or joint first/corresponding author) [1] Hong MY, Chapkin RS, Wild CP, Morris JS, Wang N, Carroll RJ, Turner ND and Lupton JR (1999). Relationship Between DNA Adduct Levels, Repair Enzyme and Apoptosis as a Function of DNA Alkylation by Azoxymethane. Cell Growth and Differentiation, 10: 749-758. [2] Hong MY, Lupton JR, Morris JS, Wang N, Carroll RJ, Davidson LA, Elder R and Chapkin RS (2000). Dietary Fish Oil Reduces 06-methylguanine DNA Adduct Levels in the Rat Colon In Part By Increasing Apoptosis During Tumor Initiation. Cancer Epidemiology, Biomarkers and Prevention, 9: 819-826. [3] Davidson LA, Brown RE, Chang W-CL, Lupton JR, Morris JS, Wang N, Carroll, RJ, Turner, ND and Chapkin, RS (2000). Morphodensitometric Analysis of Protein Kinase C II Expression in the Rat Colon: Modulation by Diet and Relation to in situ Cell Proliferation and Apoptosis. Carcinogenesis, 21: 1513-1519. [4] Rashid A, Lanlan S, Morris JS, Issa J-PJ, Hamilton SR (2001). CpG island methylation in colorectal adenomas. The American Journal of Pathology, 159:1129-1135. [5] Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY and Carroll RJ (2001). Parametric and Nonparametric Methods for Understanding the Relationship Between Carcinogen-Induced DNA Adduct Levels in Distal and Proximal Regions of the Colon. Journal of the American Statistical Association, 96: 816-826.

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[6] Shureiqi I, Cook CD, Morris JS, Soliman AS, Levin B, and Lippman SM (2001). Effect of Age on Risk of Second Primary Colorectal Cancer. Journal of the National Cancer Institute, 93: 1264-1265. [7] Hong MY, Chapkin RS, Morris JS, Wang N, Carroll RJ, Turner ND, Chang WCL, Davidson FA and Lupton JR (2001). Anatomical Site-Specific Response to DNA Damage is Related to Later Tumor Development in the Rat AOM Colon Carcinogenesis Model. Carcinogenesis, 22:1831-1835. [8] Arrington JL, Chapkin RS, Switzer KC, Morris JS and McMurray DN (2001). Dietary n-3 Polyunsaturated Fatty Acids Modulate Purified Murine T-cell Subset Activation. Clinical and Experimental Immunology, 125: 499-507. [9] Shureiqi I, Xu X, Chen D, Lotan R, Morris JS, Fischer SM and Lippman SM (2001). Nonsteroidal Anti- inflammatory Drugs Induce Apoptosis in Esophageal Cancer Cells by Restoring 15-Lipoxygenase-1 Expression. Cancer Research 61: 4879-4884. [10] Chan AOO, Issa-J-PJ, Morris JS, Hamilton SR and Rashid A: Concordant CpG Island Methylation in Hyperplastic Polyposis (2002). The American Journal of Pathology, 160: 529-536. PMID: 11839573. PMCID: PMC1850645. [11] Morris JS (2002). The BLUPs Are Not “Best” When It Comes To Bootstrapping. Statistics and Probability Letters, 56: 425-430. [12] Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY and Carroll RJ (2002). A Bayesian Analysis Involving Colonic Crypt Structure and Coordinated Response to Carcinogens Incorporating Missing Crypts, Biostatistics, 3: 529-546. [13] Baggerly K, Deng L, Morris JS, Aldez CM (2003). Differential expression in SAGE: Accounting for normal between-library variation. Bioinformatics, 19(12): 1477-1483. [14] Baggerly K, Morris JS, Wang J, Gold D, Xiao LC and Coombes K (2003). A comprehensive approach to the analysis of MALDI-TOF proteomics spectra from serum samples. Proteomics, 3: 1667-1672 (Won Best Presentation at 2002 Duke University Proteomics Data Mining Competition). [15] Morris JS, Baggerly K, and Coombes K (2003). Bayesian Shrinkage Estimators of the Relative Abundance of mRNA Transcripts using SAGE. Biometrics, 59: 476-486. [16] Morris JS, Vannucci M, Brown PJ and Carroll RJ (2003). Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis [with discussion]. Journal of the American Statistical Association, 98: 573-583 (Editor’s Invited Paper and chosen to receive Mitchell Prize). [17] Coombes KR, Fritsche HA Jr., Clarke C, Cheng JN, Baggerly KA, Morris JS, Xiao LC, Hung MC, and Kuerer HM (2003). Quality Control and Peak Finding for Proteomics Data Collected from Nipple Aspirate Fluid Using Surface Enhanced Laser Desorption and Ionization. Clinical Chemistry, 49(10): 1615-1623. [18] Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY, and Carroll RJ (2003). Understanding the Relationship between Carcinogen-induced DNA Adduct Levels in Distal and Proximal Regions of the Colon. Advances in Experimental Medicine and Biology, 537: 105-116. [19] Lin E, Morris JS, and Ayers GD (2003). Effect of Celecoxib on capecitabine-induced hand-foot syndrome and antitumor activity. Oncology, 16 (12 supplement No 14): 31-37. [20] Madoff DC, Hicks ME, Abdalla EK, Morris JS and Vauthey JN (2003). Portal vein embolization using polyvinyl alcohol particles and coils in preparation for major liver resection for hepatobiliary malignancy: Safety and Efficacy: A study in 26 patients. Radiology, 227(1): 251-260. [21] Shureiqi I, Jiang W, Zuo X, Wu Y, Stimmel JB, Leesnitzer LM, Morris JS, Fan HZ, Fischer SM, Lippman SM (2003). The 15-lipoxygenase-1 product 13-S-hydroxyocta-decadienoic acid down-regulates PPAR-{delta} to induce apoptosis in colorectal cancer cells. Proceedings of the National Academy of Sciences, 100(17): 9968-9973. PMID: 12909723. PMCID: PMC187904. [22] Pawlik TM, Paulino AF, Mcginn CJ, Baker LH, Cohen DS, Morris JS, Rees R, and Sondak VK (2003). Cutaneous angiosarcoma of the scalp: A multidisciplinary approach. Cancer, 98(8): 1716-1726. [23] Pawlik TM, Izzo F, Cohen DS, Morris JS, and Curley SA (2003). Combined resection and radiofrequency ablation for advanced hepatic malignancies: Results in 172 patients. Journal of Surgical Oncology, 10(9): 1059-1069. [24] Baggerly, KA, Morris JS, and Coombes KR (2004). Reproducibility of SELDI Mass Spectrometry Patterns in Serum: Comparing Proteomic Data Sets from Different Experiments. Bioinformatics, 20(5): 777-785 (Identified by Thomson-ISI as “one of the most cited recent papers in the field of computer science”,see http://www.esi- topics.com/nhp/2005/july-05-KeithBaggerly.html). [25] Baggerly KA, Edmonson S, Morris JS, and Coombes KR (2004). High-Resolution Serum Proteomic Patterns for Ovarian Cancer Detection. Endocrine-Related Cancers, 11(4): 583-584. [26] Baggerly KA, Deng L, Morris JS, and Aldez CM (2004). Overdispersed Logistic Regression for SAGE: Modeling Multiple Groups and Covariates. BMC Bioinformatics, 5:144. PMID: 1569612. PMCID: PMC524524. [27] Marron JS, Muller HG, Rice J, Wang JL, Wang N, Wang Y, Coull B, Fahrmeier L, Guo W, Hall P, Harezlak J, Huang J, Kneip A, Lin X, Morris JS, Pourmadi M, Staudenmayer J, Wu C, Zhang D, Zhang H, and Zhao Y (2004). Discussion of nonparametric and semiparametric regression. Statistica Sinica 14(3): 615-621. [28] Sinicrope FA, Half E., Morris JS, Lynch PM, Morrow JD, Levin B, Steinbach G, Hawk ET, Cohen DS, Ayers GD, Stephens LC, FAP Study Group (2004). Cell proliferation and apoptotic indices predict adenoma regression

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in a placebo-controlled trial of celecoxib in Familial Adenomatous Polyposis (FAP) patients. Cancer Epidemiology, Biomarkers, and Prevention, 13(6): 1-8. [29] Ajani J, Walsch G, Komaki RR, Morris JS, Swisher SG, Lynch P, Wu TT, Vaporciyan A, Faust JC, Nivers RJ, and Roth J (2004). Preoperative induction CPT-11 and cisplatin chemotherapy followed by chemoradiotherapy in patients with local-regional carcinoma of the esophagus or gastroesophageal junction. Cancer, 100(11): 2347- 2354. [30] Kalha I, Kaw M, Fukami N, Patel M, Singh S, Gagneja H, Cohen D, Morris JS (2004). The accuracy of endoscopic ultrasound for restaging esophageal carcinoma after chemoradiation therapy. Cancer, 101(5): 940-947. PMID: 15329901. [31] Ajani JA, Mansfield PF, Janjan N, Morris JS, Pisters PW, Lynch PM, Feig B, Myerson R, Nivers R, Cohen DS, and Gunderson LL (2004). A multi-institutional trial of preoperative chemoradiotherapy in patients with potentially resectable gastric carcinoma. Journal of Clinical Oncology, 22(14), 2774-2780. [32] Baggerly KA, Morris JS, Edmonson S, and Coombes KR (2005). Signal in Noise: Evaluating Reported Reproducibility of Serum Proteomic Tests for Ovarian Cancer. Journal of the National Cancer Institute, 97: 307- 309, (with commentary). [33] Morris JS, Coombes KR, Kooman J, Baggerly KA, and Kobayashi R (2005). Feature Extraction and Quantification for Mass Spectrometry Data in Biomedical Applications Using the Mean Spectrum. Bioinformatics, 21(9): 1764-1775. [34] Coombes KR, Morris JS, Hu J, Edmondson SR, and Baggerly KA (2005). Serum Proteomics Profiling: A Young Technology Begins to Mature. Nature Biotechnology, 23(3): 291-292. PMID: 15765078. [35] Hu J, Coombes KR, Morris JS, and Baggerly KA (2005). The Importance of Experimental Design in Proteomic Mass Spectrometry Experiments: Some Cautionary Tales. Briefings in Genomics and Proteomics, 3(4), 322-331. [36] Coombes KR, Tsavachidis S, Morris JS, Baggerly KA, and Kuerer HM (2005). Improved Peak Detection and Quantification of Mass Spectrometry Data Acquired from Surface-Enhanced Laser Desorption and Ionization by Denoising Spectra with the Undecimated Discrete Wavelet Transform. Proteomics, 5: 4107-4117. PMID: 16254928. [37] Baggerly KA, Coombes KR, and Morris JS (2005). Bias, Randomization, and Ovarian Proteomic Data: A Reply to Producers and Consumers. Cancer Informatics, 1(1): 9-14. PMID: 19305627. PMCID: PMC26527654. [38] Coombes KR, Koomen, JM, Baggerly KA, Morris JS, and Kobayashi R (2005). Understanding the characteristics of mass spectrometry data through the use of simulation. Cancer Informatics, 1(1): 41-52. PMID: 19305631. PMCID: 2657656. [39] Madoff DC, Abdalla EK, Gupta S, Wu TT, Morris JS, Denys A, Wallace MJ, Morello FA Jr, Ahrar K, Murthy R, Lunagomez S, Hicks ME, Vauthey JN (2005). Transhepatic ipsilateral right portal vein embolization extended to segment IV: improving hypertrophy and resection outcomes with spherical particles and coils. Journal of Vascular and Interventional Radiology, 2(1): 215-225. [40] Ajani JA, Mansfield PF, Crane CH, Wu TT, Lunagomez S, Lynch PM, Janjan N, Feig B, Faust J, Yao JC, Nivers R, Morris JS, and Pisters PW (2005). Paclitaxel-based chemoradiotherapy in localized gastric carcinoma: Degree of pathologic response and not clinical parameters dictated patient outcome. Journal of Clinical Oncology, 23(6), 1237-1244. [41] Hu, J, Yin G, Morris JS, Zhang L, and Wright FA (2005). Entropy and Survival-based Weights to Combine Affymetrix Array Types in the Analysis of Differential Expression and Survival. Methods of Microarray Data Analysis IV, eds. JS Shoemaker and SM Lin, pp. 95-108, New York: Springer-Verlag. [42] Morris JS, Yin G, Baggerly KA, Wu C, and Zhang L (2005). Pooling Information Across Different Studies and Oligonucleotide Microarray Chip Types to Identify Prognostic Genes for Lung Cancer. Methods of Microarray Data Analysis IV, eds. JS Shoemaker and SM Lin, pp. 51-66, New York: Springer-Verlag, 2005 (Won best presentation at CAMDA 2003 meetings). [43] Chirieac LR, Swisher SG, Ajani JA, Komaki RR, Correa AM, Morris JS, Roth JA, Rashid A, Hamilton SR, and Wu TT (2005). Posttherapy pathological stage predicts survival in patients with esophageal carcinoma receiving preoperative chemoradiation. Cancer, 103(7), 1347-1355. [44] Beach R, Chan AOO, Wu TT, White JA, Morris JS, Lunagomez S, Broaddus RR, Issa JP, Hamilton SR, and Rashid A (2005). BRAF mutations in aberrant crypt foci and hyperplastic polyposis. The American Journal of Pathology, 166(4), 1069-1075. PMID: 15793287. PMCID: PMC1602378. [45] Hong D, Lunagomez S, Kim EE, Lee JH, Bresalier RS, Swisher SG, Wu TT, Morris JS, Liao Z, Komaki R, and Ajani JA (2005). Value of baseline positron emission tomography for predicting overall survival in patients with non-metastatic esophageal or gastroesophageal junction carcinoma. Cancer, 104(8): 1620-1626. [46] Shureiqi I, Wu Y, Chen D, Yang XL, Guan B, Morris JS, Yang P, Newman RA, Broaddus R, Hamilton SR, Lynch P, Levin B, Fischer SM, and Lippman SM (2005). Critical role of 15-Lipoxygenase-1 in colorectal epithelial cell terminal differentiation and tumorigenesis. Cancer Research, 65(24): 11486-92. PMID: 16357157. PMCID: PMC1564070. [47] Morris JS and Carroll RJ (2006). Wavelet-Based Functional Mixed Models. Journal of the Royal Statistical Society, Series B, 68(2): 179-199. PMID: 19759841. PMCID: PMC2744105. 181

[48] Morris JS, Arroyo C, Coull B, Ryan LM, Herrick R, and Gortmaker SL (2006). Using Wavelet-Based Functional Mixed Models to Characterize Population Heterogeneity in Accelerometer Profiles: A Case Study. Journal of the American Statistical Association, 101(476): 1352-1364. PMID: 19169424. PMCID: PMC2630189. [49] Mayo MS, Gajewski BJ, and Morris JS (2006): Some Statistical Issues in Microarray Gene Expression Data. Radiation Research, 165(6): 745-748. [50] Zuo X, Wu Y, Morris JS, Stimmel JB, Leesnitzer LM, Fischer SM, Lippman SM, Shureiqi I (2006). Oxidative metabolism of linoleic acid modulates PPAR-beta/delta suppression of PPAR-gamma activity. Oncogene, Feb 23; 25(8):1225-41. [51] Baggerly KA, Coombes KR, and Morris JS (2006). An Introduction to High-Throughput Bioinformatics Data. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds., Cambridge University Press, 1-39. [52] Guindani M, Do KA, Muller P, and Morris JS (2006). Bayesian Mixture Models for Gene Expression and Protein Profiles. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds., Cambridge University Press, 238-253. [53] Morris JS, Baggerly KA, and Coombes KR (2006). Shrinkage Estimation for SAGE Data using a Mixture Dirichlet Prior. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds., Cambridge University Press, 254-268. [54] Morris JS, Brown PJ, Baggerly KA, and Coombes KR (2006). Analysis of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds., Cambridge University Press, 269-292. [55] Rohatgi PR, Mansfield PF, Crane CH, Wu TT, Sunder PK, Ross WA, Morris JS, Pisters PW, Feig BW, Gunderson LL, and Ajani JA (2006). Surgical pathology stage by The American Joint Commission On Cancer (AJCC) criteria predicts patient survival after preoperative chemoradiation for localized gastric carcinoma. Cancer, 107(7): 1475-1482. [56] Krishnan S, Janjan NA, Skibber JM, Rodrigues-Bigas MA, Wolff RA, Das P, DELclos ME, Chang GJ, Hoff PM, Eng C, Brown TD, Crane CH, Feig BW, Morris JS, Vadhan-Raj S, Hamilton SR, and Lin EH (2006). Phase II study of capecitabine (Xeloda) and concomitant boost radiotherapy in patients with locally advanced rectal cancer. Journal of Radiation Oncology, Biology, and Physics, 66(3): 762-771. [57] Herrick RC, Morris JS (2006). Wavelet-based functional mixed model analysis: Computational Considerations. Proceedings, Joint Statistical Meetings, ASA Section on Statistical Computing, 2051-2053. [58] Lin EH, Curley SA, Crane CC, Feig B, Skibber J, Delcos M, Vadhan SR, Morris JS, Ayers GD, Ross A, Brown T, Rodriguez-Bigas MA, and Janjan N (2006). Retrospective study of capecitabine and celecoxib in metastatic colorectal cancer: potential benefits and COX-2 as the common mediator in pain, toxicities and survival? Journal of Clinical Oncology, 29(3): 232-9. [59] Karpievitch YV, Hill EG, Morris JS, Coombes KR, Baggerly KA and Almeida JS (2007). PrepMs. Bioinformatics 23(2): 264-265. PMID: 17121773. PMCID: PMC2633108. [60] Song JJ, Lee HJ, Morris JS, and Kang S (2007). Clustering of time-course gene expression data using functional data analysis. Computational Biology and Chemistry, 31(4), 265-274. PMID: 17631419. PMCID: PMC1992527. [61] Gutstein HB and Morris JS (2007). Laser capture sampling and analytical issues in proteomics. Expert Reviews in Proteomics, 4(5), 627-637. PMID: 17941818. PMCID: PMC2639751. [62] Anandasabapahty S, Jhamb J, Davila M, Wei C, Morris JS, and Bresalier R (2007). Clinical and endoscopic factors predict higher pathologic grades of Barrett dysplasia. Cancer, 109(4): 558-574. [63] Cradock AL, Melly SJ, Allen JG, Morris JS, and Gortmaker SL (2007). Characteristics of school campuses and youth physical activity: Does size matter? American Journal of Preventative Medicine, 33(2): 106-113. PMID: 17673097. PMCID: PMC1992527. [64] Patel PR, Mansfield PF, Crane CH, Wu TT, Lee JH, Lynch PM, Morris JS, Pisters PW, Feig B, Sunder PK, Izzo JG, Ajani JA (2007). Clinical stage after preoperative chemoradiation is a better predictor of patient outcome than the baseline stage for localized gastric cancer. Cancer, 110(5): 989-995. [65] Coombes, KR, Baggerly KA, and Morris JS (2007). Pre-Processing Mass Spectrometry Data. Fundamentals of Data Mining in Genomics and Proteomics, W Dubitzky, M Granzow, and D Berrar, eds. Kluwer, Boston, 79-99. [66] Thomas MB, Chadha R, Glover K, Wang X, Morris JS, Brown T, Rashid A, Dancey J, & Abbruzzesse JL (2007). A phase II study of Erlotinib (OSI 774) in patients with unresectable hepatocellular carcinoma. Cancer, 110 (5): 1059-1067. [67] Shureiqi I, Zuo X, Broaddus R, Wu Y, Guan B, Morris JS, and Lippman SM (2007). The transcription factor GATA-6 is overexpressed in vivo and contributes to silencing 15-LOX-1 in vitro in human colon cancer. FASEB Journal, 21(3): 743-753. PMID: 17167069. PMCID: PMC1847772. [68] Chan AOO, Jim MH Lam KF, Morris JS, Siu DCW, Tong T, Ng FH, Wong SY, Hui WM, Chan CK, Lai KC, Cheung TK, Chan P, Wong G, Yuen MF, Lau YK, Lee S, Szeto ML, Wong BCY, and Lam SK (2007). Association of colorectal cancer and ademonas in patients with newly diagnosed coronary artery disease: a cross sectional study. Journal of the American Medical Association, 98(12): 1412-1419. PMID: 17895457.

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[69] Morris JS, Clark BN and Gutstein HB (2008). Pinnacle: A Fast, Automatic Method for Detecting and Quantifying Protein Spots in 2-Dimensional Gel Electrophoresis Data. Bioinformatics, 24, 529-536. PMID: 18194961. PMCID: PMC2662725. [70] Gutstein HB, Morris JS, Annangudi SP, and Sweedler JV (2008). Microproteomics: Analysis of protein diversity in small samples. Mass Spectrometry Reviews, 27, 316-330. PMID: 18271009. PMCID: PMC2743962. [71] Zuo X, Shen L, Issa JP, Moy O, Morris JS, Lippman SM, Shureiqi I (2008). 15-Lipxygenase-1 transcriptional silencing by DNA methyltransferase-1 independently of DNA methylation. FASEB Journal, 22(6): 1981-92. PMID: 18198215. PMCID: PMC2410033. [72] Suehiro Y, Wong CW, Chireac LR, Kondo Y, Shen L, Webb CR, Chan YW, Chan AS, Chan TL, Wu TT, Rashid A, Hamanaka Y, Hinoda Y, Shannon RL, Wang X, Morris JS, Issa JP, Yuen ST, Leung SY and Hamilton SR (2008). Epigenetic-genetic interactions in the APC/WNT, RAS/RAF and P53 pathways colorectal carcinoma. Clinical Cancer Research, 14(9): 2560-2569. PMID: 18451217. PMCID: PMC3544184. [73] Wu Y, Fang B, Yang XQ, Wang L, Chen D, Krasnykh V, Carter BZ, Morris JS, Shureiqi I (2008). Therapeutic molecular targeting of 15-Lipoxygenase-1 in colon cancer. Molecular Therapy, 16(5): 886-892. PMID: 18388920. PMCID: PMC2377397. [74] Morris JS (2008). Statistical Issues in Proteomic Research. Bulletin of the International Society for Bayesian Analysis, 14(4), 9-13. [75] Suzuki H, Morris JS, Li Y, Doll MA, Hein DW, Liu J, Jiao L, Hassan MM, Day RS, Bondy ML, Abbruzzese JL, Li D (2008). Interaction of the cytochrome P4501A2, SULT1A1 and NAT gene polymorphisms with smoking and dietary mutagen intake in modification of the risk of pancreatic cancer. Carcinogenesis, 29(6):1184-91. PMID: 18499698, PMCID: PMC2443278. [76] Overman MJ, Kopetz S, Wen S, Hoff PM, Fogelman D, Morris JS, Abbruzzesse JL, Ajani JA, and Wolff RA (2008). Chemotherapy with 5-fluorouracil and a platinum compound improves outcomes in metastatic small bowel adenocarcinoma. Cancer, 2008 Oct 15; 113(8): 2038-45. [77] Morris JS (2008). Comment on “Sure independence screening for ultra-high dimensional feature space,” by Jianqing Fan and Jinchi Lv, Journal of the Royal Statistical Society Series B, 70:5, 900-901. [78] Morris JS, Brown PJ, Herrick RC, Baggerly KA, and Coombes KR (2008). Bayesian Analysis of Mass Spectrometry Data using Wavelet Based Functional Mixed Models. Biometrics, 12, 479-489. PMID: 17888041. PMCID: PMC2659628. [79] Zuo X, Morris JS, and Shureiqi I (2009). Chromatin modification requirements for 15-lipoxygenase-1 transcriptional reactivation in colon cancer cells. J Biol Chem., 283(46): 31341-7. PMID: 18799463. PMCID: PMC2581547. [80] Li D, Suzuki H, Liu B, Morris JS, Liu J, Okazaki T, Li Y, Chang P, and Abbruzzese JL (2009). DNA repair gene polymorphisms and risk of pancreatic cancer. Clinical Cancer Research, 15: 740-746. PMID: 19147782. PMCID: PMC26229144. [81] Thomas MB, Morris JS, Chadha R, Iwasaki M, Kaur H, Lin E, Kaseb A, Glover K, Davila M, and Abbruzzese J (2009). Phase II trial of the combination of Bevacizumab and Erlotinib in patients who have advanced hepatocellular carcinoma. Journal of Clinical Oncology, 27(6): 843-850. [82] Overman MJ, Varadhachary GR, Kopetz S, Adinin R, Lin E, Morris JS, Eng C, Abbruzzese JL, and Wolff RA (2009). Phase II study of Capecitabine and Oxaliplatin for advanced adenocarcinoma of the small bowel and ampulla of vater. Journal of Clinical Oncology, 2009 Jan 21 (Epub ahead of print). [83] Kamat P, Wen S, Morris JS, and Anandasabapathy S (2009). Exploring the association between elevated body mass index and Barrett’s esophagus: a systematic review and meta-analysis. Annals of Thoracic Surgery, 87(2): 655-662. [84] Zuo X, Morris JS, Broaddus R, and Shureiqi I (2009). 15-LOX-1 transcription suppression through the NuRD complex in colon cancer cells. Oncogene 28(12): 1496-1505. [85] Fleming JB, Gonzalez RJ, Petzel MQ, Lin E, Morris JS, Gomez H, Lee JE, Crane CH, Pisters PW, Evans DB (2009). Influence of obesity on cancer-related outcomes after pancreatectomy to treat pancreatic adenocarcinoma. Arch Surg. 144(3): 216-221. [86] Zuo X, Peng Z, Moussalli MJ, Morris JS, Broaddus RR, Fischer SM, and Shureiqi I (2009). Targeted PPAR-δ genetic disruption profoundly inhibits colon tumorigenesis. Journal of the National Cancer Institute, 101(10): 762-767. PMID: 19436036. PMCID: PMC2684551. [87] Li D, Morris JS, Li J, Hassan MH, Day RS, Bondy ML, and Abbruzzese JL (2009). Body mass index and risk, age of onset, and survival in pancreatic cancer patients. Journal of the American Medical Association, 301(24), 2553- 2562. PMID: 19549972. PMCID: PMC2760963. [88] Morris JS (2009). Review of “Wavelet Methods in Statistics with R” by GP Nason. Biometrics, 65(2): 667-668. [89] Cradock AL, Melly SJ, Allen JG, Morris JS, Gortmaker SL (2009). Youth destinations associated with objective measures of physical activity in adolescents. Journal of Adolescent Health, 45(3): S91-98. PMID: 19699443. PMCID: PMC3260553.

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[90] Morris JS, Clark BN, Wei W, and Gutstein HB (2010): Evaluating the performance of new approaches to spot quantification and differential expression in 2-dimensional gel electrophoresis studies. Journal of Proteome Research, 9(1): 595-604. PMID: 19919108. PMCID: PMC2802214. [91] Morris JS (2010): Member’s Discoveries: Fatal flaws in cancer research. IMS Bulletin, 39(1), 5. [92] Dowsey AW, Morris JS, Gutstein HG, Yang GZ (2010): Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images. Methods in Molecular Biology, 604: 239-255 PMID: 20013375. NIHMSID: 478641 [93] Morris JS, Wu C, Coombes KR, Baggerly KA, Wang J, and Zhang L (2010). Alternative Probeset Definitions for Combining Microarray Data Across Studies Using Different Versions of Affymetrix Oligonucleotide Arrays. Meta-Analysis and Combining Information in Genetics and Genomics, eds. Rudy Guerra and Darlene Goldstein, Chapman-Hall, 157-174. [94] Kopetz S, Hoff PM, Morris JS, Wolff RA, Eng C, Glover K, Adinin R, Overman M, Valero V, Wen S, Lieu C, Yan S, Tran H, Ellis LM, Abbruzzesse JL, and Heymach JV (2010). Phase II Trial of Infusional 5-Fluorouracil, Irinotecan and Bevacizumab (FOLFIRI+B) for Metastatic Colorectal Cancer: Efficacy and Circulating Angiogenic Biomarkers Associated with Therapeutic Resistance. Journal of Clinical Oncology, 28(3):453-459. PMID: 20008624. PMCID: PMC2815707. [95] Malloy EJ, Morris JS, Adar SD, Suh HH, Gold DR, and Coull BA (2010): Wavelet-based functional linear mixed models: an application to measurement error corrected distributed lag models. Biostatistics 11(3): 432-52, Epub 2010 Feb 15, PMID: 20156988. PMCID: PMC2883305. [96] Morris JS, Baggerly KA, Gutstein HB, and Coombes KR (2010). Statistical contributions to proteomic research. Methods in Molecular Biology, 641:143-166. PMID: 20407946. NIHMS 261718. [97] Baladandayuthapani V, Ji Y, Talluri R, Nieto-Barajas LE, and Morris JS (2010). Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data. Journal of the American Statistical Association, 105(492): 1358-1375. PMID: 21512611. PMCID: PMC3079218 [98] Katz R, He W, Khanna A, Fernandez R, Zaidi T, Krebs M, Caraway N, Zhang H, Jiang F, Spitz M, Blowers D, Jimenez C, Mehran R, Swisher S, Roth J, Morris JS, Etzel C, and El-Zein R (2010). Genetically Abnormal Circulating Cells in Lung Cancer Patients an Antigen Independent Fluorescence in-situ Hybridization-Based Case- Control Study. Clinical Cancer Research 16(15): 3976-87 Epub 2010 Jul22 (PMID: 20651054, PMCID: PMC2949278). [99] Shureiqi I, Chen D, Day RS, Hochman FL, Ross W, Cole RA, Moy O, Morris JS, Xiao L, Newman R, Yang P, and Lippman SM (2010). Profiling Lipoxygenase Metabolism in Specific Steps of Colonic Tumorigenesis. Cancer Prevention Research 3(7): 829-38. (PMID: 20570882). [100] Kaseb A*, Xiao L, El-Deeb A, Kumar V, Lin E, Abdalla EK, Vauthey JN, Curley SA, Ellis L, Abbruzzese JL, Hassan MM, and Morris JS* (2010). V-CLIP: Integrating plasma VEGF level into a new scoring system to stratify patients with hepatocellular carcinoma. Cancer 2010 Dec 14.[Epub ahead of print] PMID:21157958. PMCID: PMC3066286. (*Joint corresponding authors) [101] Dowsey AW, English JA, Lisacek F, Morris JS, Yang GZ, and Dunn MJ (2010). Image analysis tools and emerging algorithms for expression proteomics. Proteomics, 10(23), 4226-4257. PMID: 21046614. PMCID: PMC3257807. [102] Dowsey AW, English JA, Lisacek F, Morris JS, Yang GZ, and Dunn MJ (2011). Advance Article A22975: Image Analysis Tools in Proteomics. Encyclopedia of Life Sciences. John Wiley & Sons, Ltd. eScholarID:148685|DOI:10.1002/97804770015902.a0006216.pub2. [103] Morris JS, Baladandauthapani V, Herrick RC, Sanna PP, and Gutstein HG (2011). Automated analysis of quantitative image data using isomorphic functional mixed models, with application to proteomic data. Annals of Applied Statistics, 5(2A): 894-923. PMCID: PMC3298181. [104] Fogelman D, Jafari M, Varadhachary GR, Xiong H, Chang D, Bullock S, Ozer H, Bennett B, Cunningham P, Lin E, Morris JS, Abbuzzesse JL, and Wolff RA (2011). Bevacizumab plus Gemcitabine and Oxaliplatin as First-Line Therapy for Metastatic or Locally Advanced Pancreatic Cancer: A Phase II Study. Cancer Chemotherapy and Pharmacology, 68(6): 1431-1438. [105] Zhu H, Brown PJ, and Morris JS (2011). Robust, Adaptive Functional Regression in Functional Mixed Model Framework. Journal of the American Statistical Association, 106(495): 1167-1179. PMID: 22308015. PMCID: PMC3270884. [106] Diao L, Clarke CH, Coombes KR, Hamilton SR, Roth J, Mao L, Czerniak B, Baggerly KA, Morris JS, Fung ET, and Bast, Jr. RC (2011). Reproducibility of SELDI spectra across time and laboratories. Cancer Informatics, 2011 Mar 14: 10:45-64. PMCID: PMC3085423. [107] Kaseb A*, Abbruzzese JL, Vauthey JN, Aloia TA, Abdalla EK, Hassan MM, Lin E, Xiao L, El-Deeb AS, Rashid A, and Morris JS* (2011). I-CLIP: Improved Stratification of Advanced Hepatocellular Carcinoma Patients by Integrating Plasma IGF-1 into CLIP Score. Oncology, 80(5-6): 373-381. (* Joint corresponding authors). PMID: 21822028. PMCID: PMC3171278. [108] Moussalli MJ, Wu Y, Zhu X, Yang XL, Wistuba II, Raso MG, Morris JS, Bowser JL, Minna JD, Lotan R, and Shureiqi I (2011): Mechanistic Contribution of Ubiquitous 15-Lipoxygenase-1 Expression Loss in Cancer Cells to

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Terminal Cell Differentiation Evasion. Cancer Prevention Research, 2011 Aug 31. PMID: 21881028. PMCID: PMC3232310. [109] Kaseb AO, Morris JS, Hassan MM, Siddiqui AM, Lin E, Xiao L, Abdalla EK, Vauthey JN, Aloia TA, Krishnan S, and Abbruzzese JL (2011). Clinical and Prognostic Implications of IGF-1 and VEGF in Patients with Hepatocellular Carcinoma. Journal of Clinical Oncology, 2011 Sep 12. PMID: 2191725. PMCID: PMC3189091. [110] Sabath N, Morris JS, and Graur D (2011): Is there a twelfth protein-coding gene in the genome of influenza A? A selection-based approach to the detection of overlapping genes in closely related sequences. Journal of Molecular Evolution, 73:305-315. [111] Hrafnkelsson B, Morris JS, Baladandayuthapani V (2012). Spatial Modeling of Annual Minimum and Maximum Temperature in Iceland. Meteorology and Atmospheric Physics, 116(1-2): 43-61. [112] Morris JS (2012): Statistical Methods for Proteomic Biomarker Discovery using Feature Extraction or Functional Data Analysis Approaches, Statistics and its Interface, 5(1), 117-136. NIHMS: 347640 (Awaiting PMC release). [113] Kaseb A, Garrett-Mayer E , Morris JS, Hassan MM, Hassabo H, Iwasaki M, Deaton L, Lin E, Xiao L, Onecescu G, Abbruzzesse JL, and Thomas MB (2012). Final results, clinical and molecular predictors of outcome from bevacizumab and erlotinib phase II trial in advanced hepatocellular carcinoma. Oncology, 82(2): 67-74. [114] Kaseb, AO, Morris JS, Hassan MM, and Abbruzzese JL (2012): Reply to A. Goyal et al. Journal of Clinical Oncology, 30(9): 1019-1020. [115] Morris JS (2012): Review of “Functional Data Analysis with R and MATLAB” by J. Ramsay, G. Hooker, and S. Graves. The American Statistician, 65(4):6-7. [116] Zhu H, Brown PJ, and Morris JS (2012): Robust classification of functional and quantitative image data using functional mixed models. Biometrics, 68(4): 1260-1268. DOI: 10.1111/j.1541-0420.2012.01765.x PMID: 22670567. PMCID: PMC3443537. [117] Jennings EM, Morris JS, Carroll RJ, Manyam GC, and Baladandayuthapani V (2012). Hierarchical Bayesian methods for integration of various types of genomic data. Proceedings, Genomics Signal Processing and Statistics (GENSIPS), December 2, 2012. (refereed proceedings) [118] Zuo X, Peng Z, Wu Y, Moussalli MJ, Yang XL, Wang Y, Parker-Thornburg J, Morris JS, Broaddus RR, Fischer SM, and Shureiqi I (2012). Effects of gut-targeted 15-LOX-1 transgenic expression on colonic tumorigenesis in mice. Journal of the National Cancer Institute, 104(9): 709-716. PMID: 22472308. PMCID: PMC3341308. [119] Wang W, Baladandayuthapani V, Morris JS, Broom BM, Manyam GC, and Do KA (2013). iBAG: Integrative Bayesian Analysis of High-Dimensional Multi-platform Genomic Data. Bioinformatics, 29(2): 149-159. DOI: 10.1093/bioinformatics/bts655. PMID: 23142963. PMCID: PMC3546799. [120] Crainiceanu CM, Caffo BS, and Morris JS (2013): Multilevel Functional Data Analysis. SAGE Handbook for Multilevel Modeling, Simonoff and Marx, eds., Chapter 13, pages 223-248. [121] Lynch P*, Morris JS*, Ross W, Rodriguez-Bigas M, Posadas J, Weber D, Sepeda V, Levin B, and Shureiqi I (2013) Global quantitative assessment of the colorectal polyp burden in familial adenomatous polyposis by using a web- based tool. Gastrointestinal Endoscopy, 77(3): 455-463. PMID: 23332604. PMCID: PMC3574220 (* joint first authors) [122] Martinez JG, Bohn KM, Carroll RJ and Morris JS (2013). A study of Mexican free-tailed bat syllables: Bayesian functional mixed models for nonstationary acoustic time series. Journal of the American Statistical Association, 108(502): 514-526. PMID: 23997376 PMCID: PMC3755785. [123] Fazio MA, Grytz R, Morris JS, Bruno L, Gardiner S, Girkin CA, and Downs JC (2013). Age-related changes in human peripapillary scleral stiffness. Biomechanics and Modeling in Mechanobiology, 2013 Jul30. PMID: 23896936 PMCID: PMC3875631. [124] Raghav KPS, Shetty AV, Kazmi SMA, Zhang N, Morris JS, Taggert M, Fournier K, Royal R, Mansfield P, Eng C, Wolff RA, and Overman MJ (2013). Impact of Molecular Alterations and Targeted Therapy in Appendiceal Adenocarcinomas. The Oncologist, 18(12): 1270-1277 PMID: 24149137 PMCID: PMC3868421. [125] Jennings EM, Morris JS, Carroll RJ, Manyam GC and Baladandayuthapani V (2013). Bayesian methods for expression-based integration of various types of genomics data. EURASIP Journal on Bioinformatics and Systems Biology, 13, doi:10.1186/1687-4153-2013-13. [126] Lieu C, Tran H, Jian Z, Mao M, Overman M, Chen Z, Eng C, Morris JS, Ellis L, Heymach J, and Kopetz S (2013). The association of alternate VEGF ligands with resistance to anti-VEGF therapy in metastatic colorectal cancer (mCRC), PLOS ONE, 8(10), 2013 Oct 15; e77117. PMID: 24143206 PMCID: PMC3797099. [127] Liao L, Moschidis E, Riba-Garcia I, Unwin R, Dunn W, Morris JS, Graham J and Dowsey A (2013). A workflow for novel image-based differential analysis of LC-MS experiments. Proceedings of 61st ASMS Conference on Mass Spectrometry and Allied Topics. Minneapolis, Minnesota, 9th – 13th Jun. eScholarID:209955. (refereed proceedings). [128] Olivares RJ, Rao A, Rao G, Morris JS, and Baladandayuthapani V (2013). Integrative analysis of multi-modal correlated imaging-genomics data in glioblastoma. Proceedings, Genomics Signal Processing and Statistics (GENSIPS), November 17-19, 2013. (refereed proceedings)

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[129] Eberth JM, Eschbach K, Morris JS, Nguyen H, Hossain M, and Elting L (2014). Geographic disparities in mammography capacity in the South: a longitudinal assessment of supply and demand. Health Services Research, 49(1): 171-185. PMID: 23829179. [130] Kaseb AO, Shah N, Hassabo H, Morris JS, Xiao L, Abaza Y, Soliman K, Lee J, Vauthey J, Wallace M, Aloia T, Curley S, Abbruzzese J, and Hassan M (2014). Reassessing hepatocellular carcinoma staging in a changing patient population. Oncology, 86(2): 63-71. PMID: 24401634. [131] Davidian M, Lin X, Morris JS, and Stefanski LA, eds. (2014). The Work of Raymond R. Carroll – The Impact and Influence of a Statistician. Springer. [132] Kaseb AO, Xiao L, Hassan MM, Chae YK, Lee JS, Vauthey JN, Krishnan S, Cheung S, Hassabo HM, Aloia T, Conrad C, Curley SA, Vierling JM, Jalal P, Raghav K, Wallace M, Rashid A, Abbruzzese JL, Wolff RA, and Morris JS (2014). Development and validation of an IGF-1 score to assess hepatic reserve in hepatocellular carcinoma. Journal of the National Cancer Institute, 106(5). [133] Zuo X, Xu M, Yu J, Wu Y, Moussalli MJ, Manyam GC, Lee SI, Liang S, Morris JS, Broaddus R, Shureiqi I (2014). Potentiation of colon cancer susceptibility in mice by colonic epithelial PPAR-overexpression. Journal of the National Cancer Institute, 106(4). [134] Zhang L, Morris JS, Zhang J, Orlowski RZ, and Baladandayuthapani V (2014). Bayesian joint selection of genes and pathways: Applications in multiple myeloma genomics. Cancer Informatics, 13(S2), 113-123. [135] Liao H, Moschidis E, Riba-Garcia I, Zhang I, Unwin R, Morris JS, Graham J and Dowsey A (2014). A new paradigm for clinical biomarker discovery and screening with mass spectrometry based on biomedical image analysis principles. IEEE International Symposium on Biomedical Imaging. Beijing, China. eScholarID:219592 (refereed proceedings). [136] Jeter CB, Patel S, Morris JS, Butler I, and Sereno A (2015). Oculomotor Executive Function Abnormalities with Increased Tic Severity in Tourette Syndrome, The Journal of Child Psychology and Psychiatry, to appear.

[137] Kee BK, Morris JS, Slack RS, Crocenzi T, Wong L, Esparaz B, Overman M, Glover K, Jones D, Wen S, and Fisch MJ (2015). A phase II, randomized double-blind trial of calcium aluminosilcate clay versus placebo for the prevention of diarrhea in patients with metastatic colorectal cancer treated with irinotecan. Supportive Care in Cancer, to appear. [138] Morris JS. (2015). Functional regression. Annual Review of Statistics and its Application, 2, to appear. [139] Morris JS, Gutstein HG (2015). Detection and Quantification of Protein Spots by Pinnacle: Methods in Molecular Biology: 2D Gel Data Analysis, to appear. [140] Jennings EM, Morris JS, Manyam GC, Carroll RJ, and Baladandayuthapani V (2015). Bayesian models for flexible integrative analysis of multi-platform genomic data. Integrating Omics Data: Statistical and Computational Methods, George C. Tseng, Xianghong Jasmine Zhou, Debashis Ghosh, eds., to appear. [141] Fazio M, Grytz R, Morris JS, Bruno L, Girkin C, and Downs JC (2015). Scleral structural stiffness increases more rapidly with age in donors of African descent compared to donors of European descent. Investigative Ophthalmology & Visual Science, to appear. [142] Lynch P, Burke C, Phillips R, Morris JS, Wang X, Liu J, Slack R, Patterson S, Sinicrope F, Rodriguez-Bigas M, Half E, Bulow S, Latchford A, Hasson H, Richmond E, and Hawk E. (2015). An international randomized trial of celecoxib versus celecoxib plus difuoromethylomithine in patients with familial adenomatous polyposis. Gut, to appear. [143] Tchumtchoua S, Dunson D, and Morris JS (2015). Online variational Bayes inference for high-dimensional correlated data. JCGS, to appear. [144] Calin G, Tudor S, Giza D, Lin HY, Yoshiaki K, D’Abundo L, Toale K, Shimizu M, Ferracin M, Challagundla K, Cortez M, Fuentes-Mattei E, Tullbure D, Gonzalez C, Henderson J, Row M, Rice T, Ivan C, Negrini M, Fabbri M, Morris JS, Yeung SC, Vasilescu C, and Fabris L (2015). Cellular and Kaposi’s sarcoma-associated herpes virus microRNAs in sepsis and surgical trauma. Cell Death and Disease, to appear. [145] Lancia L, Rausch P, and Morris JS (2015). Automatic quantitative analysis of ultrasound tongue contours via wavelet-based functional mixed models. Journal of Acoustical Society of America, to appear. [146] Meyer MJ, Coull BA, Versace F, Cinciripini P, and Morris JS (2015). Bayesian function-on-function regression for multi-level functional data. Biometrics, to appear. [147] Chen ZY, Raghav K, Lieu C, Jiang ZQ, Eng C, Vauthey JN, Chang GJ, Qiao W, Morris JS, Hong D, Hoff P, Tran H, Heymach J, Overman M, and Kopetz S(2015). Cytokine profile and prognostic significance of high neutrophil-lymphocyte ratio in metastatic colorectal cancer. British Journal of Cancer, to appear.

Submitted Papers: [1] Morelli MP, Overman MJ, Dasari A, Kazmi SMA, Vilar E, Morris VK, Lee MS, Harron D, Eng C, Morris JS, Kee BK, Deaton FL, Garrett C, Diehl F, Angenendt P and Kopetz S: Heterogeneity of acquired KRAS and EGFR mutations in colorectal cancer patients treated with anti-EGFR monoclonal antibodies. [2] Figueiredo JC, Mott LA, Hamilton SR, Morris JS, Ahnen D, Barry E, …, and Baron JA: Protein expression patterns in colorectal adenomatous polyps and serrated lesions using tissue microarray analysis. 186

[3] Baladandayuthapani V, Abruzzo LV, Coombes KRC, and Morris JS: Bayesian adaptive spline-based functional regression with application to copy number data. [4] Zhang L, Baladandayuthapani V, Baggerly K, Czerniak B, and Morris JS. Functional CAR models for spatially correlated high-dimensional functional data. Under revision for JASA-TM. [5] Chen J, Chen JS, Zhang J, Phan L, Munoz NM, Katz LH, Farci P, Su X, Pandita TK, Zamboni F, Shetty K, Wu X, Rashid A, Mishra B, Shaw KR, Herlong F, Morris JS, and Mishra L: Genomic landscape of human liver cancer reveals TGF-B signaling signatures with prognostic significance. Submitted. [6] Hassan MM, Abdel-Wahab R, Kaseb A, Phan AT, El-Serag HB, Morris JS, Raghav KPS, Lee JS, Vauthey JN, Shalaby A, Torres H, Amos CI, and Li D. Significance of early adulthood obesity on risk and prognosis of hepatocellular carcinoma in the United States. Submitted. [7] Lee W and Morris JS. Identification of differentially methylated loci using wavelet-based functional mixed models. Submitted. [8] Guinney J, Dienstmann R, Wang X, de Reynies A, Schlicker A, Soneson C, Marisa L, Roepman P, Nyamundanda G, Angelino P, Bot BM, Morris JS, Simon I, Gerster S, Fessler E, de Sousa e Melo F, Missiaglia E, Ramay H, Barras D, Homicsko K, Maru D, Manyam GC, Broom B, Boige V, Laderas T, Salazar R, Gray JW, Tabernero J, Bernards R, Friend SH, Laurent-Puig P, Medema JP, Sadanandam A, Wessels L, Delorenzi M, Kopetz S, Vermeulen L, and Tejpar S. The consensus molecular subtypes of colorectal cancer. Submitted to Nature Genetics. [9] Kaseb AO, Xiao L, Hassan MM, Chae YK, Lee JS, Vauthey JN, Krishnan S, Cheung S, Hassabo HM, Aloia T, Conrad C, Curley SA, Vierling JM, Jalal P, Raghav K, Wallace M, Rashid A, Abbruzzese JL, Wolff RA, and Morris JS (2014). Reply to Shao et al. RE: Development and validation of an IGF-1 score to assess hepatic reserve in hepatocellular carcinoma. Submitted.

INSTRUCTION AND MENTORING Formal Teaching Experience: [1] High school teacher, Northside Christian School (1993-1995): taught high school mathematics and physics, coached basketball and golf, before returning to graduate school in Statistics. [2] Teaching Assistant, Texas A&M University (Fall 1995): served as grader for graduate level Statistics course. [3] Teaching Assistant/Instructor, Texas A&M University (Spring 1996, Summer 1996 x 2, Fall 1996, Spring 1997, Fall 1997): served as sole instructor for introductory undergraduate statistics courses (STAT301/STAT302) for non-mathematical majors, giving all lectures, preparing all homeworks and exams, and holding full office hours. [4] Assistant Lecturer, Texas A&M University (Spring 1998): served as sole instructor for undergraduate Statistics courses for engineering majors (STAT211), giving all lectures, preparing homeworks and exams, and holding full office hours.

Postdoctoral Researchers: [1] Andrew Dowsey (EPSRC Postdoctoral Fellowship), 2008-2010. (Reader, University of Liverpool) [2] Hongxiao Zhu, 2009-2011. (Assistant Professor, Virginia Tech University) [3] Lin Zhang (co-advise with Veera Baladandayuthapani), 2012-. [4] Wonyul Lee, 2013-. [5] Bruce Bugbee (co-advise with Veera Baladandayuthapani), 2014-

Students: [1] Jijun Xu, PhD, GSBS, Advisory Committee, 2004-2006. [2] Katherine Barker, PhD, GSBS, Advisory Committee, 2004-2009. [3] Michael Lecocke, PhD, Rice, Advisory Committee, 2003-2005. [4] Alena Ixmoscane Scott, PhD, Rice, Advisory Committee, 2004-2006. [5] Julie Beaver, MS, UT School of Public Health, Predoctoral Fellow, 2004. [6] Cameron Jeter, PhD, GSBS, Advisory Committee, 2008-2010. [7] Jens Johansson, PhD, University of Copenhagen, Mentor, 2009. [8] Changlu Liu, PhD, GSBS, Tutorial Mentor, 2009. [9] Pan Tong, PhD, GSBS, Supervisory Committee, 2009-2010. [10] Selina Vattithil, PhD, GSBS, Advisory Committee, 2010-2014. [11] Chunyan Cai, PhD, GSBS, Chair, Examination Committee, 2010. [12] Haiying Pang, PhD, GSBS, Examination Committee, 2010. [13] Casey Schultz, PhD, GSBS, Advisory Committee, 2010-2011. [14] Justin Wong, PhD, GSBS, Advisory Committee, 2012-present, Examination Committee, 2013 [15] Isaac Wun, PhD, GSBS, Advisory Committee, 2012-2014. [16] Samuel Fahrenholtz, PhD, GSBS, Examination Committee, 2012. [17] Elizabeth Jennings, PhD, Texas A&M, co-advisor (Ray Carroll, Veera B. 2012-present). [18] TJ Dai, PhD, GSBS, Tutorial Mentor, 2013. 187

[19] Chen Jiong, PhD, GSBS, Tutorial Mentor, 2013, Advisory Committee 2013-present, Examination Committee 2014. [20] Jialu Li, PhD, GSBS, Advisory Committee, 2013-present. [21] Zeya Wang, Rice University, co-advisor (Wenyi Wang), 2013-present. [22] Alexander Davis, PhD, GSBS, Tutorial Mentor, 2014; Advisory Committee 2014-present.

Invited Presentations and Seminars: I have presented 135 invited lectures, including the following: Mayo Clinic 2000 Iowa State University 2000 University of Michigan 2000 University of Florida 2000 University of New Mexico 2000 University of Chicago 2000 Duke University 2000 Fred Hutchinson Cancer Research Center 2000 North Carolina State University 2000 The University of Texas MD Anderson Cancer Center 2000 Rice University 2001 University College of London 2001 University of Kent, Canterbury UK 2001 Southern Methodist University 2001 Mississippi State University 2001 Texas A&M University 2001 Yale University 2002 Harvard University 2002 University of North Carolina 2002 Texas A&M University 2002 St. Cloud State University 2002 ENAR Spring Meeting 2002 7th Valencia International Meeting on Bayesian Statistics 2002 ENAR Spring Meeting 2003 WNAR Summer Meeting 2003 Joint Statistical Meetings 2003 Critical Assessment of Microarray Data Analysis 2003 Texas A&M University 2003 University of Texas, School of Public Health 2003 ENAR Spring Meeting 2004 ISBA World Meetings 2004 International Biometrics Conference 2004 Advancing Practice, Instruction, and Innovation through Informatics 2004 Rice University 2004 Texas A&M University 2004 Los Alamos National Laboratories 2004 University of Pennsylvania 2004 Harvard University 2004 ENAR Spring Meeting 2005 EMR Meeting of the IBS 2005 ICSA Applied Statistics Symposium 2005 WNAR Summer Meeting 2005 Joint Statistical Meetings 2005 Johns Hopkins University 2005 University of Texas, Dallas 2005 ICSA Applied Statistics Symposium 2006 International Workshop on Applied Probability 2006 Clinical Proteomics in Oncology Conference 2006 Joint Statistical Meetings 2006 University of Washington 2006 University of Minnesota 2006 International Indian Statistical Association Meeting 2007 ENAR Spring Meeting 2007 188

Current and Future Trends in Nonparametrics 2007 Institute for Pure and Applied Mathematics Workshop 2007 McGill University 2007 Columbia University 2007 Brown University 2007 National Institute of Allergy and Infections Diseases 2007 University of North Carolina 2007 North Carolina State University 2007 Georgetown University 2007 University of Michigan 2007 St. Mary’s University 2007 Wyeth, Functional Mixed Models Short Course 2008 ENAR Spring Meeting 2008 Statistical Theory and Methods for Complex, High-Dimensional Data 2008 SRCOS Summer research Conference 2008 WNAR Summer Meeting 2008 International Biometrics Conference 2008 ISBA World Meetings 2008 Prairie View A&M University 2008 Imperial College London 2008 Fred Hutchinson Cancer Research Center 2008 Texas A&M University 2008 Rice University 2008 University of Rochester 2008 WNAR Summer Meeting 2009 Joint Statistical Meetings 2009 International Statistical Institute Meetings 2009 University of South Carolina 2009 Kansas University Medical Center 2009 ENAR Spring Meeting 2010 University of Buffalo (Distinguished Scholars Lecture Series) 2010 SRCOS Meetings 2010 Hong Kong University 2010 Joint Biostatistics Symposium, China 2010 Joint Statistical Meetings 2010 North Carolina State University 2010 Duke University 2010 SAMSI Workshop on Longitudinal and Functional Data 2010 Messiah College 2011 Thomas Jefferson University 2011 University of Pennsylvania 2011 Emory University 2011 University of Georgia 2011 Universi ty of Missouri 2011 ENAR Spring Meeting 2011 High Dimensional Statistics: Advances and Challenges, Singapore 2011 Statistical Methods for Very Large Data Sets Conference, JHSPH 2011 SAMSI Analysis of Object Data Program Transition Workshop 2011 University of North Carolina 2011 Joint Statistical Meetings 2011 Myrto Lefkopoulou Distinguished Lecture, Harvard University 2011 Case Studies in Bayesian Statistics & Machine Learning, Carnegie-Mellon 2011 Texas A&M University 2011 North Carolina State University 2012 University of North Carolina 2012 Workshop on Bioinformatics, Biostatistics, & Biology of Nutrition/Cancer 2012 Interface 2012, Rice University 2012 ISBA World Meetings, Kyoto, Japan 2012 IMS-APRM 2012, Tsukuba, Japan 2012 Joint Statistical Meetings 2012 BASS Meetings, Savannah, GA 2012 189

MD Anderson Biostatistics Grand Rounds 2012 Young Investigator Workshop, ENAR Spring Meeting 2013 Conference of Texas Statisticians (COTs), Houston, TX 2013 Virginia Tech University, Blacksburg, VA 2013 High Dimensional Inference with Applications, Canterbury, UK 2013 Oxford University, Oxford, UK 2013 University of Manchester Biostatistics, Manchester, UK 2013 University of Manchester CADET, Manchester, UK 2013 University of Nottingham, Nottingham, UK 2013 European Meeting of Statisticians, Budapest, Hungary 2013 Joint Statistical Meetings, Montreal, Quebec 2013 University of Washington Statistics/Biostatistics, Seattle, WA 2013 Bayesian Biostatistics 7 Meeting, Houston, TX 2014 ENAR Spring Meeting, Baltimore, MD 2014 International Biometrics Conference, Florence, IT (selected contributed) 2014 ISBA World Meetings, Cancun, Mexico 2014 Joint Statistical Meetings, Boston, MA 2014 BASP Frontiers Workshop, Switzerland 2015 Duke University, Durham, NC 2015 University of Alabama, Birmingham, AL 2015 Michigan Imaging Workshop, Ann Arbor, MI 2015 BIRS Workshop on Frontiers in Functional Data Analysis, Banff 2015 Joint Statistical Meetings, Seattle WA 2015

PROFESSIONAL SERVICE Editorial Responsibilities: • Associate Editor, Biometrics (2006-2011) (handled 50 submissions). • Associate Editor, Journal of the Royal Statistical Society, Series B, (2006-2011) (47 papers). • Associate Editor, Annals of Applied Statistics (IMS), (2006-2015) (handled 74 submissions).

Journal Reviewer: I have reviewed over 100 journal articles, including articles in: Journal of the American Statistical Association, Journal of the Royal Statistical Society (Series B), Biometrics, Annals of Statistics, Annals of Applied Statistics, Statistical Science, Biostatistics, Technometrics, Journal of Computational and Graphical Statistics, Journal of the Royal Statistical Society (Series C), Journal of Statistical Planning and Inference, Statistics in Medicine, Journal of Agricultural, Biological, and Environmental Statistics, International Journal of Statistics, Bioinformatics, PLoS One, Proteomics, Proteins, BMC Bioinformatics, Current Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Medical Imaging, Genomic Signal Processing, Science Translational Medicine, New England Journal of Medicine, Journal of the National Cancer Institute, Cancer Informatics, Communications in Statistics, Journal of VLSI Signal Processing, Clinical Cancer Research, Neuropharmacology, Nucleic Acids Research, Molecular and Cellular Proteomics, Journal of Cellular and Molecular Medicine, Chemometrics and Intelligent Laboratory Systems, Journal of Microscopy, Physiological Genomics, Drug Information Journal, International Journal of Imaging Systems and Technology, International Journal of Molecular Science.

Conference Organizer: • Invited Session Organizer, ENAR 2002. • Invited Session Organizer, WNAR 2003. • Session Organizer, Conference of Texas Statisticians, 2003. • Invited Session Organizer, ENAR 2005. • Invited Session Organizer, WNAR 2005. • Topic Contributed Session Organizer, IBC 2006. • Program Chair, Biometrics Section of the American Statistical Association, ENAR 2006. • Invited Session Organizer, ENAR 2006. • Invited Session Organizer, JSM 2006. • Program Committee Member, ENAR 2007. • Invited Session Organizer, ENAR 2007. • Member, Organizing Committee, “Statistical Methods for Complex Data” 2009. • Invited Session Organizer, JSM 2009. • Program Co-chair, ENAR 2010. • IMS Invited Session Organizer, ENAR 2010.

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• Organizing Committee, “Bayesian Biostatistics” 2010. • Organizing Committee, SRCOS 2010. • Invited Session Organizer, SRCOS 2010. • Organizing Committee, “Bayesian Biostatistics” 2011. • Special Late Breaking Session Organizing Committee, ENAR 2011. • Topic Contributed Session Organizer, JSM 2012. • Organizing Committee: “Bayesian Biostatistics” 2012. • Organizing Committee: “Interface Conference”, Rice University, 2012. • Topic Contributed Session Organizer, JSM 2013. • Organizing Committee: “Bayesian Biostatistics” 2014. • Invited Session Organizer, IBC 2014. • Invited Session Organizer, Michigan Imaging Workshop 2015. • Organizing Committee “iBRIGHT Integrative Genomics and Personalized Medicine” 2015 • Program Chair, JSM 2016.

Other Professional Service: • ENAR Regional Committee, 2013-2015. • Member, Myrto Lefkopoulou Distinguished Lectureship Committee, 2012. • Secretary, ENAR, 2011-2012. • Council of Sections Representative, ASA Section on Nonparametric Statistics, 2010-2012. • Member, DSMB, Aggenix, 2011-2012. • H.O. Hartley Award Committee, Texas A&M University, 2010-. • Member, OSMB for NHLBI grant, 2005-2008. • NIH Study Section Member, R13 2009-2012, SBIR 2010, 2012. • Susan G. Komen for the Cure’s Targeted Therapies-5 Study Section, 2009. • Texas A&M Department of Statistics Alumni Board 2008-2013. • Student Paper Review Committee, ENAR 2005-2007, 2013. • Member of Regional Advisory Board, ENAR, 2004-2006. • Student Paper Review Committee, WNAR 2004.

Institutional Service (MD Anderson): • Institutional Tenure and Promotions Review Committee, 2014-present. • Deputy Chair, Department of Biostatistics, 2011-present. • Mentoring Coordinator, Department of Biostatistics, 2013-present. • Co-Director, Joint MDACC-Rice Biostatistics Program, 2011-present. • Director, Joint MDACC-TAMU Medical Statistics Program, 2011-present. • Graduate Education Committee, GSBS, 2012-2015. • Chair, Faculty Search Committee, 2012, 2015. • Member, Faculty Search Committee, Behavioral Science Statistics 2012. • Member, Faculty Search Committee, Bioinformatics 2014. • Member, Faculty Search Committee, Biostatistics 2011. • Faculty Achievement Awards Selection Committee, 2012. • Clinical Research Council, MD Anderson Cancer Center, 2009-2012. • Clinical Research Advisory Committee, 2011-present. • Internal Advisory Board, Multiple Myeloma P01, 2006-2012. • Internal Advisory Board, GU P01, 2009-2011. • Study Section Member, Internal Research Grants, 2005-2008. • Study Section Member, ACS Institutional Research Grants, 2008-2010. • Member, Faculty Compensation Committee, MD Anderson Cancer Center, 2006-2009. • Chair, Faculty Compensation Committee, MD Anderson Cancer Center, 2007-2009. • Faculty Senator, MD Anderson Cancer Center, 2006-2011. • Faculty Appeals Committee Member, MD Anderson Cancer Center, 2009-2012. • Mid-tenure Review Committees, Veera Baladandayuthapani (Chair, 2009), Paul Scheet (Chair, 2012), Michele Guindani (Chair, 2012), Wenyi Wang (Member, 2012), Han Liang (Member, 2013), Francesco Stingo (Chair, 2014)

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SCOTT D. GRIMSHAW Department of Statistics, Brigham Young University 219 TMCB, Provo, Utah 84602-6575 Voice: 801-422-6251 Email: [email protected]

EDUCATION: 1989 Ph.D., Statistics, Texas A&M University, College Station, TX Dissertation: A Unified Approach to Estimating Tail Behavior. Chairman: Emanuel Parzen

1985 M.S., Statistics, Texas A&M University, College Station, TX Thesis: Estimation of the Linear-Plateau Segmented Regression Model in the Presence of Measurement Error. Chairman: P. Fred Dahm

1983 B.S., Mathematics, Southern Utah State College, Cedar City, UT Magna Cum Laude

EXPERIENCE: 2004– Professor, Department of Statistics, Brigham Young University, Provo, UT. 2010– Statistician, BYU Broadcasting, Provo, UT. 1999-2004 Associate Professor, Department of Statistics, Brigham Young University, Provo, UT. 2001 Faculty Advisor, Washington Seminar, Brigham Young University, Provo, UT. 1999-2000 Visiting Research Analyst, Structured Transactions and Analytical Research, First Union Capital Markets, Charlotte, NC. 1993-99 Assistant Professor, Department of Statistics, Brigham Young University, Provo, UT. 1989-93 Assistant Professor (tenure track), Management Science and Statistics, College of Business and Management, University of Maryland, College Park, MD. 1987-89 Research Assistant, Department of Statistics, Texas A&M University, College Station, TX. 1985-86 Statistics Internship Program, Jointly Sponsored by the Applied Statistics Group, Engineering Department, E.I. du Pont de Nemours & Co. (Inc.), Wilmington, DE and the Department of Statistics, Texas A&M University, College Station, TX.

HONORS & AWARDS: • 2007 BYU Statistics Faculty Fellowship. • 2005 H.O. Hartley Award, for Distinguished Service to the Discipline of Statistics by a Former Student of the Texas A&M Statistics Department. • 2005 BYU Statistics Chair’s Outstanding Paper Award. • 2005 BYU Statistics Teacher of the Year. • 2003 BYU Statistics Chair’s Outstanding Paper Award. • 2001 Frank Wilcoxon Prize for the Best Practical Application Paper in Technometrics. • 1997 Best Contributed Paper in Statistics, Data Analysis, and Modeling Section, Twenty- Second Annual SAS Users Group International Conference. • 1987 W.S. Connor Memorial Award, Outstanding Ph.D. candidate, Department of Statis- tics, Texas A&M University.

SERVICE TO SPONSORING INSTITUTION • 2014–2015 Faculty Advisory Council, College of Physical and Mathematical Sciences Representative. • 2014–15, Teaching Committee • 2013 Mathematical Sciences Committee Evaluating ENGL 316, College of Physical and Mathematical Sciences. • 2012 Modeling Donor Affinity to BYU Colleges and Units, LDS Philanthropy. • 2012 Impact of PBS Host Event on Preschool Reading, KBYU Eleven. • 2010–12 Teaching and Learning Committee Chair, Department of Statistics. • 2008–12 Rank and Status Committee, Department of Statistics. • 2006–10 Associate Chair, Department of Statistics. Responsible forfaculty teaching assignments, program learning outcomes and assessment that led to a new curriculum that satisfies ASA Undergraduate Statistics Guidelines. • 2006–10 Graduate Coordinator, Department of Statistics. Changed the graduate culture from one were 60% of students took longer than the stated 2 years to graduate. Since Fall 2006 all admitted students complete degree in 2 years or less. Worked with students who had left the

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program to complete project or thesis and graduate (last two graduated April 2008). Grew the BS/MS Statistics Integrated program as the department’s flagship undergraduate experience. • 2008–10 Resources Subcommittee of Department Teaching and Learning Committee, Department of Statistics. • 2008 Spring Research Conference Organizing Committee, College of Physical and Mathematical Sciences. • 2007 Rank and Status Committee, College of Physical and Mathematical Sciences. • 2005–07 University Academic Unit Review Committee. • 2006 Summer Institute of Applied Statistics Organizer, R. Todd Ogden, “Essential Wavelets for Statistical Applications and Data Analysis.” • 2005 Search Committee Chair, Department of Statistics. • 2002–03 Search Committee, Department of Statistics. • 2002–04 Five-year Plan Committee, Department of Statistics. • 2001–03 Scholarship and Awards Committee Chair, Department of Statistics. • 2001 Faculty Advisor, Washington Seminar. Supervised 31 BYU students that arrived in Washington, DC two weeks before the September 11 terrorist attack on the Pentagon. Those events changed the student needs, many internship assignments, and some of the Washington Seminar program. One highlight was a debriefing by the Honorable Robert Bennett, Senator (R-UT), the day Congress recessed after the October anthrax letters were delivered to the Senate majority leader’s office. • 2000 Co-Advisor of 2000 Utah Colleges Exit Poll, Departments of Statistics and Political Science. One of four faculty advisors who mentored undergraduate statistics and political science students to perform the ambitious sampling class project of a Utah statewide exit poll. The students are organized into a virtual polling firm and committed over 2,500 man-hours to sample polling places throughout the state by training over 500 student pollsters from BYU and other Utah colleges and universities. • 1999 Summer Institute of Applied Statistics Organizer, Raymond J. Carroll and David Ruppert, “Measurement Error Models.” • 1999 MS Comprehensive Exam Committee, Department of Statistics • 1998–99 Curriculum Committee, Department of Statistics • 1998 Summer Institute of Applied Statistics Organizer, Bradley P. Carlin, “Bayes and Empirical Bayes for Data Analysis.” • 1995 Electronic Classroom Evaluation and Review Task Force Chair, Assistant Aca- demic Vice-President, Computing. • 1995 Analysis of Time to Graduation at BYU (Alumni 1980–1994), Assistant Aca- demic Vice-President, Computing. • 1993– Business Emphasis Advisor, Department of Statistics.

SERVICE TO THE PROFESSION • 2013–14 ASA Presidential Initiative: Committee to Revise the Curriculum Guidelines for Undergraduate Majors and Minors in Statistics, Chair: Nicholas J. Horton, Amherst College. • 2013–14 Past-President, Utah Chapter of the American Statistical Association. • 2012–14 Associate Editor, Reviews in Journal of the American Statistical Association, and The American Statistician. • 2008– Texas A&M Statistics Alumni Advisory Board • 1990– Referee, JASA, Technometrics, JQT, TAS, JCGS, Communications in Statis- tics, JSPI, JQAS • 2012–13 President, Utah Chapter of the American Statistical Association. • 2006–12 Associate Editor, Computational Statistics • 2011–12 First Vice President, Utah Chapter of the American Statistical Association. • 2011 SPES Fall Technical Conference Program Committee Chair • 2010 SPES Fall Technical Conference Program Committee Representative • 2007–09 H.O. Hartley Award Selection Committee, Texas A&M Statistics Department. • 2007 Local Area Committee Chair, Joint Statistics Meeting, Salt Lake City, UT. • 2005 Contributed Program Chair, Spring Research Conference on Statistics in In- dustry, Park City, UT. • 2003 Invited Session Organizer, “Financial Risk and Fraud Detection,” Interface 2003, Salt Lake City, UT. • 1998 Invited Session Organizer, “Utilizing Large Industrial Data Sets for Product and Process Quality Improvement,” Joint Statistics Meetings, Dallas, TX. • 1997 Special Contributed Paper Session Organizer, “Batch Process Monitoring Us- ing SPC,” Joint Statistics Meetings, Anaheim, CA. • 1996 Invited Session Organizer, “Tree-based Models,” Joint Statistics Meeting, Chicago, IL. • 1995–97 Treasurer, Utah Chapter of the American Statistical Association. • 1994–95 Second Vice President, Utah Chapter of the American Statistical Association.

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• 1987–89 Treasurer, Southeast Texas Chapter of the American Statistical Association.

PUBLICATIONS: Refereed: 1. Grimshaw, Scott D., and Burwell, Scott J. (2014). “Choosing the Most Popular NFL Games in a Local TV Market.” Journal of the Quantitative Analysis of Sport, 10, 329–343. 2. American Statistical Association Undergraduate Guidelines Workgroup (2014). “2014 Cur- riculum Guidelines for Undergraduate Programs in Statistical Science.” Alexandria, VA: American Statistical Association. http://www.amstat.org/education/curriculumguidelines.cfm Members: Beth Chance, Steve Cohen, Scott Grimshaw, Johanna Hardin, Tim Hester- berg, Roger Hoerl, Nicholas Horton (chair), Chris Malone, Rebecca Nichols, Deborah Nolan. 3. Grimshaw, Scott D., Sabin, R. Paul, and Willes, Keith M. (2013). “Analysis of the NCAA Men’s Final Four TV audience.” Journal of the Quantitative Analysis of Sport, 9,115–126. 4. Grimshaw, Scott D., Blades, Natalie J., and Miles, Michael P. (2013). “Spatial Control Charts for the Mean.” Journal of Quality Technology, 45, 130–148. 5. Wilde, Sarah L., and Grimshaw, Scott D. (2013). “Efficient Computation of Generalized Median Estimators.” Computational Statistics, 28, 307–317. 6. Dahlin, Eric C., Strong, A. Brent, and Grimshaw, Scott D. (2012). “Combining Creativity and Civilization: A Natural Experiment in a General Education Course.” International Journal of Instructional Technology and Distance Learning, 9, 33–41. 7. Grimshaw, Scott D. and Alexander, William P. (2011). “Markov Chain Models for Delin- quency: Transition Matrix Estimation and Forecasts.” Applied Stochastic Models in Business and Industry, 27, 267–279. 8. Cornia, Gary C., Nelson, Ray D., Walter, Lawrence C., and Grimshaw, Scott D. (2010). “The Effect of Local Option Sales Taxes on Local Sales.” Public Finance Review, 38, 659–681. 9. Blades, Natalie J., Grimshaw, Scott D., and Pendleton, Carly R. (2010). “A Simulation- Based Approach to Evaluating Microarray Analyses.” Biostatistics, 11, 533–536. 10. Eddleman, James L., Sorber, Samual C., Morris, Thomas H., Grimshaw, Scott D., Dastrup, Emily, Christensen, William F., Morris, Scott L. (2007). “Analysis of Fremont River strath terraces in the area of the Capitol Reef National Park, Utah–Implications for fluvial landscape evolution and the role of climate forcing.” Central Utah– Diverse Geology of a Dynamic Landscape, G.C. Willis, M.D. Hylland, D.L. Clark and T.C. Chidsey, Jr. (eds.). Utah Geological Association, Salt Lake City, UT. 11. Grimshaw, Scott D., McDonald, James B., McQueen, Grant R. and Thorley, Steven R. (2005). “Testing for Duration Dependence with Discrete Data.” Communications in Statistics: Simulation and Computation, 34, 451- 464. 12. Grimshaw, Scott D., Christensen, Howard B., Magleby, David B. and Patterson, Kelly D. (2004). “The Utah Colleges Exit Poll: Learning by Doing.” Chance, 17, 32-38. 13. Alexander, William P., Grimshaw, Scott D., McQueen, Grant R., and Slade, Barrett A. (2002). “Some Loans Are More Equal than Others: Third-Party Originations and Defaults in the Subprime Mortgage Industry.” Real Estate Economics, 30, 667–697. 14. Grimshaw, Scott D., Collings, Bruce J., Larsen, Wayne A., and Hurt, Carolyn (2001). “Eliciting Factor Importance in a Designed Experiment.” Technometrics, 43, 133-146. (2001 Wilcoxon Prize) 15. Grimshaw, Scott D., Whiting, David G., and Morris, Thomas H. (2001). “Likelihood Ratio Tests for a Mixture of Two von Mises Distributions.” Biometrics, 57, 260-265. 16. Hilton, Sterling C., Grimshaw, Scott D., and Anderson, Genan T. (2001). “Statistics in Preschool.” The American Statistician, 55, 332–336. 17. Grimshaw, Scott D., Bryce, G. Rex and Meade, David J. (2000). “Control Limits for Group Charts.” Quality Engineering, 12, 177-184. 18. Grimshaw, Scott D., Shellman, Scott D., and Hurwitz, Arnon M. (1998). “Real-Time Process Monitoring for Changing Inputs.” Technometrics, 40, 283–296. 19. Grimshaw, Scott D. (1998). “Treed Regression.” In Encyclopedia of Statistical Sciences Update, vol. 2, Samuel Kotz, Compbell B. Read, and David L. Banks (eds.), 677–679. Wiley, New York. 20. Lawson, John L., Grimshaw, Scott D., and Burt, Jason (1998). “A Quantitative Method for Identifying Active Contrasts in Unreplicated Factorial Designs Based on the Half- Normal Plot.” Computational Statistics and Data Analysis, 26, 425–436. 21. Grimshaw, Scott D. and Alt, Frank B. (1997). “Control Charts for Quantile Function Values.” Journal of Quality Technology, 29, 1–7. 22. Alexander, William P. and Grimshaw, Scott D. (1996). “Treed Regression.” The Journal of Computational and Graphical Statistics, 5, 156–175.

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23. Morris, Thomas H., Richmond, Dean R. and Grimshaw, Scott D. (1996). “Orientation of Dinosaur Bones in Riverine Environments: Insights into Sedimentary Dynamics and Taphonomy.” The Continental Jurassic, Michael Morales (ed.), 60, 521–530. Museum of Northern Arizona, Flagstaff, AZ. 24. Grimshaw, Scott D. (1993). “Investigating the Bias and MSE of Exceedance Based Tail Estimators for the Cauchy Distribution.” In Proceedings of the Conference on Extreme Value Theory and Applications, vol. 3, 139–147. NIST Special Publication 860. 25. Grimshaw, Scott D. (1993). “Computing Maximum Likelihood Estimates for the General- ized Pareto Distribution.” Technometrics, 35, 185–191. 26. Jain, Kamlesh, Alt, Frank B. and Grimshaw, Scott D. (1993). “Multivariate Quality Con- trol – A Bayesian Approach.” In ASQC Quality Congress Transactions, 645–651. American Society of Quality Control. 27. Grimshaw, Scott D. (1992). “Estimation of the Linear-plateau Segmented Regression Model in the Presence of Measurement Error.” Communications in Statistics: Theory and Methods, 21(8), 2399-2413. 28. Grimshaw, Scott D. (1990). “A Unification of Tail Estimators.” Communications in Statis- tics: Theory and Methods, 19(12), 4841-4857.

Non-Refereed: 1. Alt, Francis B. and Grimshaw, Scott D. (2013). “Quality Control,” in Encyclopedia of Operations Research & Management Science 3rd ed., Gass, Saul I. and Fu, Michael C. (eds.). Springer, NY. 2. Alt, Francis B. and Grimshaw, Scott D. (2013). “Multivariate Quality Control,” in Ency- clopedia of Operations Research & Management Science 3rd ed., Gass, Saul I. and Fu, Michael C. (eds.). Springer, NY. 3. Blades, Natalie J., Grimshaw, Scott D., and Scott, Del T. (2011). “Learning Outcomes for Undergraduate Statistics Programs.” BYU Statistics Department Technical Report. 4. Grimshaw, Scott D. (2004). “Preschool Statistics.” The Statistics Teacher Network. Fall 2004. 5. Grimshaw, Scott D. and Fellingham, Gilbert W. (1998). “Statistical Development Using SAS / TOOLKIT Software.” In Proceedings of the Twenty-Third Annual SAS Users Group International Conference, 1374–1377. SAS Institute, Inc., Cary, NC. 6. Nelson, Todd R. and Grimshaw, Scott D. (1997). “SAS Interface for Run-to-Run Batch Process Monitoring Using Real-Time Data.” In Proceedings of the Twenty-Second Annual SAS Users Group International Conference, 1215–1219. SAS Institute, Inc., Cary, NC. (Best Contributed Paper) 7. Grimshaw, Scott D. (1995). Book Review of “An Introduction to the Bootstrap,” by Bradley Efron and Robert J. Tibshirani, Technometrics, 37, 341. 8. Grimshaw, Scott D. and Alexander, William P. (1994). “Computational Efficiency in Treed Regression Using the QR Decomposition,” BYU Statistics Department Technical Re- port. 9. Grimshaw, Scott D. (1991). “Calculating Maximum Likelihood Estimators for the Gen- eralized Pareto Distribution.” In Computing Science and Statistics: Proceedings of the 23rd Symposium on the Interface, Elaine M. Deramidas, ed., 616–619. Interface Foundation of North America. Fairfax Station, VA.

CURRENT RESEARCH INTERESTS: Audience Measurement and Analytics; Control Charts; Data Mining; Statistical Computing.

Work In Progress: • Jensen, Willis A., Espen, Ben, and Grimshaw, Scott D. “Nonlinear Profile Monitoring for Oven Temperature Data.” Revise and Resumit to Journal of Quality Technology. • Grimshaw, Scott D. “Incorporating Authentic Data Experiences Within Statistics Major Courses.” Under Review to the American Statistician.

FUNDED RESEARCH: • 2014–15 (not funded, submitted 2014). BYU Broadcasting. “TV Audience Analytics and Market Research.” $24,000. • 2014–15 (not funded, submitted 2014). National Institutes of Health. “Anthropome- try of Passive Wrist and Forearm Stiffness.” $135,552. (P.I. with Steven K. Charles). • 2013–14 BYU Broadcasting. “TV Audience Analytics and Market Research.” $18,000. • 2013 (not funded, submitted 2013). Utah Valley University. “Philanthropic Wealth Screening and Predictive Modeling.” $120,904. • 2012 (not funded, submitted 2012). State of Utah, Administrative Office of the Courts. “Public Trust and Confidence Survey.” $80,607. (P.I. with William F. Christensen). • 2010–13 BYU Broadcasting. “Audience Measurement and Analytics.” $84,000. • 2010-11 BYU Marriott School of Management (Gary C. Cornia). “Measuring the Im- pact of Wal-Mart Coming to Sanpete County.” $12,000.

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• 2009–11 (not funded, submitted 2009). National Science Foundation. “Focus on Fresh- men: Growing Undergraduate Statistics Education.” $198,328. (P.I. with Natalie J. Blades and Del T. Scott). • 2001–02 Manufactured Housing Division, Conseco Finance. “Dynamic Delinquency Movement.” $25,000. Conseco Finance, Inc., St. Paul, MN. • 1998–99 DuPont Education Aid Program Unrestricted Grant. “Experimental Design & Empirical Modeling.” $20,000. DuPont, Inc., Wilmington, DE. • 1997–98 DuPont Education Aid Program Unrestricted Grant. “Experimental Design & Empirical Modeling.” $20,000. DuPont, Inc., Wilmington, DE. • 1996–97 SEMATECH Sponsored Research Program No. 36082500-OP. “Methods for Modeling Real-time Data from Inputs & Initial Conditions for use in the Real-time Process Monitor.” $17,500. SEMATECH, Inc., Austin, TX. • 1996–97 NBC Program Research, “Model Consistent Bias in Telephone Surveys that Gauge the Strength of Programming Relative to Competition,” $15,000. NBC, Burbank, CA. • 1995-96 SEMATECH Sponsored Research Program No. 75008932. “Development of Real-time Control Methods: Real-time Process Monitor.” $17,020. SEMAT- ECH, Inc., Austin, TX. • 1992 Office of Facilities Engineering, Fort Meade. “Measurement for Quality Im- provement for L-5 Managers.” $3,500. Fort Meade, MD. • 1990 Systems and Technology, Westinghouse. “Radar Processing Enhancement.” $5,000. With Frank B. Alt. Westinghouse Electric, Corp., Baltimore, MD. • 1990 General Research Board of Graduate Studies and Research Summer Research Award. “Tail Behavior Parameters Estimated from the Sample Quantile Process.” $5,200. University of Maryland, College Park, MD.

PRESENTATIONS: 1. Invited, “Control Charts for Spatial Data,” INFORMS 2014, San Francisco, CA, October 2014. 2. “Choosing Most Popular NFL Games in a Local TV Market,” 2014 Joint Statistics Meetings, Boston, MA, August 2014. 3. “Final Four TV Audience,” Fall 2012 Utah ASA Chapter Meeting, Salt Lake City, UT, December 2012. 4. “Control Charts for Spatial Data,” 2012 Joint Statistics Meetings, San Diego, CA, August 2012. 5. “Efficient Computation of Generalized Median Estimators,” Statistics Department Seminar, Brigham Young University, January 2011. 6. “Learning Outcomes and Assessment for Undergraduate Statistics Programs,” 2010 Joint Statistics Meetings, Vancouver, BC, August 2010. “Control Charts for Spatial Data,” Virginia Tech, April 2009. 7. Invited Paper, “Control Charts for Spatial Data,” 2008 Fall Technical Conference, Phoenix, AZ, October 2008. 8. “Control Charts for Spatial Data,” Spring Research Conference for Industry & Technology, Atlanta, GA, May 2008. 9. Invited Poster, “Markov Chain Models for Delinquency: Transition Matrix Estimation and Forecasts,” 2003 Joint Statistics Meetings, San Francisco, CA, August 2003. 10. Invited Paper, “Some Loans Are More Equal than Others: Third-Party Originations and Defaults in the Subprime Mortgage Industry,” Interface ’03, Salt Lake City, UT, March 2003. 11. “Ancient Rivers, Dinosaur Bones, and Directional Data,” Brigham Young University — Idaho, October 2002. 12. “The Utah Colleges Exit Poll: Learning by Doing,” 2002 Joint Statistics Meetings, New York, NY, August 2002. 13. “Ancient Rivers, Dinosaur Bones, and Directional Data,” Statistics Department Seminar, Brigham Young University, February 2002. 14. Invited Technometrics Session, “Eliciting Factor Importance in a Designed Experiment,” Spring Research Conference on Statistics in Industry and Technology, Roanoke, VA, June 2001. 15. “Eliciting Factor Importance in a Designed Experiment,” Utah Chapter of the American Statistican Association, Salt Lake City, UT, February 2001. 16. “Accuracy of 2000 Utah Colleges Exit Poll Predictions,” Math Department, Southern Utah University, Cedar City, UT, December 2000. 17. “The Seven and a Half Laws of Statistical and Financial Success,” Statistics Department Seminar, Brigham Young University, September 2000. 18. “Dynamic Delinquency Movement Matrix Loss Forecasting,” Delaware Chapter of the American Statistical Association Annual Conference, April 2000. 19. “Dynamic Delinquency Movement Matrix Loss Forecasting,” College of Business and Man- agement, University of Maryland, College Park, MD, April 2000. 20. “Regression Trees,” Structured Transactions and Analytical Research, First Union Capital Markets, Charlotte, NC, November 1999. 21. “Regression Trees,” Department of Statistics Colloquium, University of South Carolina, Columbia, SC, October 1999.

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22. “Process Improvement Using Real-time Data,” Spring Research Conference on Statistics in Industry and Technology, Minneapolis, MN, June 1999. 23. “Process Improvement Using Real-time Data,” DuPont Experimental Design and Empirical Modeling Conference, Wilmington, DE, March 1999. 24. Invited Seminar, “Eliciting Factor Importance in a Designed Experiment,” Institute for Improvement in Quality and Productivity, University of Waterloo, October 1998. 25. Invited Discussant, “Utilizing Large Industrial Data Sets for Product and Process Quality Improvement,” 1998 Joint Statistics Meetings, Dallas, TX, August 1998. 26. “Prior Elicitation for Bayesian Analysis of Screening Designs,” Faculty Enrichment Seminar, Statistics Department, Brigham Young University, June 1998. 27. “Examples of Prediction Using Stacked Treed Regressions,” Interface ’98, Minneapolis, MN, May 1998. 28. “Prior Elicitation for Bayesian Analysis of Screening Designs,” DuPont Quality Manage- ment & Technology Center, Wilmington, DE, May 1998. 29. “Statistical Development Using SAS/TOOLKIT Software,” with Gilbert W. Fellingham, Twenty-Third Annual SAS Users Group International Conference, Nashville, TN, March 1998. 30. Special Contributed Paper, “Run-to-Run Batch Process Monitoring Using Real-Time Data,” 1997 Joint Statistics Meetings, Anaheim, CA, August 1997. 31. “SAS Interface for Run-to-Run Batch Process Monitoring Using Real-Time Data,” with Todd R. Nelson, Twenty- Second Annual SAS Users Group International Conference, San Diego, CA, March 1997. 32. “Treed Regression,” Mathematics & Statistics Department Seminar, Utah State University, February 1997. 33. “Treed Regression,” Statistics Department Seminar, Texas A&M University, February 1997. 34. “RTPM-PRO Performance on Fault Detection and Classification Benchmarking Data,” SEMATECH, Austin, TX, February 1997. 35. Invited Paper, “Regression Trees,” 1996 Joint Statistical Meetings, Chicago, IL, August 1996. 36. “Introduction to Quality Improvement & STAT 361,” AICHE Meeting, Brigham Young University, November 1995. 37. “Imposing Monotonicity in Treed Regression,” 1995 Joint Statistics Meetings, Orlando, FL, August 1995. 38. “The Bootstrap: a tutorial,” Statistics Department Seminar, Brigham Young University, November 1994. 39. “Treed Regression,” 1994 Joint Statistics Meetings, Toronto, CA, August 1994. 40. “Tail Estimation,” Statistics Department Seminar, Brigham Young University, October 1993. 41. “Quantile-based Control Charts,” Statistics Department Seminar, Brigham Young University, December 1992. 42. “An EWMA Using the Sample Generalized Variance for Monitoring a Multivariate Normal Process,” Quality Assurance in the Government, Washington, DC, July 1992. 43. “Calculating Maximum Likelihood Estimators for the Generalized Pareto Distribution,” 23rd Symposium on the Interface between Computing Science and Statistics, Seattle, WA, April 1991.

STUDENTS SUPERVISED Year Student Role 1992 Fawzi Abdul-Wahab Chair (Ph.D. U. Maryland–College Park) “Optimal Quantile Based Control Charts for Location-Scale Alternatives” 1993 Kamlesh Jain Chair (Ph.D. U. Maryland–College Park) “A Bayesian Approach to Multivariate Quality Control” 1995 Shane Reese (MS BYU) Chair 1996 Scott Shellman (MS BYU) Chair 1996 Courtney Black (MS BYU) Chair 1996 Greg Jones (MS BYU) Member 1996 Xiaoying Xiao (MS BYU) Member 1996 Todd Nelson (BS BYU) Mentor 1997 Todd Nelson (MS BYU) Chair 1997 Matthew Johnson (MS BYU) Member 1997 David Dahl (BS BYU) Mentor 1998 Chris Peterson (MS BYU) Chair 1998 David Dahl (MS BYU) Chair 1998 Carolyn Hurt (MS BYU) Member 1998 Jared Christensen (BS BYU) Mentor (Undergraduate Award Recipient) 1999 Mike George (MS BYU) Chair 1999 Rachelle Wilkinson (MS BYU) Member 1999 Jamis Perrett (MS BYU) Member 1999 Mike Richmond (MS BYU) Member 2000 Stephanie Stanworth (MS BYU) Chair 197

2000 Alexis Merrill (Exit Poll) Mentor 2000 Betsy Lundy (Exit Poll) Mentor 2000 Jeff Larsen (BS BYU) Mentor 2000 Jana Sheppard (BS BYU) Mentor 2000 Aimee Wahle (BS BYU) Mentor 2000 Alvin Van Orden (BS BYU) Mentor 2000 Melaney Slater (BS BYU) Mentor 2000 Marcie Fillmore (BS BYU) Mentor 2001 Hripsime Bandourian (MS BYU) Chair 2001 Saule Ahoshina (MS BYU) Member 2002 Kenton Wride (MS BYU) Chair 2002 Alexis Merrill (MS BYU) Member 2003 Sherstin Merx (BS BYU) Mentor 2003 Jerry Butler (BS BYU) Mentor 2003 Mark Lyman (BS BYU) Mentor 2004 Nicole Smith (MS BYU) Member 2004 Chris Green (MS BYU) Member 2004 Betsy Lundy (MS BYU) Member 2005 Emily Dastrup (MS BYU) Chair 2005 Mandy Woolstenhulme Member (Ph.D. Exercise Science BYU) 2005 James Eddleman (MS Geology BYU) Member 2006 Michael Smith (MS BYU) Chair 2006 Ross Larsen (MS BYU) Member 2006 Stephen Manortey (MS BYU) Member 2006 Clint Stevenson (MS BYU) Member John Ward (DNF) Chair 2007 Rebecca Monson Richardson (MS BYU) Chair 2007 April Logan (MS BYU) Member 2007 Carly Pendleton (MS BYU) Member 2007 Wendy Bunn (MS BYU) Member 2007 Trenton Pulsipher (MS BYU) Member 2007 Mark Lyman (MS BYU) Member 2007 Natalie Johnson (MS BYU) Member 2007 Kassie Fronczyk (MS BYU) Member 2007 Matt Heaton (MS BYU) Member 2007 Jared Collings (MS BYU) Member 2007 Andrew Stacey (MS BYU) Member 2007 Paul Johnson (MS BYU) Member 2008 Emily Bell (MS BYU) Member 2008 Scott Howard (MS BYU) Chair 2008 Todd Remund (MS BYU) Member 2008 Greg Johnson (MS BYU) Member 2008 Tom Stewart (MS BYU) Member 2008 Jonathan Liljegren (MAcc BYU) Master’s Minor Member 2008 Zijun Dozier (MS Mathematics BYU) Master’s Minor Member 2008 Ben Hudson (MS Technology BYU) Member 2008 Tomo Funai (BS BYU) Mentor 2008 Angela Nelson (BS BYU) Mentor 2008 Jared Geurts (BS BYU) Mentor 2008 Claire Barker (BS BYU) Mentor 2009 Brenda Ginos (MS BYU) Chair 2009 Claire Owen (MS BYU) Member 2009 Andrea Thomas (MS BYU) Member 2009 Mike Ulrich (MS BYU) Member 2009 Enkhmart Dudleenamjil Member (PhD Microbiology BYU) 2009 Scott Morris (BS BYU) Mentor 2009 Sarah Clark (BS BYU) IMPACT Mentor 2009 Rachel Teh (BS BYU) IMPACT Mentor 2010 James Hattaway (MS BYU) Chair 198

2010 Erika Hernandez (MS BYU) Member 2010 Tommy Leininger (BS/MS BYU) Member 2010 Sarah Wilde (BS BYU) IMPACT Mentor 2010 Rachel Teh (BS BYU) IMPACT Mentor 2011 Angela Nelson (BS/MS BYU) Chair 2012 Sarah Victors (MS BYU) Chair 2014 Paul Sabin (BS/MS BYU) Chair 2014 Andrew Brock (MS BYU) Chair

COURSES TAUGHT AT BRIGHAM YOUNG UNIVERSITY Graduate Courses • Stat 535: Applied Linear Models. (1 time, last taught Fall 2013) • Stat 536: Modern Regression Methods. (8 times, last taught Winter 2013) Stat 624: Statistical Computation. (2 times, last taught Fall 2008) • Stat 525: Statistical Inference. (1 time, last taught Fall 1998) Stat 536: Regression Analysis. (3 times, last taught Fall 1997) Majors Courses • Stat 340: Introduction to Regression. (1 time, last taught Fall 2014) • Stat 435: Nonparametric Statistical Methods. (4 times, last taught Fall 2014) Stat 340: Inference. (1 time, last taught Winter 2014) • Stat 290: Communication of Statistical Results. (5 times, last taught Winter 2013) Stat 462: Quality Control & Industrial Statistics. (5 times, last taught Winter 2007) Stat 336: Statistical Methods I. (10 times, last taught Winter 2005) • Stat 469: Applied Time Series & Forecasting. (5 times, last taught Fall 2005) Stat 334: Methods of Survey Sampling. (2 times, last taught Winter 2001) • Stat 421: Probability and Distribution Theory. (2 times, last taught Winter 1997)

Undergraduate Service Courses • Stat 121: Principles of Statistics. (1 time, last taught Fall 2013) • Stat 201: Statistics for Engineers and Scientists. (4 times, last taught Fall 2013) Stat 332: Quality Improvement for Industry. (4 times, last taught Summer 2010) Stat 361: Quality Improvement for Industry. (5 times, last taught Spring 2003) Stat 221/222: Principles of Statistics. (7 times, last taught Winter 1999) • Stat 321: Elements of Mathematical Statistics. (2 times, last taught Winter 1993)

Graduate Service Courses • Stat 510: Introduction to Statistics for Graduate Students. (1 time, last taught Winter 2008) • Stat 512: Statistical Methods for Research 2. (2 times, last taught Winter 2003) Stat 532: Quality Improvement for Engineering. (1 time, last taught Winter 1998)

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APPENDIX J.

Faculty Postdoctoral Researchers, 2009-2014

Carroll, Raymond Assaad, Houssein (Research Assistant Professor, STATA Corporation) Bhadra, Anindya (Assistant Professor, Purdue University) Bliznyuk, Nikolay (Assistant Professor, University of Florida) Garcia, Tanya (Assistant Professor, Texas A&M School of Public Health) Hernandez-Magallanes, Irma (Postdoctoral Research Associate, Texas A&M Department of Statistics) Joseph, Maria (Senior Statistician, General Dynamics Information Technology) Kaprievitch, Yuliya (Lecturer, University of Tasmania) Lee, Myoungji (Manager, Enterprise Model Validation Group, American Express) Li, Haocheng (Affiliation Unknown) Martinez, Josue (Affiliation Unknown) Potgieter, Cornelius (Assistant Professor, University of Johannesburg) Ryu, Duchwan (Assistant Professor, Northern Illinois University) Maadooliat, Mehdi (Assistant Professor, Marquette University) McLean Mathew (Research Assistant Professor, Texas A&M Department of Statistics) Mohsenizadeh, Daniel (Research Assistant Professor, Texas A&M Electrical & Computer Engineering) Murphy, Mary (Affiliation Unknown) Tekwe, Carmen (Assistant Professor, Texas A&M School of Public Health) Wei, Jiawei (Statistical Methodologist, Novartis) Xu, Ganggang (Assistant Professor, Binghamton University) Zhang, Xinyu (Affiliation Unknown) Zoh, Roger (Research Assistant Professor, Texas A&M School of Public Health) Zollanvari, Amin (Assistant Professor, Electronic Engineering Istanbul Kemerburgaz University) Zorych, Ivan (Columbia University)

IAMCS/KAUST (Raymond Carroll) Copeland, Dylan (Research Scientist at Global Geophysical Services) Jin, Bangti (Assistant Professor, University of California, Riverside) Li, Xiangfang (Assistant Professor, Prairie View A&M University) McClarren, Ryan (Assistant Professor, Texas A&M Nuclear Engineering) Oancea, Cosmin (Assistant Professor, University of Copenhagen) Qian, Xiaoning (Assistant Professor, University of South Florida) Pauletti, Miguel S. (Affiliation Unknown) Schwartz, Scott (Research Associate, University of Texas, Austin) Simeonova, Lyubima (Process Control Engineer, IM Flash Technologies) Steinhauer, Dustin (Instructional Assistant Professor, Texas A&M Mathematics) Wang, Jue (Senior Research Scientist, Adobe Research) Wang, Xueying (Assistant Professor, Washington State University) Zedler, Sarah (Research Associate, University of Texas at Austin Institute for Geophysics)

Huang, Jianhua Huang, Wei (Affiliation Unknown)

Johnson, Valen Breda, Ardala (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015) Pan, Xuedong (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015) Reed, Katherine (Postdoctoral Research Associate, Texas A&M Department of Statistics) Sanyal, Nilotpal (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015) Yajima, Ayako (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015)

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Mallick, Bani Bhadra, Anindya (Assistant Professor, Purdue University) Chakraborty, Avishek (Assistant Professor, University of Arkansas) Chatterjee, Arindam (Assistant Professor, Stat-Math Unit, Indian Statistical Institute) De, Swarup (Analytical Consultant, SAS) Dhavala, Soma (Associate Research Scientist, Dow AgroSciences, LLC) Guha, Nilabja (Postdoctoral Research Associate, Texas A&M Department of Statistics) Kundu, Suprateek (Assistant Professor, Emory University) Zoh, Roger (Research Assistant Professor, Texas A&M School of Public Health)

Sheather, Simon Broglio, Kristine (Statistical Scientist, Berry Consultants)

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APPENDIX K.

Texas A&M University Department of Statistics ByLaws

Introduction

The faculty of the Department of Statistics has as its primary duty to advance the discipline of statistics through teaching, research, service, and consulting. This should be accomplished in an atmosphere of collegiality and cooperation. Each faculty member has a responsibility in furthering the academic goals of the department and in maintaining the excellence of the department. This set of bylaws outlines the manner in which the faculty can achieve these goals.

The Department of Statistics shall be governed by these bylaws, which in turn are governed by policies of the Texas A&M University System, Texas A&M University, and the College of Science. The policies and procedures described in this document are based on the policy statements of the Texas A&M System, Texas A&M University, and the College of Science when appropriate. When those rules and policies change, the Department shall abide by those new rules and policies until the Department can amend these bylaws to reflect the changes.

A major goal of the bylaws is to bring order to the functioning of the Department by defining the rights and duties of department members. These bylaws reflect the principle that the responsibility for e ective governance rests with both the faculty and the Department Head. Furthermore, e ective governance depends on the exercise of responsible leadership by the faculty and the Department Head in their respective roles. The rulesﬀ and responsibilities described in these bylaws shall be implemented with strict adherenceﬀ to academic freedom, due process, and equal opportunity.

I. Faculty Organization

A. Membership of the Faculty of the Department of Statistics 1. All persons holding half-time or greater academic appointments in the Department of Statistics at the ranks of Distinguished Professor, Professor, Associate Professor, Assistant Professor, Executive Professor, Senior Professor, Senior Associate Professor, Instructional Professor, Instructional Associate Professor, Instructional Assistant Professor, Senior Lecturer, and Lecturer are considered to be voting members of the faculty of the Department of Statistics at Texas A&M University (hereinafter, Department). A full-time appointment is defined as 100% during the nine month academic year. The descriptions of all faculty categories and ranks are contained in the document, “Texas A&M University Guidelines to Faculty Titles.” 2. Faculty members holding joint appointments or adjunct appointments in the Department, visiting faculty, and part-time faculty are welcome to attend faculty meetings but cannot vote on Departmental issues. A vote on tenure or promotion matters is restricted to appointments to be made at an equivalent or lower rank than the voting faculty member. Faculty ranks for voting purposes are as follows: Professor, Associate Professor, Assistant Professor, Executive Professor, Senior Professor, Senior Associate Professor, Instructional Professor, Instructional Associate Professor, Instructional Assistant Professor, Senior Lecturer, Lecturer.

B. Administrative Positions in the Department a. Department Head The Department Head is the administrative and executive o cer of the Department and serves as the spokesperson to the University administration and communities outside of the University. ffi b. Term of O ce The term of o ce of the Department Head shall be four years, and is renewable. The Department ffiHead shall be reviewed in the third year of the term according to the procedures ffi 202

established by the College of Science for all department heads within the College of Science.

c. Procedures for Selection of the Department Head

i. The Dean will establish a search committee following consultation with the faculty of the Department and will appoint the chair of the committee, who often is a faculty member outside of the Department but within the College of Science. A majority of the committee should be elected by the faculty of the Department. The Dean may appoint additional members to the committee. ii. The search committee will advertise the position, will review all applicants and nominations, and will make recommendations to the faculty of the Department regarding their preferred candidate(s). A faculty meeting will be held to discuss the qualifications of the recommended candidates. After the faculty meeting, the committee will send the Dean a list of candidates which the committee has identified to invite for an interview. After receiving the Dean’s approval, the candidates will be invited for an interview. Pursuant to the Texas Open Records Act, all non-confidential material pertinent to applicants and nominations will be available to the entire faculty for review. iii. Following a written or online ballot vote of the faculty, the candidate(s) receiving a majority a rmative support will be recommended to the Dean. A ranking of the candidates may also be sent to the Dean if the faculty or search committee so desires. If the vote of the faculty asﬃ a whole di ers from the opinion of the search committee, that information will also be reported to the Dean, along with the recorded vote. The Dean will select and appoint the Department Head.ﬀ iv. See University Document 12.99.99.M6 - Faculty Participation in the Selection, Evaluation, and Retention of Department Heads - for more details. d. Duties of the Department Head The Department Head, through direct action or delegation, shall:

i. In consultation with the Advisory Committee and appropriate Department committees, formulate and implement policies of the Department; ii. Consult regularly with Departmental committee chairs; iii. Preside at Departmental faculty meetings and ensure that accurate minutes of the meetings are preserved and that a summary of the minutes is distributed to the faculty at a reasonable time following the meeting; iv. Formulate and manage the Departmental budget; v. Manage o ce operations; vi. Evaluate faculty and sta annually; ffi vii. Encourage faculty development; ff viii. Carry on departmental correspondence; ix. Resolve student complaints and potential conflicts; x. Serve as the Department’s representative to ASA, SRCOS and COTS; xi. Seek advice from individual faculty members, from Departmental committees, and from the faculty as a whole; xii. Be an ex o cio member of all duly constituted Departmental committees. e. Authority offfi the Department Head

i. The Department Head appoints the chairs of all Departmental committees.

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ii. It is expected that the Department Head will usually support the decisions of the committees and the faculty. If the Department Head is unable to support a recommendation made through usual procedures, the Department Head should, in a timely fashion, give a written explanation to the faculty or to the appropriate committee. In cases of disagreement, the Department Head should include relevant votes of committees and the vote of the faculty when reporting to the College of Science and University. iii. The Department Head, serving as the principal financial o cer of the Department, shall:

1. Supervise receipt and expenditure of all monies; ﬃ 2. Prepare an annual operating budget.

iv. The Department Head, in conjunction with appropriate committees, shall supervise and coordinate the recruiting of new faculty members. v. The Department Head shall make recommendations for faculty salary increases to the Dean. vi. The Department Head shall be responsible for initiating meetings of the Promotion and Tenure Committee in order to ensure timely recommendations for promotion and tenure decisions in the Department and at the College level.

2. Associate Department Head a. The appointment of the Associate Department Head is recommended to the Dean by the Department Head, in conjunction with the Advisory committee. b. The term of the o ce of the Associate Department Head shall be four years, renewable at the discretion of the Department Head. c. The duties of the ﬃAssociate Department Head include:

i. Serve in the capacity of the Department Head whenever the Department Head is unavailable; ii. Serve as the chair of the Advisory committee; iii. Serve on the Student Evaluation committee; iv. Administer teaching assistantships; v. Administer MS Diagnostic Exam and PhD Qualifying Exam; vi. Assign teaching schedules; vii. Develop and coordinate summer internships; viii. Function in the capacity of the Department Head in all matters delegated by the Department Head.

3. Academic Director of Online Programs a. Is appointed by the Department Head. b. The duties of the Academic Director of Online Programs include: i. Prepare an annual budget for the online program; ii. Chair the online M.S. admissions committee; iii. Develop marketing plans for the online program; iv. Supervise the online program’s sta ; v. Develop projects for online M.S. students; ﬀ vi. Be responsible for new initiatives in the online program.

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4. Academic Director of M.S. Analytics a. Is appointed by the Department Head. b. The duties of the Academic Director of M.S. Analytics include: i. Oversee curriculum development and faculty teaching; ii. Manage all administrative aspects of the program: budgeting, strategic enrollment management, all student life cycle issues, and alumni a airs; iii. Faculty recruitment, hiring, and ongoing management; ﬀ iv. Instructional support for faculty; v. Student advising; vi. Chair the admissions committee; vii. Interface with external organizations; viii. Plan and implement specific co-curricular and extra-curricular events as needed.

5. Graduate Advisor a. Is appointed by the Department Head. b. Chairs the Graduate Curriculum committee. c. Chairs the Graduate Student Admissions committee. d. The duties of the Graduate Advisor include: i. Advise graduate students; ii. Serve on university committees associated with graduate admissions, advising, and fellowships; iii. Administer graduate student fellowships; iv. Conduct an annual evaluation of graduate students’ advancement to their Ph.D.; v. Function in the capacity of the Department Head in all matters delegated by the Department Head.

6. Undergraduate Advisor a. Is appointed by the Department Head. b. Chairs the Undergraduate Curriculum committee. c. Chairs the Undergraduate Student Admissions committee. d. The duties of the Undergraduate Advisor include: i. Advise undergraduate students; ii. Serve on university committees associated with undergraduate admissions, advising, and fellowships; iii. Administer undergraduate scholarships; iv. Function in the capacity of the Department Head in all matters delegated by the Department Head.

C. Faculty Meetings 1. There will be at least six regular meetings of the Department faculty during the academic year. These regular meetings of the Department faculty shall be held at even intervals during the academic year. The Department Head shall distribute to the faculty an agenda for each regular meeting at least two days prior to the meeting. 2. The Department Head, or designee, shall preside at each meeting of the Department faculty. 3. Guests may be invited to meetings of the Department faculty by the Department Head or by a member of the Department faculty with concurrence of the Department Head. 4. The Department Head will ensure that accurate minutes of the meetings are preserved and that

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a summary of the minutes is distributed to the faculty at a reasonable time following the meeting. II. Faculty

A. New Faculty 1. Priorities for new faculty recruitment shall be discussed during a meeting of the Department faculty. 2. Tenured/tenure-track faculty positions shall be advertised nationally. Applicants shall be requested to supply a professional vita, along with a statement of research interests and teaching philosophy, and at least three letters of recommendation. All applicants received shall be reviewed by the Department Faculty Recruitment Committee and this committee will select a subset of all applicants for consideration by the faculty during a Department faculty meeting. The faculty shall then select which applicants to be invited for an on campus interview. 3. A Department faculty meeting shall be held to discuss the qualifications of all applicants making a campus visit. A faculty vote to select which applicant(s) will receive a position o er will be conducted after the discussion. 4. Appointments at the rank of Lecturer may be made by the Department Headﬀ with the concurrence of the Advisory Committee. 5. Appointments at the rank of Senior Professor, Senior Associate Professor, Instructional Professor, Instructional Associate Professor, Instructional Assistant Professor, and Senior Lecturer may be made by the Department Head upon recommendation of the P&T Committee. 6. Adjunct Faculty: Any voting faculty member may propose an adjunct faculty appointment. The candidate’s curriculum vitae must be distributed to the faculty. A discussion and vote on granting of the adjunct position will take place at the first faculty meeting following the distribution of the cv.

B. Visiting Faculty Appointments 1. Any member of the Faculty may recommend the appointment of visiting faculty members at the rank of Visiting Professor, Visiting Associate Professor, or Visiting Assistant Professor. The purpose of such appointments shall be to bring within the Department for a limited period of time scientists whose interactions with the faculty or students of the Department can be expected to benefit the Department with respect to research and/or teaching. 2. Visiting faculty appointments shall be for a period of no more than one year. 3. The decision on o ering a visiting faculty position shall be made by the Department Head.

ﬀ C. Faculty Leaves of Absence 1. Applications for sabbatical leaves shall ordinarily be submitted to the Department Head not later than nine months before the proposed leave. 2. A leave of absence shall be for a period of no more than one year. 3. If the sabbatical is for one semester, then the faculty member’s teaching load will be one course during the second semester of the sabbatical year. 4. Requests for short term leaves during a period in which classes are in session must be submitted to the Department Head. 5. Texas A&M University’s parental teaching load redistribution guideline is designed to provide flexibility in teaching obligations of faculty members who are the primary care givers to their newborn infant, or to their newly adopted infant or child. The Department Head will work with faculty to arrange one/ two semester(s) of relief from formal classroom teaching or other time- rigid duties for the birth or adoption of a child for any eligible faculty member. Also, faculty may be granted leave in accordance with the Family and Medical Leave Act or any currently applicable state or federal law.

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D. Instructional Faculty and Lecturers An instructional faculty member (i.e., instructional professor, instructional associate professor, instructional assistant professor) or lecturer is a non-tenure track faculty member whose primary function is classroom teaching. The appointment of an instructional faculty member or lecturer is generally restricted to persons who possess a Ph.D. in statistics or related fields but in special circumstances, an M.S. will be acceptable. The term of initial appointment is one year; subsequent one-year appointments may be o ered. Instructional faculty members and lecturers will be recruited by an open announcement of the position. The Department Head shall decide on whether to hire an instructional faculty member or lecturer.ﬀ

There will not be a faculty vote on the hiring of instructional faculty members or lecturers. 1. The title of Instructional Professor, Instructional Associate Professor, Instructional Assistant Professor and Senior Lecturer is to be used for faculty who meet the criteria of Lecturer, and who have at least fi e years of experience as a Lecturer or its equivalent. Initial appointment to these ranks requires a recommendation of the Promotion and Tenure Committee, the Department Head, and approval of the Dean. 2. Instructional faculty members and Senior Lecturers will have annual appointments for at least the first three years, but will always receive 12 months’ notice if they are not to be reappointed. 3. Status, Expectations, and Professional Development

a. Instructional faculty members and lecturers are members of the Department faculty and will be a orded the respect and status comparable to that of tenured and tenure track faculty. b. Instructional faculty members and lecturers will be included in all Depart- mental academic ff a airs, including faculty meetings, committee meetings, and curriculum development. c. Instructional faculty members and lecturers will be provided o ce space and the computer facilitiesff necessary to fulfill their teaching responsibilities. d. Instructional faculty members and lecturers will be encouraged toffi initiate and/or participate in scholarly activities associated with all aspects of statistical education. e. Instructional faculty members and lecturers may apply for membership on the graduate faculty in accordance with OGAPS guidelines. An instructional faculty member or lecturer may serve as the chair of an MS student’s committee but not as the chair of a Ph.D. student’s committee. 4. Annual Review a. The performance of all Instructional faculty members and lecturers will be reviewed by the Department Head annually. b. Performance criteria will be based on teaching and related activities, with additional recognition given to publications and service. c. Based on annual reviews, instructional faculty members and lecturers may be recommended to the P&T Committee for promotion to Senior Lecturer, Instructional Assistant Professor, Instructional Associate Professor, or Instructional Professor.

III. Teaching

A. Academic Year Teaching Assignments 1. The teaching load for all tenured, tenure-track faculty will be three courses during the academic year during that period of their career when they are actively involved in research. 2. If a faculty member’s research e ort is deemed by the Department Head to be inactive, the Department Head will modify the duties of the faculty member by increasing the teaching load to more than three courses per academicﬀ year and/or ask the faculty member to direct the M.S. projects for Online Learning students. Faculty members may initiate a discussion with the

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Department Head concerning a change in title to Senior Professor or Senior Associate Professor if they do not intend to increase their research productivity. A change in title requires the Dean of Faculty’s approval. 3. Other exceptions to the standard teaching assignment are a two course per academic year assignment for Distinguished Professors, Associate Department Head, Academic Director of Online Programs, and Graduate Advisor. The Department Head is not expected to have teaching responsibility but may teach at his/her discretion. The Department Head, at his or her discretion, may also reduce the teaching load of regular faculty members by one course for exemplary service in attracting external grant funding, for the publication of seminal research, or for meritorious service as the chair of a departmental committee. 4. Senior Lecturers and Lecturers will teach three or more courses per semester during the academic year. 5. The Department Head, as part of the recruitment package, may reduce the teaching load for newly hired faculty. For example, Assistant Professors during the first two years of their appointment have a teaching load of two courses per academic year. 6. Faculty members may decide to reduce their teaching load by using grant money to buy out of a course. The rate to buy out a course for a faculty member who is the P.I. on a grant is the smaller of $28,500 and 2 months salary. The cost of a non-P.I. is the smaller of $28,500 and 3 months salary. This rate will be adjusted annually by the Department Head. The faculty member shall notify the Associate Department Head at least two months prior to the beginning of the semester so that adjustments may be made to the teaching assignments. 7. To facilitate preparation of course materials, teaching assignments shall normally be determined three months in advance of the assignment.

B. Departmental Summer Appointments 1. Prospective summer teaching positions shall be advertised to the Department faculty by the Associate Department Head. 2. Department faculty members shall apply for summer teaching appointments in writing to the Associate Department Head, in accordance with a time schedule announced by the Department Head. 3. Summer teaching appointments shall be made by the Associate Department Head. Priority in summer teaching opportunities will be given fi to Department faculty. 4. Certain activities such as the M.S. Diagnostic Examination and Ph.D. Qualifying Examination will require faculty participation during the summer. Faculty members who can comply without serious inconvenience may be called upon to perform such duties without additional compensation.

C. Distance Learning Teaching Assignments 1. The Department teaches a number of distance learning courses. The Distance Learning program provides a stipend to the instructor for teaching the two extra sections of the assigned course. This stipend is deposited into an account to be used by the instructor for professional development.

2. The Department o ers a repeat of distance courses taught in the previous semester. The instructors for these courses do not provide the lecture for the course but create homework assignments, exams, ﬀconduct a weekly Q&A session, and monitor the discussion board. These duties are referred to as “minding the course”. The Distance Learning program provides one month of summer salary for minding a course. The selection of faculty to mind a course is made by the Associate Department Head and is an additional course which does not count towards the instructors three course teaching assignment.

D. Analytics Teaching Assignments 1. In conjunction with the Mays Business School, the Department o ers a M.S. degree in Analytics. The courses are taught in Houston and online. The instructors for these courses are recruited ﬀ 208

by the Academic Director of Online Programs. The instructors are paid a stipend which is in addition to their nine month salary. 2. The teaching of an Analytics course does not count towards the faculty member’s teaching assignment.

IV. Research Advising

A. Selection of Gra dua te Research Advisors 1. The selection of a graduate research advisor is one of the most important decisions that a graduate student will make. To assist students in making the decision, the faculty are encouraged to participate in Brown Bag seminars sponsored by the Statistics Graduate Student Association. Another avenue to assist the graduate students and the faculty in obtaining a productive matching of graduate student with advisor is the teaching of Special Topics courses. In these STAT 689 courses the student and faculty member are able to assess the capability of the student to conduct research and for the student to become familiar with the research interests of the faculty member. The faculty are encouraged to have a current webpage populated with information detailing their research program. The faculty are encouraged to present seminar talks in our department to expose interested students to the faculty member’s research interests. 2. OGAPS allows an Adjunct Professor in the Department of Statistics and any member of the graduate faculty at Texas A&M University to serve as a co- chair of M.S. and Ph.D. committees. The Chair of these committees must be a faculty member in the Department of Statistics. 3. The selection of a research advisor is a serious matter and usually it is expected that a student will remain with his/her chosen advisor for the duration of the degree program. However, in the rare case that a student may wish to change advisor, a petition in writing by the student to the Graduate Advisor shall be composed. The Graduate Advisor shall then provide the student with advice on making the change. The student is expected to select a new advisor prior to the start of the following semester. B. Postdoctoral Appointments All appointments at the postdoctoral level must be approved by the Department Head, regardless of the funding source. This requirement is normally satisfied via the employment documents which bear the Department Head’s signature. Appointment periods must be stated clearly on the appropriate employment documents.

C. Research Assistantships Faculty wanting to support a research assistant shall notify the Associate Department Head at least two months prior to the beginning of the semester in which the support is provided if the proposed student is currently being supported as a teaching assistant (TA) or technology teaching assistant (TTA).

V. Committees

A. General Procedures 1. Service on Departmental committees is considered a normal part of each faculty member’s duties. All faculty members are encouraged to raise issues to be considered by any of the Department’s committees. Meetings of committees will be held only when a majority of the voting members of the committee are present. Unless otherwise stated, all committee members serve in a voting capacity. 2. The agenda for each meeting will be determined by the committee chair and a copy of the agenda should be distributed to members at least one day in advance of the meeting.

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3. Except as otherwise noted, all committees will establish their own procedures, provided that the following conditions are met: a. Members of the Department concerned with an issue relevant to the committee shall be a orded an opportunity to present their views during a scheduled meeting of the committee. b. Any faculty member of the Department may make proposals to the committee in writing. Sucﬀ h proposals will normally be given consideration within two months. c. Each committee will establish procedures for receiving and considering proposals from undergraduate and graduate students as appropriate. d. Some committees include student representation. During discussions involving the evaluation of a particular student or faculty member, the student representative must be excused from the room in which the meeting is being held.

B. Departmental Committees Unless otherwise stated in this document, departmental committees will be selected by the Department Head, with the proviso that at least one member of the committee shall serve a two- year term in order to provide continuity to the committee’s operations.

Advisory Committee - The purpose of the Advisory Committee is to review major departmental actions and make recommendations to the Department Head, and to serve as a resource for long-range planning and policy issues related to all activities, other than curriculum, in the Department.

Awards Committee - Solicits and reviews nominations of Department faculty members for College and University awards, and for professional society awards. Reviews applications and nominations for awards to Department graduate students.

Colloquia-Special Events Committee - Organizes and coordinates departmental colloquium and special seminars.

Endowed Positions Committee - Reviews applications and nominations for endowed positions

Faculty Recruitment Committee - Reviews applications and nominations for faculty positions Graduate Admissions Committee - Reviews academic records and qualifications of prospective graduate students; Recommends to the Department Head students for admission.

Graduate Curriculum Committee - Establishes and reviews Departmental standards related to the graduate course requirements; review Depart- mental policies related to M.S. Diagnostic exam, Ph.D. Qualifying exam, and Ph.D. Preliminary exam; reviews faculty proposals for new graduate courses.

Graduate Service Committee - Periodically reviews the syllabi for graduate service courses. Graduate Student Evaluation Committee - Constructs the Ph.D. Qualifying Exam which will be administered annually, two weeks after the end of Spring Semester. Reviews academic records and performance on the Ph.D. Qualifying Exam and makes a recommendation to the Department Faculty on which students shall be allowed to continue in the Ph.D. program. To facilitate student advising, the Graduate Advisor shall not be a member of this committee.

Post-Tenure Review Committee - Reviews instructional and research performance and professional activities of Full Professors; provides input to the Department Head on the performance of tenured Full Professors.

Promotion and Tenure Committee - Reviews instructional and research performance and

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professional activities of Lecturers, Assistant and Associate Professors; advises Department Head on promotion, tenure, and appointment recommendations.

Undergraduate Curriculum Committee - Reviews curricula and requirements of undergraduate majors; plans modifications and improvements to the undergraduate program.

C. Advisory Committee (AC) 1. The AC consists of eight members with at least one Lecturer, Assistant Professor, and Associate Professor serving on the committee. The chair of the AC is the Associate Department Head. The AC’s members are either elected by the faculty or appointed by the Department Head. 2. The AC will establish a regular time for its meeting. The agenda for these meetings will be determined by the chair of the AC and will be posted several days prior to the meeting. It is expected that the AC will meet every month during the academic year and occasionally during the summer months as needed. 3. The purpose of the AC is to advise the Department Head and to serve as the Department Head’s resource for long range planning and policy issues. The AC will represent the Department as a whole, keeping the Department Head informed of both current problems confronting the faculty as well as discussing directions for future development of the Department.

D. Post-Tenure Review (PTR) and the PTR Committee At least once every six years, an evaluation of each tenured faculty member is conducted by the Department of Statistics. This review is in addition to the annual reviews performed by the Department Head. The performance of each tenured faculty member will be evaluated with respect to teaching, research, and service. 1. Membership of the PTR Committee will consist of three elected members by vote of the Department’s Full Professors and two members appointed by the Department Head. 2. The duties of the PTR Committee are as follows: a. Each tenured professor will be reviewed by the PTR Committee no less than once every six years. b. The PTR Committee will base their review on materials submitted by the reviewed faculty member and materials from the annual faculty reviews. The faculty member undergoing review may include materials other than those listed. c. The PTR Committee will recommend to the Department Head an evaluation of Satisfactory or Unsatisfactory for each tenured professor along with supporting documentation of their assessment. The assessment will be based on the criteria listed in Section VI. d. A vote of all fi e members is required. 3. If the report from the PTR Committee fi the faculty member at an unsatisfactory level in performance, a Professional Review will be initiated. The details for the Professional Review are in the Texas A&M University Post- Tenure Review document, 12.06.99.M0.01. 4. If a faculty member receives an unsatisfactory report from the annual evaluation by the Department Head for three consecutive years, the faculty member will be subject to the Professional Review as specified in the Texas A&M University Post-Tenure Review document, 12.06.99.M0.01.

E. Promotion and Tenure Committee (P&T) 1. The procedural rules for the P&T Committee are detailed in the document, Promotion, Tenure, and Annual Review Guidelines, Department of Statistics, Texas A&M University, August 2012. 2. Membership consists of three faculty members appointed by the Department Head; three Full Professors elected by a majority vote of the entire tenured and tenure-track faculty; and one Associate Professor elected by a vote of the Assistant and Associate Professors. Elections are held during the fi week of February. The P&T Committee chair is appointed by the Department Head. Faculty who have served three consecutive years will be removed from the ballot for the following two years.

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3. The duties of the P&T Committee are as follows: a. Each spring the P&T Committee prepares a written evaluation of the progress of each of the non-tenured faculty members in tenure-track positions. b. A third-year review will be prepared for all non-tenured Assistant Professors in a tenure-track position. c. Each spring the P&T Committee prepares a written evaluation of the progress of each of the Associate Professors towards promotion to Full Professor. d. The Department Head does not participate in making the written evaluation but the Department Head will meet with each of the Assistant and Associate Professors to review the P&T Committee’s evaluation. e. The P&T Committee prepares a committee discussion report and recommendations for each candidate for promotion and/or tenure. The report shall follow the guidelines from the Dean of Faculties. f. The P&T Committee shall prepare guidelines on the procedures required of candidates for tenure and promotion. These guidelines shall be distributed to all faculty holding the rank of Lecturer, Assistant Professor, and Associate Professor. g. The P&T Committee will consider for emeritus status every individual who, at the time of retirement, holds a tenured appointment in the department and has served the university at least ten years unless the in faculty member requests in writing that he/she not be so considered. Individuals who are non-tenured or who have served less than ten years may also be considered. 4. A vote of all seven members is required for promotion and tenure decisions.

VI. Faculty Evaluation The evaluation of faculty in the Department of Statistics is the responsibility of the Department Head. The Department Head solicits advice from Departmental committees in the evaluation of the performance of the faculty.

A. Procedures 1. Annual Review: Each year the department, in accordance with the University Statement on Academic Freedom, Responsibility, Tenure, and Promotion (SAFRT), will carry out an annual review of all faculty in the ranks of Lecturer, Senior Lecturer, Instructional Assistant Professor, Instructional Associate Professor, Instructional Professor, Senior Associate Professor, Senior Full Professor, Assistant Professor, Associate Professor, and Full Professor. The review will follow the form contained in the SAFRT with the following clarifications: i. The criteria to be used in the evaluation process are contained in Section B. ii. The annual review will take place during the Spring semester. iii. The faculty shall submit the department’s Annual Report Form detailing their activities for the previous calendar year with respect to research, teaching, and service. iv. The Department Head shall provide every faculty member a written report detailing the Department Head’s assessment of their performance in the areas of teaching, research, and service. v. The Department Head will also meet with each Assistant Professor and Associate Professor to discuss their performance and progress towards tenure and promotion. Any of the remaining faculty may request a meeting with the Department Head to discuss the written summary of their performance. vi. If a faculty member wishes to disagree with anything contained in the Department Head’s written report, he/she may append a written comment to the report. vii. If a faculty member’s annual evaluation by the Department Head results in an Unsatisfactory

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for three consecutive years, the faculty member will be subject to the Professional Review as specified in the Texas A&M University Post-Tenure Review document, 12.06.99.M0.01.

2. Promotion and Tenure: The P&T Committee is responsible for advising the Department Head on promotion and tenure decisions. See Section V, subsection E of this document.

3. Post Tenure Review: At least once every six years, an evaluation of each tenured faculty member is conducted by the Department of Statistics. The PTR Committee is responsible for providing the Department Head the post tenure review of all tenured faculty members. The PTR Committee shall focus on the faculty member’s performance during the past two years but will also take into account achievements over a longer period and work in progress. The PTR Committee will recommend to the Department Head an evaluation of Satisfactory or Unsatisfactory for each faculty member under review along with supporting documentation of their assessment. If the report from the PTR Committee fi the faculty member at an Unsatisfactory level in performance, the faculty member will be subject to Professional Review as specified in the Texas A&M University Post-Tenure Review document, 12.06.99.M0.01.

B. Evaluation Scores The PTR committee will evaluate the research, teaching, and service performance of every tenured faculty member at least once every six years. The Department Head will evaluate every faculty member during the spring semester of every year. The evaluations will be designated as Superior, Satisfactory, or Unsatisfactory. For purposes of Post Tenure Review, the Department Head and PTR committee shall rate faculty members at one of three levels of performance in each of the three categories of research, teaching, and service, as shown below:

Research Teaching Service 1. Superior Superior Superior 2. Satisfactory Satisfactory Satisfactory 3. Unsatisfactory Unsatisfactory Unsatisfactory

The ratings for research, teaching, and service would then be combined to give an overall assessment of Satisfactory or Unsatisfactory as follows: Rule 1: If research is unsatisfactory, then the overall rating is unsatisfactory.

Rule 2: If teaching is unsatisfactory, then research must be superior to obtain an overall satisfactory, otherwise the overall rating is unsatisfactory. Rule 3: If service is unsatisfactory for one year, then the Department Head will specify corrective action that must be taken to achieve a satisfactory rating. If service is unsatisfactory for two years (not necessarily in succession), then the Department Head may, at his or her discretion, provide an overall rating of unsatisfactory. The criteria for the determination of the ratings in research, teaching, and service are described in the next section.

Criteria for Determination of Performance Ratings 1. Research Evaluation: The evaluation of research is mainly based on original scientific research and the publication of the results of such research. By its very nature, the evaluation of research is subjective, and the period over which research productivity is evaluated also depends on the outcome of the research. For example, the publication of a research volume may require two or more years, and

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articles published in leading statistical journals may sometimes have less impact than articles published in more general scientific outlets. In general, however, the following guidelines are to be used in evaluating research; the time frame over which these criteria are applied is typically one or two years, depending on the nature of the work and the publication times of targeted journals.

Superior - Achieve several of the following: • Publications in leading refereed statistics journals or leading refereed journals in allied fi • Receiving significant external peer-reviewed funding for research • Frequent citation of publications • Publication of scholarly book(s) • Selection for a University, College of Science, or professional society outstanding researcher award • Publications and funding resulting from collaborative e ort with leading researchers in other fields ff Satisfactory - Achieve several of the following: • Publications in refereed journals • Publication of a chapter in a scholarly book • Presentation of invited and contributed papers at international and national meetings • Publications in refereed proceedings of conferences and professional meetings • Significant self-development activities that lead to increased research and publication e ectiveness • Publications and funding resulting from collaborative e ort with researchers in other fields ff Unsatisfactory ff • Not achieving a superior or satisfactory rating

2. Teaching Evaluation: The evaluation of teaching includes classroom instruction; development of new courses and teaching methods; publication of innovative pedagogical approaches or instructional materials, including textbooks; and supervision of graduate student research. The following factors may be used to evaluate the level of teaching performance.

Superior - Achieve several of the following: • Selection for a University, College of Science, or professional society outstanding teaching award • Chair of doctoral research committees • Evidence of courses taught at a rigorous and challenging level • Publication of widely adopted or acclaimed instructional material • Outstanding teaching performance as evidenced by outstanding teaching evaluations • Development of innovative pedagogical methods and materials • Development of new courses or major revision of existing courses • Extraordinary service on graduate student advisory committees • Publications in refereed education journals • Evidence of high quality in class preparation, interaction with students, and lectures

Satisfactory - Achieve several of the following: • Chair of M.S. committees • Member of graduate student advisory committees • Evidence of quality in class preparation and interaction with students

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• E ective coordination of multi-section courses • Serve as Departmental undergraduate or graduate advisor ﬀ • Significant self-development activities leading to enhanced teaching e ectiveness

Unsatisfactory ﬀ • Continuing or repeated substantial neglect of teaching responsibilities

3. Service Evaluation: The evaluation of service includes service to the students, Department, Texas A&M University, and service to professional societies, research organizations, governmental agencies, and the public at large. Superior - Achieve superior performance in several of the following: • O cer in a national professional organization • Serving on a major government commission, task force, or board ﬃ • Administrative leadership role at University, College, or Department level • Editor or member of editorial board of major journal • Member of review panel for national research organization • Program chair at a national meeting • O cer in Faculty Senate • Chair of major Departmental or Texas A&M University committee ﬃ • Substantial fund raising to support Departmental activities • Member of review panel for national research organization • Obtain positive state, regional, or national recognition for the department

Satisfactory - Achieve excellent performance in several of the following: • O cer in regional or state professional organization • Program or committee chair for regional or state professional meeting ﬃ • Serving as an active member of the Faculty Senate • Serving on University, College of Science, or Departmental committee • Serving as consultant to business or governmental agencies • Advisor to student organizations • Administrative roles with the Department • Director of the Department’s consulting and internship e orts • Participating in department’s outreach to industry and continuing education activities ﬀ • Service as a reviewer for major refereed journals • Organizer of a session at a national meeting • Regularly attend Departmental seminars and faculty meetings • Participate in departmental activities, such as, recruitment of new faculty and students, attend departmental functions outside of the normal business hours, etc. • Organizing Departmental research workshop

Unsatisfactory • Continuing or repeated substantial neglect of service responsibilities Behavior that is deemed by the Department Head and a majority of the Post Tenure Re- view Committee as being detrimental to the collegial atmosphere and working environment within the Department.

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VII. Amendment of Bylaws Amendments to these bylaws may be initiated by either the Department Head or by the petition of twenty fi e percent of the Departmental faculty. To be adopted, an amendment must be approved by a two-thirds majority of the Departmental faculty.

VIII. Conflict between Bylaws and Other Regulations Should any part of these Bylaws be in conflict with regulations of the Texas A&M System, Texas A&M University, College of Science, State of Texas, or the United States of America, those regulations take precedence over the Department of Statistics Bylaws.

IX. History of Bylaws • Accepted By Faculty Vote on March 23, 2015

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APPENDIX L.

Faculty Biographical Sketches

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DERYA GÜVEN AKLEMAN

Education: Middle East Technical Univ. Statistics B.S. (1987) Middle East Technical Univ. Statistics M.S (1989) Texas A&M University Statistics M.S (1993) Texas A&M University Agricultural Economics Ph.D. (1996) (Marketing & Econometrics) Appointments: Instructor & Assist. Dept. Head Dept. of Statistics, Middle East Technical Univ. June 1996-June 1997 Visiting Assistant Professor Dept. of Statistics, Texas A&M University Spring 1998-Fall 2002 Lecturer Dept. of Statistics, Texas A&M University Fall 2002-Fall 2008 Senior Lecturer Dept. of Statistics, Texas A&M University Fall 2008-present

Teaching: Last five years: 1. Stat 653: Statistics in Research III, In class and online (three sections, every Spring), Spring2012-present 2. Stat 652: Statistics in Research II, In class and online (three sections, every Fall and Spring), Spring 2006-present 3. Stat 651: Statistics in Research I, In class and online (three sections, every Fall and Spring), Spring 2001-present 4. Stat 642: Methods in Statistics II, online (three sections), Summer 2011 Other TAMU courses thought before: 1. Stat 211: Principles of Statistics I, Fall 2000,01,02,03,04; Spring 2002,03,04,05; Summer 2000,01,02,03 2. Stat 212: Principles of statistics II, Spring 1998,99 3. Stat 302: Statistical Methods, Spring 1998,2000; Fall 1999, 2000; Summer 2000 4. Stat 225: Mechanical Engineering Statistics, Fall 1998,99; Spring 1999

Noteworthy Publications:

1. Turgut Var, Ozlem Unal, and Derya Güven Akleman, “Tourism in Peripheral Areas: A Case of Three Turkish Towns”, e-Review of Tourism Research (eRTR) (an international electronic bulletin for tourism research. http://ertr.tamu.edu), Applied Research Notes, Vol.2, No.2, 2004, 33-37. 2. Derya Güven Akleman, David A. Bessler and Diana M. Burton, “Modeling Corn Exports and Exchange Rates with Directed Graphs and Statistical Loss Functions” Clark Glymour and Gregory Cooper, editors: Computation, Causation and Discovery. Cambridge:MIT Press, 1999, 497-520. 3. David A. Bessler and Derya Güven Akleman, “Farm Prices, Retail Prices and Directed Graphs: Results for Pork and Beef” American Journal of Agricultural Economics. Vol. 80, No.5, December 1998, 1144-1149. 4. Mehmet R. Tolun and Derya Güven, “Analyzing the Inter and Intra Vocabulary Performances in Isolated Speech Recognition”, Journal of American Voice Input/Output Society, 10, July 1991, 19-37. University and Department Service:

Last nine years: 1. Member, Department of Statistics Faculty Advisory Committee (April 2014-present) 2. Member, College of Science Diversity Committee, Texas A&M University (Fall 2008-Present) 3. Member, Faculty Senate, Texas A&M University (Fall 2006-Fall 2012, Fall 2014-present) 4. Member, Diversity Committee (now called Workplace, Climate and Diversity) of Faculty Senate, Texas A&M University (Fall 2007-Fall 2012, Fall 2014-present) 5. Member, College of Science Caucus, Faculty Senate, Texas A&M University (Fall 2006--Fall 2012, Fall 2014- present)

218

6. Member, Academic Affairs Committee, Faculty Senate, Texas A&M University (Fall 2006-Fall 2011) 7. Leader, College of Science Caucus, Texas A&M University (Fall 2007-Fall 2008) 8. Member, Personal and Welfare Committee, Faculty Senate, Texas A&M University (Fall 2006-Fall 2007)

Membership: American Statistical Association, 1990-present

Honors (Chosen by students): The Physicians Centre Hospital Guest Coach, Fall 2008

Grants awarded: Last five years: 1. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2013-Fall 2014 2. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2012-Fall 2013 3. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2010-Fall 2011

Student committee membership: Last five years: Nayab Ali MS in STAT Elizabeth Goldman MS in Math Ashley Schnoor MS in Math Nancy Okeudo MS in Math Mark Chapman MS in Math Jay Clawson MS in Math Matthew Austin MS in Math Craig Sullivan MS in Math Jason Mahaffey MS in Math Madhuri Sanagaram MS in INEN (Graduated Spring 2014) Lisa C. Obrien MS in MATH Erika Pesek MS in MATH Lorenzo Gordon MS in MATH Joel T. Ward MS in MATH (Graduated Spring 2014) Radhika Sundararaman MS in INEN (Graduated Spring 2014) Julie Sarzynski MS in MATH Ashley Hubble MS in MATH (Graduated Summer 2014) Joshua Wilkerson MS in MATH Rebekah Zimmermann MS in MATH Lisa Beatty MS in Math (Graduated Spring 2014) Ahlam Mohamad Musa Ph.D in EDUCATION (Graduated Spring 2013) Karevaradharaj Doraiswamy Selvaraj MS in INEN (Graduated Fall 2012) Eduardo Drucker MS in MATH (Graduated Fall 2013) Stephen Dauphin MS in MATH (Graduated Spring 2013) Susan Powell MS in MATH (Graduated Fall 2012) Chanin L. Monestero MS in MATH (Graduated Fall 2012) Mark McKinnon MS in MATH (Graduates Spring 2014) Kathryn Lemons MS in MATH (Graduated Summer 2012) Suzanne Fluke MS in MATH (Graduated Spring 2013) Jason Daniel Tepe MS in MATH Janessa Kathleen Tucker MS in MATH (Graduated Spring 2012) Meghan Waterbury MS in MATH (Graduated Fall 2012) Gail Faith Thorne MS in MATH (Graduated Spring 2013) David Lee Fleeger MS in MATH (Graduated Summer 2013) Sarah Evangeline MS in MATH Zachary Dean Adian MS in MATH Scott Harold Copperman MS in MATH (Graduated Spring 2013) Janell Christine (Eck) Martin MS in MATH (Graduated Spring 2013) 2

219 Bradley Keith Scott MS in MATH (Graduated Fall 2011) Stephanie Gail Nite MS in MATH (Graduated Summer 2012) Janessa Kathleen Tucker MS in MATH Teo J. Paoletti MS in MATH (Graduated Fall 2010) Michael Vieira Serpa MS in MATH (Graduated Fall 2011) Michael Kenneth Soper MS in MATH (Graduated Spring 2011) Jennifer Kristi Ulrich MS in MATH (Graduated Spring 2011) Scott Harold Copperman MS in MATH (Graduated Spring 2013) Janell Christine Eck Bradley Keith Scott Camellia Blackbery Ebru Celile Ozbay MS in MATH (Graduated Spring 2011) Christopher M. Golubski MS in MATH (Graduated Fall 2010) Rodney Dale Wyrick MS in MATH (Graduated Summer 2010) Thomas Andrew Moseder MS in MATH (Graduated Spring 2011) Rudy C. Medina MS in MATH (Graduated Spring 2011) Cynthia Lucille Bervig Betsy McIver G Jones Daniel J. Groom MS in MATH (Graduated Fall 2010) Joshua Dustin D. Hammond Scott T. Dickie MS in MATH (Graduated Summer 2010) Kurt Michael Bruggeman MS in MATH (Graduated Spring 2010) Damon McDaniel MS in MATH (Graduated Fall 2010) Richard Uber MS in MATH (Graduated Summer 2010) Alexander Munson MS in MATH (Graduated, Summer 2009) Sarah Martin Luther MS in MATH (Graduated, Fall 2009) Diana Wright Branton MS in MATH (Graduated, Summer 2009) Yanjing Liu MS in MATH (Graduated, Summer 2009) April Lile Carne MS in MATH (Graduated, Fall 2009) Ryan Albert Melbard MS in MATH (Graduated, Spring 2009)

220 ANIRBAN BHATTACHARYA

Education: Indian Statistical Institute, Kolkata, India Statistics B.S. (2006) Indian Statistical Institute, Kolkata, India Statistics M.S. (2008) Duke University Statistics Ph.D. (2012) Appointments: Assistant Professor Texas A&M Univeristy 2013 – Pres. PostdoctoralAssociate DukeUniversity 2012–2013 Publications: i. Last ﬁve years: 1. (with Dunson, D.B.) Sparse Bayesian inﬁnite factor models. Biometrika, (2011), 98(2), 291-306. 2. (with Dzirasa, K., Mcgrarity, D., and others) Impaired limbic gamma oscillatory synchrony during anxiety related behavior in a genetic mouse model of bipolar mania. Journal of NeuroScience, (2011), 31(17), 6449- 6456. 3. (with Dunson, D.B.) Simplex factor models for multivariate unordered categorical data. Journal of the Amer- ican Statistical Association, (2012), 107, 362-377. 4. (with Pati, D., Dunson, D.B.) Anisotropic function estimation using multi-bandwidthGaussian processes. The Annals of Statistics, (2014), 42(1), 352-381. 5. (with Pati, D., Pillai, N.S. and Dunson, D.B.) Posterior contraction in sparse Bayesian factor models for massive covariance matrices. The Annals of Statistics, (2014), 42(3), 1102-1130. 6. (with Pati, D., Pillai, N.S. and Dunson, D.B.) Dirichlet-Laplace priors for optimal shrinkage, Journal of the American Statistical Association, In press. 7. (with Zhou, J., Herring, A.H. and Dunson, D.B.) Bayesian factorizations of big sparse tensors. Journal of the American Statistical Association, In press. 8. (with Pati, D. and Cheng, G.) Optimal Bayesian estimation in random covariate design with a rescaled Gaus- sian process prior. Journal of Machine Learning Research, To appear.

Grants:

1. PI, Ofﬁce of Naval Research (ONR BAA 14-0001), $105,721, Bayesian inference for high-dimensional covariance matrices and tensors, 2014-2016.

Awards and Honors:

1. Leonard J. Savage Dissertation Award (Theory and Methods) 2012, awarded by the International Society for Bayesian Analysis (ISBA) 2. Student paper award from Section of Bayesian Statistical Science (SBSS), 2011 3. Member of Editorial Boards: Statistics and Probability Letters (2015-Present).

221 Service:

1. Session chair, Joint Statistical Meetings, Montreal, Canada, 2013 2. Organized session on “Emerging trends in Bayesian nonparametrics”, International Symposium on Business and Industrial Statistics / Conference of the ASA Section on Statistical Learning and Data Mining (ISBIS/SLDM), Durham, NC, 2014.

3. Session chair, International Society of Bayesian Analysis (ISBA) World Meetings, Cancun, Mexico, 2014. 4. Colloquium chair, Department of Statistics, Texas A&M University, 2014 - Pres. 5. Reviewer for Annals of Applied Statistics, Annals of Statistics, Bayesian Analysis, Bernoulli, Biometrika, Electronic Journal of Statistics,Journal of the American StatisticalAssociation, Journal of Machine Learning Research among others. 6. Member of PhD qualifying exams committee, Department of Statistics, Texas A&M University, 2014 - Pres.

222 JULIE HAGEN CARROLL

Education: Texas A&M University Mathematics B.S. (1979) Texas A&M University Industrial Engineering M.S (1985) Texas A&M University Statistics M.S. (1990)

Appointments: Lecturer Department of Statistics, Texas A&M University 1992-1999 Senior Lecturer Department of Statistics, Texas A&M University 1999-Pres.

Course Taught: STAT 303 200+ undergraduates both Fall and Spring 1992-Pres.

Service: Undergraduate Service Committee Assistantship Duties Committee Corps of Cadet Academic Advisor for Company F-2

Awards: TAMU Fish Camp Namesake TAMU Association of Former Students College Level Teaching Award

223 RAYMOND J. CARROLL

Education: University of Texas at Austin Mathematics B.S. (1971) Purdue University Statistics Ph.D.(1974) Appointments: Distinguished Professor and Harlin Chair Department of Statistics, TAMU 1987–1998 and 2000-present Professor and Fairhill Chair Department of Epidemiology University of Pennsylvania, 1998-2000 Assistant,Associate and FullProfessor Universityof NorthCarolina 1974-1987 Publications: i. Last ﬁve years, selected from 87 papers, 2010-present 1. Martinez, J. G., Huang, J. Z., Burghardt, R. C., Barhoumi, R. and Carroll,R. J. (2010). Useof multiplesingular value decompositions to analyze complex intracellular calcium ion signals. Annals of Applied Statistics, 3, 1467-1492. 2. Sinha, S., Mallick, B. K., Kipnis, V.and Carroll, R. J. (2010). Semiparametric Bayesian analysis of nutritional epidemiology data in the presence of measurement error. Biometrics, 66, 444-454. 3. Zhou, L., Huang, J., Martinez, J. G., Maity, A., Baladandayuthapani, V. and Carroll, R. J. (2010). Reduced rank mixed effects models for spatially correlated hierarchical functional data. Journal of the American Sta- tistical Association, 105, 390-400. 4. Staicu, A.-M., Crainiceanu, C. M. and Carroll, R. J. (2010). Fast methods for spatially correlated multilevel functional data. Biostatistics, 11, 177-194. 5. Li, Y., Wang, N. and Carroll, R. J. (2010). Generalized functional linear models with semiparametric single- index interactions. Journal of the American Statistical Association, 105, 621-633. 6. Carroll, R. J., Hart, J. D. and Ma, Y. (2011). Local and omnibus tests in classical measurement error models. Journal of the Royal Statistical Society, Series B, 73, 81-98. 7. Carroll, R. J., Delaigle, A. and Hall, P. (2011). Testing and estimating shape-constrained nonparametric density and regression in the presence of measurement error. Journal of the American Statistical Association, 106, 191-202. 8. Zhang, S., Midthune, D., Guenther, P. M., Krebs-Smith, S. M., Kipnis, V., Dodd, K. W., Buckman, D. W., Tooze, J. A., Freedman, L. S. and Carroll, R. J. (2011). A new multivariate measurement error model with zero-inﬂated dietary data, and its application to dietary assessment. Annals of Applied Statistics, 5, 1456-1487. 9. Wang, L., Liu, X., Liang, H. and Carroll,R. J. (2011). Generalized additivepartial linear models— polynomial spline smoothing estimation and variable selection procedures. Annals of Statistics, 39, 18271851. 10. Ma, Y., Hart, J. D. and Carroll, R. J. (2011). Density estimation in several populations with uncertain population membership. Journal of the American Statistical Association, 106, 1180-1192. 11. Yi, G. Y. Y., Ma, Y and Carroll, R. J. (2012). A robust, functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error. Biometrika, 99, 151-165. 12. Wei, Y., Ma, Y.and Carroll, R. J. (2012). Multiple imputationin quantile regression. Biometrika, 99, 423-438. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4059083/ 13. Carroll, R. J., Midthune, D., Subar, A. F., Shumakovich, M., Freedman, L. S., Thompson, F. E. and Kipnis, V. (2012). Taking advantage of the strengths of two different dietary assessment instruments to improve intake estimates for nutritional epidemiology. American Journal of Epidemiology, 175, 340-347. 14. Kipnis, V., Midthune, D., Freedman, L. S. and Carroll, R. J. (2012). Regression calibration with more instruments than mismeasured variables. Statistics in Medicine, 31, 2713-2732.

224 15. Carroll, R. J., Delaigle, A. and Hall, P. (2012). Deconvolution when classifying noisy data involving transformations. Journal of the American Statistical Association, 106, 1166-1177. 16. Chen, Y.-H., Chatterjee, N. and Carroll, R. J. (2013). Using shared genetic controls in studies of gene- environment interactions. Biometrika, 100, 319-338. 17. Xun, X., Cao, J., Mallick, B. K., Maity, A. and Carroll, R. J. (2013). Parameter estimationofpartial differential equation models. Journal of the American Statistical Association, 108, 1009-1020. 18. Carroll, R. J., Delaigle, A. and Hall, P. (2013). Unexpected properties of bandwidth choice when smoothing discrete data for constructing a functional data classiﬁer. Annals of Statistics, 41, 27392767. 19. Li, Y., Wang, N. and Carroll, R. J. (2013). Selecting the number of principal components in functional data. Journal of the American Statistical Association, 108, 1284-1294. 20. Serban, N., Staicu, A.-M. and Carroll, R. J. (2014). Multilevel cross-dependent binary longitudinal data. Biometrics, 69, 903-913. 21. Guenther, P. M., Kirkpatrick, S. L., Reedy, J., Krebs-Smith, S. M., Buckman, D. W., Dodd, K. W. Casavale, K. O. and Carroll, R. J. (2014). Healthy Eating Index-2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans. Journal of Nutrition, to appear. 22. Sarkar, A., Mallick, B. K., Staudenmayer, J., Pati, D. and Carroll, R. J. (2014). Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors. Journal of Com- putational and Graphical Statistics, 25, 1101-1125. 23. Lian, H., Liang, H. and Carroll, R. J. (2014). Variance function partially linear single-index models. Journal of the Royal Statistical Society, Series B, 77, 171-194. 24. Ma, Y. and Carroll, R. J. (2015). Semiparametric estimation in the secondary analysis of case-control studies. Journal of the Royal Statistical Society, Series B, to appear. 25. Yi, G. Y., Ma, Y., Spiegelman, D. and Carroll, R. J. (2015). Functional and structural methods with mixed measurement error and misclassiﬁcation in covariates. Journal of the American Statistical Association, to appear. ii. Other Noteworthy Publications: 1. Ruppert, D., Wand, M. P. and Carroll, R. J. (2003). Semiparametric Regression. Cambridge University Press. 2. Carroll, R. J., Ruppert, D., Stefanski, L. A. and Crainiceanu, C. M. (2006). Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition. Chapman and Hall CRC Press. 3. Liang, F., Liu, C. and Carroll, R. J. (2010). Advanced Markov Chain Monte Carlo: Learning from Past Samples. Wiley, New York. ISBN: 978-0-470-74826-8.

Grants in last ﬁve years: 1. National Cancer Institute (CA-57030), support for basic research, Measurement Error, Nutrition and Breast-Colon Cancer, 1992-present (P.I.). Funded 2005-2015 via a MERIT Award. Renewed May 1, 2015. 2. National Cancer Institute (CA-90301), support for a training program in Biostatistics, Bioinformatics and the Biol- ogy of Nutrition and Cancer, 2001-present (P.I.). Funded through 2016. 3. King Abdullah University of Science and Technology (KAUST, P.I.): support for the funding of the Texas A&M University Institute of Applied Mathematics and Computational Science, 2008-2014. 4. National Science Foundation, co-investigator on Bayesian Data Mining Approaches for Biological Threat Detection (B. Mallick, P.I.), 2009-2012.

Awards and Honors (Selected): 1. Gottfried E. Noether Senior Scholar Award and Lecture, American Statistical Association, 2014 2. Elected Fellow, American Association for the Advancement of Science, 2014.

225 3. Honorary doctorate, Institut de Statistique, Universit Catholique de Louvain, 2012. 4. Mitchell Prize for Bayesian Statistics, 2003 (from the International Society for Bayesian Analysis). 5. Fisher Award and Lecture, 2002 (from COPSS) 6. Outstanding Achievement Award for Promoting Diversity, Texas A&M University, 1996. 7. Wilcoxon Prize, American Society for Quality Control, 1986. 8. COPSS Presidents’ Award (IMS, ASA, ENAR, WNAR, CSS), 1988. 9. 13 named lectures at universities Service (Selected): 1. Editor, Biometrics (1997-2001). 2. Editor, Journal of the American Statistical Association, Theory and Methods Section (1988-1990). 3. Founding Chair, NIH Study section on Biostatistics (BMRD), 2002-2004.

Students Supervised (From 43): 1. Leonard A. Stefanski (1983). Estimation for binary regression models. Professor, North Carolina State University (past editor of the Journal of the American Statistical Association). 2. Douglas Simpson (1985). Robust estimation for discrete data. Professor, University of Illinois (also department head). 3. Marie Davidian (December, 1986). Variance function estimation in regression. Professor, North Carolina State University (also past editor, Biometrics, past President of the American Statistical Association). 4. C. Y. Wang (August, 1993). Analysis of case-control studies. Full Member, Fred Hutchinson Cancer Research Center. 5. J. S. Morris (July, 2000). Statistical models for colon cancer cell mechanisms. Professor, M. D. Anderson Cancer Research Center. 6. Hua Liang (March, 2001). Semiparametric statistical methods and computation. Professor, George Washington University. 7. Tanya Apanasovich (June, 2004). Longitudinal and spatial methods in the analysis of Aberrant Crypt Foci in colon carcinogenesis. Associate Professor, George Washington University. 8. Veerabhadran Baladandayuthapani (June, 2005). Bayesian methods in Bioinformatics. Associate Professor, Uni- versity of Texas M. D. Anderson Cancer Center. 9. Yehua Li (June, 2006). Functional data analysis in biology. Associate Professor, Iowa State University. 10. Bo Li (August, 2006). Spatial statistics. Associate Professor, University of Illinois. 11. Arnab Maity (August, 2008). Semiparametric methods for repeated measures data. Assistant Professor, North Carolina State University. 12. Abhra Sarkar (May 2014). Bayesian analysis of high dimensional data. Postdoctoral fellow, Duke University. Post-Docs Supervised (From 19): 1. Helmut K¨uchenhoff, Professor, University of Munich 2. Danh V. Nguyen, Professor, University of California at Irvine 3. Ana-Maria Staicu, Assistant Professor, North Carolina State University 4. Anindya Bhadra, Assistant Professor, Purdue University 5. Tanya Garcia, Assistant Professor, Texas A&M School of Public Health

226 WILLA W CHEN

Education: New York University Statistics Ph.D (2000) New York University Statistics MS (1995) Appointments: Professor Department of Statistics, Texas A&M University 2012 – Present Associate Professor Department of Statistics,Texas A& M University 2007-2012 Assistant Professor Department of Statistics,Texas A& M University 2001-2007 Postdoc Watson Research Center, IBM 2000-2001 Publications: i. Last five years: 1. Chen W., Deo, R. and Yi, Y. (2013). Uniform Inference in Predictive Regression Models, Journal of Business & Economic Statistics 31, 525-533 2. Chen W. and Deo R. (2012). The Restricted Likelihood Ratio Test for Autoregressive Processes, Journal of Time Series Analysis 33, 325-339 3. Chen, W. (2010). Efficiency in Estimation of Memory, Journal of Statistical Planning and Inference 140, 3820-3840 4. Chen, W. and Deo, R. (2010). Weighted Least Squares Approximate Restricted Likelihood Estimation for Vector Autoregressive Processes, Biometrika 97, 231-237 5. Chen, W. and Deo, R. (2009). The Restricted LikelihoodRatio Test at the Boundary in Autoregressive Series, Journal of Time Series Analysis 30, 618-630 6. Chen, W. and Deo, R. (2009). Bias Reduction and LikelihoodBased Almost-Exactly Sized HypothesisTesting in Predictive Regressions using the Restricted Likelihood, Econometric Theory 25, 1143-1179 ii. Other Noteworthy Publications: 1. Chen, W., and Hurvich, C. (2008). Fractional Cointegration, Chapter in the Handbook of Financial Time Series, Springer 2. Chen, W., and Hurvich, C. (2006). Semiparametric Estimation of Fractional Cointegrating Subspaces, Annals of Statistics 27, 2939-2979 3. Chen, W. and Deo, R. (2006). Estimation of Mis-specified Long Memory Models,” Journal of Econometrics 134, 257–281 4. Chen, W., Hurvich, C. and Lu, Y.(2006). On the Correlation Matrix of the Discrete Fourier Transform and the Fast Solution of Large Toeplitz Systems For Long-Memory Time Series, Journal of the American Statistical Association 101, 812-821 5. Chen, W. and Deo, R. (2006). The Variance Ratio Statistic at Large Horizons, Econometric Theory 22, 206–234 6. Chen, W. and Deo, R. (2004). Power Transformations to Induce Normality and Their Applications, Journal of the Royal Statistical Society, Series B 66, 117–130 7. Chen, W. and Deo R. (2004). A Generalized Portmanteau Goodness-of-Fit Test for Time Series Models, Econometric Theory 20, 382–416

227 8. Chen, W. and Hurvich, C. (2003). Estimating Fractional Cointegration in the Presence of Polynomial Trends, Journal of Econometrics 117, 95–121 9. Chen, W. and Hurvich, C. (2003). Semiparametric Estimation of MultivariateFractional Cointegration, Jour- nal of the American Statistical Association 98, 629–642 10. Hurvich, C. and Chen W. (2000). An Efﬁcient Taper for Potentially Overdifferenced Long-Memory Time Series, Journal of Time Series Analysis 21, 155–180 11. Deo R. and Chen W. (2000). On the Integral of the Squared Periodogram, Stochastic Processes and Their Applications 85, 159–176

Grants in last five years: i. Last five years: 1. National Science Foundation, $143,047, ”Restriction likelihood in time series: Applications to moderate and near integrated autoregressions, conintegration, panel data and nonlinear time seires”, 2010-2014. ii. Other Noteworthy Grants: 1. National Science Foundation, $116,292, ”Long Memory Time Series Modelling: Computational and Statisti- cal Efficiency, Nonstationarity/Noninvertibility and Goodness of Fit”, 2006-2010. 2. National Science Foundation, $107,483, ”Fractional Cointegration, Data Tapering and Estimation of Misspec- ified Models in Long Memory Time Series”, 2003-2006.

Editorial Work:

Member of Editorial Boards: Journal of the American Statistical Association – T&M (2014-Present). Journal of Computational and Graphical Statistics (2009-Present). Electronic Journal of Statistics (2010-2013). Journal of the American Statistical Association – A&CS (2009-2012).

Students Supervised:

Priya Kohli (2012), Ph.D (Co-advised with M. Pourahmadi) Dissertation: Prediction of Stationary Random Fields.

228 DAREN B.H. CLINE

Education: Colorado State University Statistics Ph.D. (1983) Colorado State University Statistics M.S. (1980) Harvey Mudd College Mathematics B.S. (1978)

Appointments: Professor Department of Statistics, Texas A&M University 2002–2015 Assoc. Professor Department of Statistics, Texas A&M University 1990–2002 Asst. Professor Department of Statistics, Texas A&M University 1984–1990 Visiting Research Asst. Prof. Center for Stochastic Processes, Univ. of North Carolina 1986 Visiting Assistant Prof. Department of Statistics, University of British Columbia 1983–1984

Publications: i. Last Five Years: 1. (2015) Z. Yao, D.B.H. Cline and D. Loguinov, Unstructured P2P link lifetimes redux, to appear IEEE Trans. on Networking. 2. (2015) A. Banaei, D.B.H. Cline, C. Geoghiades and S. Cai, On asymptotic statistics for geometric routing schemes in wireless ad-hoc networks, to appear IEEE Trans. on Networking. 3. (2015) R. Kumar, D.B.H. Cline and P. Gardoni, A stochastic framework to model deterioration in engineering systems, Structural Safety to appear. 4. (2014) Z. Yao, D.B.H. Cline, X. Wang, and D. Loguinov, Unifying models of churn and resilience for unstructured P2P graphs, IEEE Trans. on Parallel and Distributed Systems 25, 2475–2485. 5. (2011) D.B.H. Cline, Irreducibility and continuity assumptions for positive operators with application to threshold GARCH models, Adv. Appl. Probab. 43, 49–76. 6. (2010) Z. Yao, D.B.H. Cline, and D. Loguinov, In-degree dynamics of large-scale P2P systems, ACM SIGMETRICS Performance Evaluation Review 38, 37–42. ii. Other Noteworthy Publications: 1. (2009) D.B.H. Cline, Thoughts on the connections between threshold time series models and dynamical systems. Exploration of a Nonlinear World: An Appreciation of Howell Tong's Contributions to Statistics, K.-S. Chan, ed., World Scientific, 165–181. 2. (2007) D.B.H. Cline, Stability of nonlinear stochastic recursions with application to nonlinear AR-GARCH models, Adv. Appl. Probab. 39, 462–491. 3. (2004) D.B.H. Cline and H.H. Pu, Stability and the Lyapounov exponent of threshold AR-ARCH models, Ann. Appl. Probab. 14, 1920–1949. 4. (1994) D.B.H. Cline, Intermediate regular and Π-variation, Proc. London Math. Soc. 68, 594–616. 5. (1988) R.J. Carroll and D.B.H. Cline, An asymptotic theory for weighted least squares with weights estimated by replication, Biometrika 75, 35–43.

Research Grants: i. Last Five Years: 1. National Science Foundation (Co-PI, with Dmitri Loguinov), total award $473,420 (my share $95,228), CSR: Small: Yesterday’s News: Theory of Staleness under Data Churn, 2013–2016. ii. Other Noteworthy Grants: 1. National Science Foundation (PI), Regular Variation: Analytic Approaches to Probability and Statistics, 1991– 1993. 2. National Science Foundation (Co-PI, with Tailen Hsing), Applications of Asymptotic Structures for Dependence, Distribution Tails and Characteristic Functions, 1990.

Awards and Honors: 1. James L. Madison Award, Statistics, Colorado State University. 2. The Association of Former Students Distinguished Teaching Award, College of Science, Texas A&M University. 1

229 Selected National, University and Department Service: 1. Promotion and Tenure Committee, Department of Statistics (various). 2. Graduate Curriculum Committee, Department of Statistics (various). 3. Workshop on Predictive Modeling, National Science Foundation (2007). 4. Faculty Advisor Council, College of Science (2002–2008). 5. Faculty Grievance Committee, College of Science (2001–2004). 6. Faculty Senate, Texas A&M University (1992–1994).

Students Supervised: i. Ph.D.: 1. (2014) Bo Wei (Co-chair with Sila Çetinkaya, Industrial and Systems Engineering), Stochastic Clearing Models with Applications in Shipment Consolidation. 2. (2003) Thomas R. Boucher, V-Uniform Ergodicity of Threshold Autoregressive Nonlinear Time Series. 3. (1995) Huay-min H. Pu, Recurrence and Transience for Autoregressive Nonlinear Time Series. ii. Most Recent M.S.: 1. (2013) Steven Jackson 2. (2012) Kaitlin Olmstead 3. (2008) Jie Li 4. (2006) Jessica Wickersham 5. (2004) Lian Liu 6. (2004) Bo Li

230 ALAN DABNEY

Education: University of Texas at Arlington Mathematics B.S. (1999) University of Washington Biostatistics M.S. (2001) University of Washington Biostatistics Ph.D. (2006)

Appointments: Associate Professor Department of Statistics, Texas A&M University 2011-Pres. Assistant Professor Department of Statistics, Texas A& M University 2006-2011

Publications: i. Last five years: 1. Ball, R.L., Feiveson, A.H., Schlegel, T.T., Starc, V., and Dabney, A.R. Predicting “heart age” using electrocardiography, Journal of Personalized Medicine, (2014), 4, 65-78. 2. Turner, S., and Dabney, A.R. A story-based simulation for teaching sampling distributions, Teaching Statistics, (2014), 37, 23-25. 3. Menon, R., Watson, S., Thomas, L., Allred, C., Dabney, A.R., Azcarate-Peril, M., and Sturino, J. Diet complexity and estrogen receptor β–status affect the composition of the murine intestinal microbiota, Applied and Environmental Microbiology, (2013), 79, 5763-5773. 4. Karpievitch, Y.V., Dabney, A.R., and Smith, R.D. Normalization and missing value imputation for label-free LC- MS analysis, BMC Bioinformatics, (2012), 13, S5. 5. Taverner, T., Karpievitch, Y.V., Polpitiya, A., Brown, J., Dabney, A.R., Anderson, G.A., and Smith, R.D. DanteR: An extensible R-based tool for quantitative analysis of –omics data, Bioinformatics, (2012), 28, 2404-2406. 6. Tekwe, C.D., Carroll, R.J., and Dabney, A.R. Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data, Bioinformatics, (2012), 28, 1998-2003. 7. Wang, X., Anderson, G.A., Smith, R.D., and Dabney, A.R. A hybrid approach to protein differential expression in mass spectrometry-based proteomics, Bioinformatics, (2012), 28, 1586-1591. 8. Stanley, J., Adkins, J.N., Slysz, G., Monroe, M., Purvine, S., Karpievitch, Y.V., Anderson, G.A., Smith, R.D., and Dabney, A.R. A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics, Analytical Chemistry, (2011), 83, 6135-6140. 9. Karpievitch, Y.V., Polpitiya, A., Adkins, J.N., Anderson, G.A., Smith, R.D., and Dabney, A.R. Mass spectrometry-based proteomics: Biological and technological aspects, Annals of Applied Statistics, (2010), 4, 1797-1823. ii. Other Noteworthy Publications: 1. Klein, G., and Dabney, A.R. The Cartoon Introduction to Statistics, Farrar, Straus, and Giroux, (2013).

Grants in last five years: i. Last five years: 1. National Institutes of Health, $1,805,862, “Epigenetics of the Aging Astrocyte: Implications for Stroke”, 2011- 2016, Role: Co-I. 2. American Cancer Society, $718,000, “Effects of Estrogen on Sporadic and Inflammation-Associated Colon Cancer”, 2011-2015, Role: Co-I. 3. U.S. Department of Agriculture, $9,750,000, “Integrated Program for Reducing Bovine Respiratory Disease Complex in Beef and Dairy Cattle”, 2011-2016, Role: Co-I. 4. National Science Foundation, $997,710, “UBM-Institutional: Integrated Undergraduate Research Experiences in Biological and Mathematical Sciences”, 2010-2015, Role: Co-I. ii. Other Noteworthy Grants: 1. Subcontract from Pacific Northwest National Laboratory, $350,000, “Statistical Methods for LC-MS Proteomics”, 2007-2009, Role: PI.

231 Awards and Honors: 1. TAMU Distinguished Achievement College-Level Award in Teaching from the Association of Former Students (2011). 2. TAMU College of Science Montague-Center for Teaching Excellence Scholar (2009).

Service: 1. 2014 Member, Undergraduate Program Committee, TAMU Department of Statistics. 2. 2012-2014 Member, M.S. Qualifying Exam Committee, TAMU Department of Statistics. 3. 2012 Member, Selection Committee, The Association of Former Students’ College-Level Teaching Awards. 4. 2012 Member, External Advisory Board, TAMU AgriLife Genomics and Bioinformatics Services (TAGS) Core. 5. 2011-2014 Member, TAMU Undergraduate Academic Appeals Panel.

Students Supervised:

Ph.D. Students:

Robyn Ball (2013), Ph.D., Texas A&M University Dissertation: Statistical Methods for High-Dimensional Biological Data.

Xuan Wang (2011), Ph.D., Texas A&M University Dissertation: Statistical Methods for the Analysis of Proteomics Data.

Post-Docs:

Carmen Tekwe, Texas A&M University, 2011-2013.

Yuliya Karpievitch, Texas A&M University, 2007-2010.

M.S. Students:

More than 15 M.S. students supervised, including many students in the Distance Learning program.

232 PAUL FREDERICK DAHM

Education: Iowa State University Distributed Studies (minors in Mathematics, Statistics & Physics) B.S. (1973) Iowa State University Statistics M.S. (1977) Iowa State University Statistics Ph.D. (1979)

Appointments: Professor Department of Statistics, Texas A& M University 1993-present Graduate Advisor Department of Statistics, Texas A& M University 1989-2014 Associate Professor Department of Statistics, Texas A& M University 1985-1993 IPA/Visiting Statistician Biostatistics Branch, National Cancer Institute 1988-1989 Assistant Professor Department of Statistics, Texas A& M University 1979-1985

Publications: i. Last five years: None ii. Manuscripts in revision or preparation: 1. Abdulsalam, F., Pittroff, W. and Dahm, P.F. Quantitative Simulation Model Evaluation. In revision. 2. Lu, M. and Dahm, P.F. Evaluation of trace-driven stochastic simulation models. (Working title) In preparation. 3. Lu, M. and Dahm, P.F. Tests for independence in the evaluation of stochastic simulation models. In preparation.

Grants in last five years: i. Last five years: None ii. Other Noteworthy Grants: 1. National Institute of Mental Health, “Partial Hospitalization of High Risk Suicidal Youth,” 1991-1993. (Collaborator) 2. National Institutes of Health, “NIH: Chromosomal Rearrangement Incorporation in Mammals,” 1993-1996. (Co Principal Investigator with I. M. Greenbaum) 3. United States Department of Agriculture, “Estimation of Growth Curves with U. S. Sheep Experiment Station Researchers,” 1998-1999. (Statistical Consultant) 4. Food and Agricultural Organization of the United Nations, $10,000, “Statistical Design and Analytical Support for the Afghanistan Livestock Census,” 2002-2005. (Statistical Consultant) 5. National Institutes of Health, $250,000, “Sex Steroids and TMJ Pain,” 2005-2009. (Collaborator)

Awards and Honors: 1. Texas A&M Association of Former Students College of Science Teaching Award (1992) 2. Texas A&M University International Excellence Award (2000) 3. Texas A&M Association of Former Students Distinguished Achievement Award in Student Relations (2001)

Service: Sessions Organized and Work at National and International Meetings: 1. Program Chair of General Methodology Sections of the Joint Statistical Meetings, Orlando, FL, 1987.

Students Supervised: (Listings are for Ph.D. Committees Chaired or Co-chaired only)

Yoshihiko Tsukuda (1985) (Chair) Dissertation: Asymptotic Expansions of the Distributions of Certain Test Statistics for the Slope in a Linear Functional Relationship.

Ed Miller (1987) (Co-chair) Dissertation: Inference for the Parameters of the Complete Symmetry Covariance Structure Model.

Jong-Duk Kim (1989) (Chair) Dissertation: Construction of Restricted D-Optimal Designs for Polynomial Regression Models.

233 Kyung Chang (1990) (Chair) Dissertation: Asymptotic Expansions of the Distributions of Studentized Test Statistics for the Slope Parameter in Simple Linear Structural Relationships.

Mahinda Karunaratne (1991) (Chair) Dissertation: Estimating the Odds Ratio under Double Sampling.

Anne Coleman (1995) Dissertation: Variance Components Estimation with Missing Cells.

Fayez Abdul-Salam (1995) (Chair) Dissertation: Small Sample Inference for the Structural and Functional Simple Linear Measurement Error Models.

Tony White (1998) (Chair) Dissertation: A PC Program for the Parameter Estimation of Nonlinear Growth Models with Unequally Spaced Correlated Observations.

Ann Olmsted (1999) (Chair) Dissertation: Algorithms Using Chi-squared and Other Goodness of Fit Tests to Identify a High-expectation Subset of Independent Poisson Random Variables, or a Subset of Multinomial Cells Having Relatively High Probabilities, with Applications in Chromosomal Fragile Site Identification.

Dan Gaile (2003) (Chair) Dissertation: Development of Statistical Tools with Applications in Radiation Hybrid and Linkage Mapping.

Chris Hintze (2005) (Chair) Dissertation: Modeling Correlation in Binary Count Data with Application to Fragile Site Identification.

Ming Lu (2014) (Chair) Dissertation: Investigation of Simple Linear Measurement Error Models (SLMEMs) with Correlated Data.

Rupa Kanchi (2014) (Co-chair) Dissertation: Recombination Studies and Development of QTL-targeted Tiled Introgression Libraries by Marker Assisted Backcrossing Across Four Maize Chromosomal Segments.

234 JEFFREY D. HART

Education: B.S., Mathematics, Southern Methodist University (1977) M.S., Statistics, Southern Methodist University (1979) Ph.D., Statistics, Southern Methodist University (1981) Appointments: Adjunct Professor Department of Biostatistics, M.D. Anderson Cancer Center 2007- Visiting Professor Department of Statistics, Limburgs Universitair Centrum 1997-98 Professor Department of Statistics, Texas A&M University 1994- Research Fellow Statistics Research Section, Australian National University 1989 Visiting Adjunct Associate Professor Department of Statistics, North Carolina State University 1989 Visiting Associate Professor Institut fur¨ Wirtschaftstheorie II, Universitat¨ Bonn 1988 Associate Professor Department of Statistics, Texas A&M University 1988-94 Assistant Professor Department of Statistics, Texas A&M University 1982-88 Assistant Professor Department of Mathematics, University of Arkansas 1981-82 Publications: i. Last five years: 1. Hart, J.D. (2009). Frequentist-Bayes lack-of-fit tests based on Laplace approximations. Journal of Statistical Theory and Practice 3 681-704. 2. Claeskens, G. and Hart, J.D. (2009). Goodness-of-fit tests in mixed models (with discussion). TEST 18 213-239. 3. Hart, J.D. (2009). Discussion of “Parametric Versus Nonparametrics: Two Alternative Methodologies,” by E.L. Lehmann. Journal of Nonparametric Statistics 21 411-413. 4. Park, B.-J. , Lord, D. and Hart, J.D. (2010). Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis. Accident Analysis and Prevention 42 741-749. 5. Savchuk, O.Y., Hart, J.D. and Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the American Statistical Association 105 415-423. 6. Savchuk, O.Y., Hart, J.D. and Sheather, S.J. (2010). An empirical study of indirect cross-validation. Nonpara- metric Statistics and Mixture Models – A Festschrift in Honor of Thomas P Hettmansperger (D.R. Hunter, D.S.P. Richards and J.L. Rosenberger, eds.), World Scientific 288-308. 7. Song, J. and Hart, J.D. (2010). Bootstrapping in a high-dimensional but very low sample size problem. Journal of Statistical Computation and Simulation 80 825-840. 8. Ma, Y., Hart, J.D., Janicki, R. and Carroll, R.J. (2011). Local and omnibus goodness-of-fit tests in classical measurement error models. Journal of the Royal Statistical Society, Series B 73 81-98. 9. Kim, J. and Hart, J.D. (2011). A change-point estimator using local Fourier series. Journal of Nonparametric Statistics 23 83-98. 10. Hart, J.D. and Canette,˜ I. (2011). Nonparametric estimation of distributions in random effects models. Journal of Computational and Graphical Statistics 20 461-478. 11. Ma, Y., Hart, J.D. and Carroll, R.J. (2011). Density estimation in several populations with uncertain population membership. Journal of the American Statistical Association 106 1180-1192. 12. Sun, Y., Hart, J.D. and Genton, M. (2012). Nonparametric inference for periodic sequences. Technometrics 54 83-96.

235 13. Savchuk, O., Hart, J.D. and Sheather, S.J. (2013). One-sided cross-validation for nonsmooth regression functions. Journal of Nonparametric Statistics 25 889-904. 14. Sun, Y., Hart, J.D. and Genton, M. (2013). Improved nonparametric inference for multiple correlated periodic sequences. Stat 2 197-210. 15. Zhan, D. and Hart, J.D. (2014). Testing equality of a large number of densities. Biometrika 101 449-464. 16. Gong, X., Gonzalez, R., McVay, D.A. and Hart, J.D. (2014). Bayesian probabilistic decline curve analysis reliably quantifies uncertainty in shale well production forecasts. SPE Journal 19 1047-1057. ii. Other Noteworthy Publications: 1. Hart, J.D. (1988). An ARMA type probability density estimator. Annals of Statistics 16 842-855. 2. Hall, P. and Hart, J.D. (1990). Bootstrap test for difference between means in nonparametric regression. Journal of the American Statistical Association 85 1039-1049. 3. Hart, J.D. and Vieu, P. (1990). Data-driven bandwidth choice for density estimation based on dependent data. Annals of Statistics 18 873-890. 4. Hart, J.D. (1991). Kernel regression estimation with time series errors. Journal of the Royal Statistical Society, Series B 53 173-187. 5. Eubank, R. L. and Hart, J.D. (1992). Testing goodness-of-fit in regression via order selection criteria. Annals of Statistics 20 1412-1425. 6. Hart, J.D. and Wehrly, T.E. (1993). Consistency of cross-validation when the data are curves. Stochastic Processes and their Applications 45 351-361. 7. Hart, J.D. (1994). Automated kernel smoothing of dependent data by using time series cross-validation. Journal of the Royal Statistical Society, Series B 56 529-542. 8. Eubank, R.L, Hart, J.D., Simpson, D. and Stefanski, L. (1995). Testing for additivity in nonparametric regression. Annals of Statistics 23 1896-1920. 9. Hart, J.D. (1997). Nonparametric Smoothing and Lack-of-Fit Tests. Springer-Verlag, New York. 10. Hart, J.D. and Yi, S. (1998). One-sided cross-validation. Journal of the American Statistical Association 93 620-631. 11. Aerts, M., Claeskens, G. and Hart, J.D. (1999). Testing the fit of a parametric function. Journal of the American Statistical Association 94 869-879. 12. Aerts, M., Claeskens, G. and Hart, J.D. (2004). Bayesian-motivated tests of function fit and their asymptotic frequentist properties. Annals of Statistics 32 2580-2615. 13. Hart, J.D. and Lee, C.-L. (2005). Robustness of one-sided cross-validation to autocorrelation. Journal of Multivariate Analysis 92 77-96. 14. Ma, Y. and Hart, J.D. (2007). Constrained local likelihood estimators for semiparametric skew-normal distributions. Biometrika 94 119-134. 15. Hart, J.D., Koen, C. and Lombard, F. (2007). An analysis of pulsation periods of long-period variable stars. Journal of the Royal Statistical Society, Series C 56 587-606.

Grants: i. Last ﬁve years: 1. National Science Foundation, $170,665, ”New Methodology for Estimating Random Effects and for Statistical Simulation Studies,” 2011-2015. (Sole P.I.) ii. Other Noteworthy Grants: 1. National Science Foundation, $97,000, “Cluster-Based Bootstrapping in Multiple Hypotheses Testing,” 2006- 2009. (Sole P.I.)

236 2. National Science Foundation, $80,000, “Model Selection and Tests of Model Fit,” 1999-2002. (Sole P.I.)

Awards and Honors: 1. Fellow of the Institute of Mathematical Statistics, 1994 2. Texas A&M University College of Science Distinguished Achievement Award in Teaching, 1995 3. Fellow of the American Statistical Association, 2001 4. Don Owen Award, 2007 5. Member of Editorial Boards: Journal of the American Statistical Association (2008-2011, 1996-2002) TEST (1997-2000) Probability Theory and Related Fields (1992-1993) Communications in Statistics (1991-1993) 6. Visiting Scholar: Department of Applied Mathematics and Statistics, Colorado School of Mines (November 2013) Department of Statistics, Limburgs University, Diepenbeek, Belgium (May 1999, June 2001) Departamento de Matematicas,´ Universidade da Coruna,˜ La Coruna,˜ Spain (February 1998) Institut de Statistique, Universite´ catholique de Louvain, Louvain-la-Neuve, Belgium (December 1997)

Service:

1. In 2014 organized session for Second International Society of Nonparametric Statistics Conference, Spain. 2. Chair, ASA Section on Nonparametrics, 2005. 3. Co-organizer of 2005 American Statistical Association Workshop entitled “Nonparametric Statistics: Frontier.” 4. Organized session for 2002 International Conference on Current Advances and Trends in Nonparametric Statistics, Crete, Greece.

Ph.D. Students Supervised (8 most recent of 21): 1. Beverly Gaucher (2013) “Factor Analysis for Skewed Data and Skew-Normal Maximum Likelihood Factor Analy- sis.” (Co-chair with Thomas E. Wehrly) 2. Ying Sun (2011) “Inference and Visualization of Periodic Sequences.” (Co-chair with Marc Genton) 3. Qi Wang (2011) “Frequentist-Bayes Goodness-of-ﬁt Tests.” 4. Olga Savchuk (2009) “Choosing a Kernel for Cross-Validation.” (Co-chair with Simon Sheather) 5. Nathaniel Litton (2009) “Deconvolution in Random Effects Models Via Normal Mixtures.” 6. Yi Qian (2005) “Topics in Multiple Hypotheses Testing.” 7. Juhee Song (2005) “Bootstrapping in a High Dimensional but Very Low Sample Size Problem.” 8. Suriani Pokta (2004) “Bayesian Model Selection Using Exact and Approximated Posterior Probabilities with Ap- plications to Star Data.”

237

KEITH HATFIELD

Education: University of Texas – Arlington BBA – Operations Research (1978) North Texas State University MBA – Operations Research (1980)

Professional Experience Hatfield Consulting Group Principal – 1996 to present R.J. Stanley & Associates, Inc. Senior Consultant – 1983 to 1999 Ebasco Business Consulting Consultant – 1981 to 1983

Appointments: Lecturer Department of Statistics, TAMU, Fall 2005 – present

Publications: None

Grants in last five years: None

Awards and Honors: None

Service: Coordinator of STAT 211 – Spring 2013 – present

238 JIANHUA HUANG

Education: University of California at Berkeley Statistics Ph.D. (1997) Beijing University, China Probabilityand Statistics M.A. (1992) Beijing University, China Probabilityand Statistics B.A. (1989) Appointments: Professor Department of Statistics, Texas A&M University 2008-Present Associate Professor Department of Statistics, Texas A&M University 2005-2008 Assistant Professor Department of Statistics, University of Pennsylvania 1997-2004 Research Expertise: Statistical learning, regularization methods, multivariate and high-dimensional data, functional and longitudinal data analysis, nonparametric and semiparametric methods, statistics application in astronomy, biology, business, economics and engineering

Publications: i. Last five years: (selected from 48 refereed journal publications) 1. Pourhabib, A., Huang, J. Z. and Ding, Y. (2015). Short-term wind speed forecast using measurements from multiple turbines in a wind farm. Technometrics, 57, to appear. 2. Xu, G., Wang, S. and Huang, J.Z. (2015). Nearly efficient robust estimation and inference based on focused information model averaging. Scandinavian Journal of Statistic, 42, to appear. 3. Zhang, B., Sang, H. and Huang, J. Z. (2015). Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets. Statistica Sinica, 25, 99–114. 4. Jung, Y., Huang, J. Z., Hu, J. (2014). Biomarker Detection in Association Studies: Modeling SNPs Simultane- ously via Logistic ANOVA. Journal of American Statistical Association, 109, 1355–1367. 5. L. Zhang, H. Shen, and J. Z. Huang (2013). Robust Regularized Singular Value Decomposition for Two-way Functional Data. Annals of Applied Statistics, 7, 540–1561. 6. Tian S. T., Huang, J.Z., Shen, H. and Li, Z. (2013). EEG/MEG Source Reconstruction with Spatial-temporal Two-Way Regularized Regression. Neuroinformatics, 11(4): 477–93. 7. Sang, H. and Huang, J. Z. (2012). A full-scale approximation of covariance functions for large spatial data sets. Journal of Royal Statistical Society, Series B, 74, 111–132. 8. J. Cao, J. Z. Huang, H. Wu (2012). Penalized nonlinear least squares estimation of time-varying parameters in ordinary differential equations. Journal of Computational and Graphical Statistics, 21, 42–56. 9. Tian S. T., Huang, J.Z., Shen, H. and Li, Z. (2012). A two-way regularization method for MEG source reconstruction. Annals of Applied Statistics, 6, 1021–1046. 10. Chen, L. and Huang, J.Z. (2012). Sparse reduced-rank regression for simultaneous dimension reduction and variable selection. Journal of American Statistical Association, 107, 1533–1545. 11. Xu, G. and Huang, J.Z. (2012). Asymptotic optimality and efficient computation of the leave-one-subject-out cross-validation. Annals of Statistics, 40, 2765–3175. 12. Hays, S., Shen, H. and Huang, J.Z. (2012). Functional dynamic factor models with application to yield curve forecasting. Annals of Applied Statistics, 6, 870–894. 13. Park, C., Huang, J.Z., Ji, J. and Ding, Y. (2012) Segmenting, inference and classification of partially overlapping nanoparticles. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 507–522.

239 14. C. Park, J. Z. Huang, Y. Ding (2011). Domain decomposition approach for fast Gaussian process regression of large spatial datasets. Journal of Machine Learning Research, 12, 1697–1728 15. H. Sang, M. Jun, J. Z. Huang (2011). Covariance approximation for large multivariate spatial datasets with an application to multiple climate model errors. Annals of Applied Statistics, 5, 2519–2548. 16. Lee, M., Shen, H., Huang, J. Z. and Marron J. S. (2010). Biclustering via sparse singular value decomposition. Biometrics, 66, 1087–1095. 17. Park C., Huang, J.Z. and Ding, Y. (2010). A computable plug-in estimator of minimum volume sets for novelty detection. Operations Research, 58, 1469–1480. 18. Lee, S., Huang, J.Z. and Hu, J. (2010). Sparse logistic principal components analysis for binary data. The Annals of Applied Statistics, 4, 1579–1601. 19. Cheng G. and Huang, J. Z. (2010). Bootstrap consistency for general semiparametric M-estimation. The Annals of Statistics, 38, 2884–2915. 20. Zhou, L., Huang, J. Z., Martinez, J.G., Maity, A., Baladandayuthapani, V. and Carroll, R. J. (2010). Reduced rank mixed effects models for spatially correlated hierarchical functional data. Journal of American Statistical Association, 105, 390–400. ii. Publications Before 2010: (selected from 28 refereed journal publications) 1. Huang, J. Z., Shen, H. and Buja, A. (2009). The analysis of two-way functional data using two-way regularized singular value decompositions. Journal of American Statistical Association, 104, 1609–1620. 2. Wang L., Li, H. and Huang, J. Z. (2008). Variable selection in nonparametric varying-coefﬁcient models for analysis of repeated measurements. Journal of American Statistical Association, 103, 1556–1569. 3. Zhou, L., Huang, J. Z. and Carroll, R. J. (2008). Joint modeling of paired sparse functional data using principal components. Biometrika, 95, 601–619. 4. Shen, H. and Huang, J. Z. (2008). Sparse principal component analysis via regularized low rank matrix approximation. Journal of Multivariate Analysis, 99, 1015–1034. 5. Shen, H. and Huang, J. Z. (2008). Interday forecasting and intraday updating of call center arrivals. Manufactur- ing & Service Operations Management, 10, 391–410. 6. Huang, J. Z., Liu, N., Pourahmadi, M., and Liu, L. (2006). Covariance selection and estimation via penalised normal likelihood. Biometrika, 93, 85–98. 7. Huang, J. Z. (2003). Local asymptotics for polynomial spline regression. The Annals of Statistics, 31, 1600–1635. 8. Huang, J. Z., Wu., C. O., Zhou, L. (2002). Varying coefﬁcient models and basis function approximations for the analysis of repeated measurements. Biometrika, 89, 111–128. 9. Huang, J. Z. (2001). Concave extended linear modeling: A theoretical synthesis. Statistica Sinica, 11, 173–197. 10. Huang, J. Z. (1998). Projection estimation in multiple regression with application to functional ANOVA models. The Annals of Statistics, 26, 242–272.

Grants in last five years: i. Last five years: 1. Texas A&M University–NSFC Joint Research Program (2014-2015), $25,000, “Statistical Machine Learning and Data Mining of the LAMOST Spectroscopic Survey,” (PI) 2. Air Force Office of Scientific Research (2013-2015),$611,152, “Dynamic, Data-Driven Modeling of Nanoparticle Self Assembly Processes,” (co-PI; PI: Yu Ding) 3. National Science Foundation (2012-2015), $225,104, “Collaborative Research: New Developments for Analysis of Two-way Structured Functional Data,” (PI) 4. King Abdullah University of Science and Technology (2012-2015), $275,000, “Computational and Statistical Approaches for Protein Structure Prediction and Determination,” (co-PI; PI: Xin Gao)

240 5. Institute for Applied Mathematics and Computational Science, Texas A&M University (2011-2012), $25,000, “Nonparametric Probabilistic Approach for Modeling the Local Protein Structure”, (PI) 6. National Science Foundation (2010-2014), $179,660, “A New Approach of Statistical Modeling and Analysis of Massive Spatial Data Sets,” (co-PI; PI: Huiyan Sang) 7. Institute of Applied Mathematics and Computational Science, Texas A&M University (2010-2011), $25,000, “Computationally Tractable Approximate Likelihood Inference for Irregularly Spaced Massive Spatial Data Sets,” (PI) 8. National Science Foundation (2009-2013), $262,106, “Statistical Methods for Complex Functional Data,” (co-PI; PI: Lan Zhou) ii. Other Noteworthy Grants: 1. National Science Foundation (2009-2010), $10,000, “Conference on Statistical Methods for Complex Data” (PI) 2. National Science Foundation (2006-2009), $99,165, “Collaborative Research: Statistical Learning and Object Oriented Data Analysis,” (PI) 3. National Science Foundation (2002-2005), $99,000, “Nonparametric and Semiparametric Methods for Longitu- dinal Data Analysis,” (PI)

Awards and Honors: 1. Best Application Paper for IIE Transactions (Quality/Reliability Engineering Focus Issue): Park, C., Huang, J. Z., Huitink, D., Kundu, S., Mallick, B., Liang, H. and Ding, Y. (2012) A Multi-stage, Semi- automated procedure for analyzing the morphology of nanoparticles. IIE Transactions Special issue on Nanomanufac- turing, 44, 507–522. 2. Fellow of the American Statistical Association 3. Fellow of the Institute of Mathematical Statistics 4. Member of Editorial Boards: STAT—The ISI’s Journal for the Rapid Dissemination of Statistics Research (2015-Present).

Service: 1. Member of National Science Foundation Review Panel, multiple times 2. Referee for more than 30 journals 3. Chair of 2012 ICSA Applied Statistics Symposium Student Paper Award Committee, 2012 4. Member of the Organizing Committee for “Conference on Resampling Methods and High Dimensional Data,” College Station, March 25-26, 2010 5. Member of the Organizing Committee for “Conference on Statistical Methods for Complex Data,” College Station, March 14, 2009

Ph.D. Students Supervised: Past Students (14): Linxu Liu (2004), Naiping Liu (2004), Liangyue Zhang (2004), Zhihua Qiao (2005), Min Chen (2008), Seokho Lee (2009), John Wagaman (2009), Saijuan Zhang (2010), Mehdi Maadooliat (2011), Chiwoo Park (2011), Huijun Pan (2011), Ganggang Xu (2011), Shuo Feng (2014), Yuan Qu (2014). Current Students (6): Bohai Zhang, Nan Zhang, Senmao Liu, Ya Su, Shiyuan He, Kejun He.

Post-Docs Supervised: Mehdi Maadooliat (2011-2013; Marquette University), Ganggang Xu (2012-2014; Binghamton University)

241 VALEN E. JOHNSON

Education: RensselaerPolytechnicInstitute Mathematics B.S.(1981) Universityof Texas at Austin Applied Mathematics M.S. (1985) The University of Chicago Statistics Ph.D. (1989) Appointments: Head Department of Statistics, Texas A& M University 2014-Pres. Professor Department of Statistics,Texas A& M University 2012-Pres. Ad InterimDivisionHead DivisionofQuantitativeSciences, MDAnderson Cancer Center 2011-2012 Deputy Chairman Department of Biostatistics,MD Anderson Cancer Center 2007-2010 Professor Department of Biostatistics,MD Anderson Cancer Center 2004-2011 Adjunct Professor Department of Statistics, Rice University 2005-2011 Adjunct Professor Department of Statistics, Texas A&M University 2007-2011 Technical Staff Member Los Alamos National Laboratory 2001-2002 Professor Instituteof Statistics and Decision Sciences,Duke University 2000-2003 Adjunct Professor Department of Statistics, University of North Carolina 1999-2002 Director of GraduateStudies Instituteof Statisticsand Decision Sciences,Duke University 2000-2001 Associate Professor Instituteof Statistics and Decision Sciences,Duke University 1993-2000 Director of Undergraduate Studies Instituteof Statistics and Decision Sciences,Duke University 1995-1999 Assistant Professor Instituteof Statistics and Decision Sciences,Duke University 1989-1993 Publications: i. Last ﬁve years (selected from 37 publications): 1. Hu, J. and Johnson, V.E. (2009), “Bayesian Model Selection Using Test Statistics,” Journal of the Royal Statistical Society. Series B, 71, 143-158. 2. Banerjee, K., Chabris, C.F., Johnson, V.E., Lee, J., Tsai, F., Hauser, M.D. (2009), “General Intelligence in Another Primate: Individual Differences across Cognitive Task Performance in a New World Monkey (Saguinus oedipus),” PLoS ONE, 4 (6): e5883.doi:10.1371/journal.pone.0005883. 3. Johnson, V.E. and Cook, J.D. (2009), “Bayesian Design of Single-Arm Phase II Clinical Trials with Contin- uous Monitoring,” Clinical Trials, 6, 217-226. 4. Hu, J. and Johnson, V.E. (2009), “Log-Linear Models for Gene Association,” Journal of the American Statis- tical Association, 104, 597-607. 5. Johnson, V.E. and Rossell, D. (2010), “On the use of non-local prior densities for default Bayesian hypothesis tests,” Journal of the Royal Statistical Society. Series B, 72, 143-170. 6. Cao, J., Moosman, A., and Johnson, V.E. (2010), “A Bayesian Chi-Squared Goodness of Fit Test for Censored Data Models,” Biometrics, 66, 426-434. 7. Wang, X.S., Cleeland, C.S., Mendoza, T.R., Yun, Y.H., Wang, Y., Okuyama, T., Johnson, V.E. (2010), “Im- pact of Cultural and Linguistic Factors on Symptom Reporting by Patients with Cancer,” Journal of the Na- tional Cancer Institute, 102, 732-738. 8. Johnson, V.E. (2010), “Bayesian Aggregation Error?,” International Journal of Safety and Reliability, 4, 359- 365. 9. Reese, C.S, Wilson, A.G., Guo, J., Hamada, M., and Johnson, V.E., (2011), “A Bayesian Model for Integrating Multiple Sources of Lifetime Information in System-Reliability Assessments,” Journal of Quality Technology, 43, 127-141.

242 10. Johnson, V.E. and Rossell, D. (2012), “Bayesian Variable Selection in High-dimensional Settings,” Journal of the American Statistical Association, 107, 649-660. 11. Yuan, Y. and Johnson, V.E. (2012), “Goodness-of-fit diagnostics for Bayesian hierarchical models,” Biomet- rics, 68, 156-164. 12. Amici, F., Barney, B., Johnson, V.E., Cail, J., and Aurelli, F. (2012), “A Modular Mind? A Test Using Individual Data from Seven Primate Species,” PLoS ONE, e51918. doi:10.1371/journal.pone.0051918. 13. Johnson V.E. (2013), “Uniformly most powerful Bayesian tests,” Annals of Statistics, 41, 1716-1741 14. Johnson, V.E. (2013), “Revised standards for statistical evidence,” Proceedings of the National Academy of Sciences, 110(48), 19313-19317. 15. Cai, C., Yuan, Y., and Johnson, V.E. (2013), “Bayesian Adaptive Phase II Screening Design for Combination Trials,” Clinical Trials, 10, 353-362. 16. Johnson, V.E. (2013), “On Numerical Aspects of Bayesian Variable Selection in High and Ultrahigh Dimen- sional Settings,” Bayesian Analysis, 7, 1-18. 17. Liu S., Yuan Y., Castillo R., Guerrero T., and Johnson V.E. (2014), “Evaluation of Image Registration Spatial Accuracy Using a Bayesian Hierarchical Model,” Biometrics, 70(2), 366-377. 18. Jun M., Katzfuss M., Hu J.and Johnson V.E. (2014), “Assessing fit in Bayesian models for spatial processes,” Environmetrics, 25(8), 584-595. 19. Barney B., Amici F., Aureli F., Call J. and Johnson, V.E. (2015), “Joint Bayesian Modeling of Binomial and Rank Data for Primate Cognition,” Journal of the American Statistical Association, in press. ii. Other Noteworthy Publications (selected from over 100 peer-reviewed publications): 1. Johnson, V.E. and Albert, J. (1999), Ordinal Data Models, Springer-Verlag: New York. 2. Johnson, V.E. (2003), Grade Inflation: A Crisis in College Education. Springer-Verlag, New York. 3. Johnson, V.E. (1994), “A Model for Segmentation and Analysis of Noisy Images,” Journal of the American Statistical Association, 89, 230-241. 4. Johnson, V.E. (1996), “Studying Convergence of Markov Chain Monte Carlo Algorithms Using Coupled Sampling Paths,” Journal of the American Statistical Association, 91, 154-166. 5. Johnson, V.E. (1996), “On Bayesian Analysis of Multirater Ordinal Data: An Application to Automated Essay Grading,” Journal of the American Statistical Association, 91, 42-51. 6. Johnson, V.E. (1998), “A Coupling-Regeneration Scheme for Diagnosing Convergence in Markov Chain Monte Carlo Algorithms,” Journal of the American Statistical Association, 93, 238-248. 7. Johnson, V.E., Deaner, R.O. and van Schaik, C.P. (2002), “Bayesian Analysis of Multi-StudyRank Data with Application to Primate Intelligence Ratings,” Journal of the American Statistical Association, 8-17. 8. Johnson, V.E. (2004), “A Bayesian χ2 Test for Goodness-of-Fit,” Annals of Statistics, 32, 2361-2384. 9. Johnson, V.E. (2005), “Bayes Factors Based on Test Statistics,” Journal of the Royal Statistical Society, Series B, 67(5), 689-701. 10. Johnson, V.E. (2008), “A Statistical Analysis of the NIH Peer Review System,” Proceedings of the National Academy of Sciences, 105 (32), 11076-11080.

Grants in last ﬁve years: i. Last ﬁve years: 1. Principal Investigator, “Consistent Model Selection in the p n Setting,” NIH R01, 2011-2015. 2. Biostatistics Core Director, “Symptom Mechanisms of Multiple Myeloma and Its Therapy,” (Principal Inves- tigator: Charles Cleeland), NIH P01, 2008-2013.

243 3. Collaborating Investigator, “Reducing the Symptom Burden Produced by Aggressive Cancer Therapies,” Prin- cipal Investigator: Charles Cleeland), NIH R01, 2008-2011. 4. Collaborating Investigator, “Statistical methods for genomic analysis of heterogeneous tumors,” (Principal Investigator: Wenyi Wang), NIH R01, 2015-2019. ii. Other Noteworthy Grants: 1. Principal Investigator, NIH Center for Scientific Review Intergovernment Personnel Agreement “Analysis of Scientific Review Group Ratings,” 2005-2006. 2. Principal Investigator, Los Alamos National Laboratory Contract in response to proposal 58947-SOL-02, “Bayesian Methodology for Reliability Analyses,” 2002. 3. Principal Investigator, NSF grant “Discrete Models for High-Level Image Analysis,” 1998-2001. 4. Principal Investigator, NSF grant“Scientific Computing Research Environment for Mathematical Sciences,” 1995. 5. Principal Investigator, NIH FIRST Award “Reconstruction and Analysis of Emission Computed Tomography Data,” 1992-1997.

Awards and Honors: 1. Fellowships: Elected member of the International Statistical Institute (ISI) Fellow of the American Statistical Association Fellow of the Royal Statistical Society 2. Member of Editorial Boards and Award Committees: Co-Editor, Bayesian Analysis, 2010-2014 Associate Editor, J. of the American Stat. Assoc. (JASA) (1992-1996, 2011-Present) Associate Editor, Bayesian Analysis (2006-2010) Associate Editor, IEEE Transactions on Medical Imaging, 1993-2002 Chair, Lindley Award Committee, 2008 Char or Member, Savage Award Committee, 2004-2007 Treasurer, International Society for Bayesian Analysis, 1998-2001 Savage Award for Outstanding Thesis in Bayesian Statistics and Econometrics, 1989

Doctoral Students Supervised: 1. Alyson Wilson, “Statistical Models for Shapes and Deformations,” 1995. Alyson won the Savage Award for the best thesis in Bayesian statistics and econometrics. 2. Colin McCulloch, “High-level Image Understanding Through Bayesian Hierarchical Models,” 1998. Colin was one of four finalists for the 1999 Savage Award. 3. Jacob Laading, “Practical Methodologyfor Inclusion of Modality-SpecificModifications in a Hierarchical Bayesian Deformation Model,” 1999. 4. Stephen Ponisciak, “Bayesian Analysis of Teacher Effectiveness,” 2002. 5. Sining Chen, “On Automated Bayesian Image Analysis,” 2002. 6. Adarsh Joshi, “Bayesian Model Selection for High-Dimensional High-Throughput Data,” Department of Statistics, Texas A&M University, 2010 (while a faculty member at M.D. Anderson Cancer Center). 7. Brad Barney, “Bayesian Joint Modeling of Binomial and Rank Response Data,” Department of Statistics, Texas A&M University, 2011 (while a faculty member at M.D. Anderson Cancer Center). 8. Scott Goddard, “Restricted Most Powerful Bayesian Tests,” Department of Statistics, Texas A&M University.

244 EDWARD R. JONES

Education: Texas A&M University – Commerce Computer Science B.S. w/honors (1972) Virginia Polytechnic & State Univ. Statistics M.S. (1974) Virginia Polytechnic & State Univ. Statistics Ph.D. (1976)

Appointments: 2010-Pres Executive Professor Dept. of Statistics, Texas A&M University 2008-2010 Senior Statistician Stata, Inc., College Station, TX 2002-2008 Senior Statistical Advisor Visual Numerics, Inc., Houston, TX 1992-2003 Assoc. Professor Dept. of Math. & Computer Sci., Texas A&M University-Corpus Christi 1985-1989 Vice President Jones Reilly & Assoc., Cupertino, CA 1984-1985 Dir. of Consulting Enhansys, Inc., Cupertino, CA 1977-1984 Senior Statistician Chevron Research Company, Richmond, CA 1975-1977 Asst. Professor Dept. of Statistics, Texas A&M University

Presentations and Workshops: Past 2 years i. Invited 1. Presentation for IAMCS Machine Learning on Text Analytics, Feb 4, 2014 2. 2-day Workshop – Econometrics using Stata, Aug 21-22; Mexico City

ii. Contributed 1. Half-Day Workshops 2. Text Analytics - CSP-2014, Tampa, FL; Feb 20, 2014 3. Text Analytics - SESUG, Myrtle Beach, NC; Oct 19, 2014 4. Text Analytics - SCSUG, Austin, TX; Nov 12, 2014 5. Text and Social Media Analysis – CSP-2015, New Orleans, LA; Feb 21, 2015.

iii. Papers 1. Text Analytics using High Performance SAS, MWSUG, Chicago, IL; Oct 7, 2014 2. Text Analytics – Today and Tomorrow, INFORMS 2014, San Francisco, CA, Nov 10, 2014.

Grants in last five years: i. University Grants – Submitted (co-investigator) 1. (2013) 2 submitted for $32,222 2. (2014) 3 submitted for $325,514 3. (2015) 1 submitted for $137,555 ii. Contracts 1. (2012-2015) Dept. of Veterans Affairs ($21,600/Yr) 2. (2014) Capital One ($59,000) 3. (2015-2018) Dept. of Treasury ($199,000 over 3 years)

Awards and Honors: Please annotate as space allows i. 2014 – Mentored 1st and 3rd place teams in Capital One Modeling Competition ii. 2012 – Mentored 1st and 2nd place team in Capital One Modeling Competition iii. (2015-2017) Elected Director on the Executive Committee, ASA Section on Statistical Consulting iv. 2013 – Text Analytics Workshop selected for sponsorship by ASA Board of Directors

Service: Please annotate as space allows Sessions Organized and Work at National Meetings of the American Statistical Association (ASA)

245 i. Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2014 – Orlando, FL. ii. Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2015 – New Orleans, CA. iii. Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2016 – San Diego, CA.

Students Supervised (2014-2016): i. MS expected in 2016 1. Cindy Czako 2. Giewee Hammond 3. Ziad Katrib 4. Yoel Kluk 5. Pablo Ormachea

ii. MS expected in 2015 1. William C. Dean 2. Aaron D. Agnew 3. Salsawit Shifarraw 4. Katrina Williams 5. James M. Bergeron 6. Steve J. Bowden 7. Lauren Engle 8. Danny Leonard 9. Erin Parrott 10. Bora Tarhan 11. Bryce Durgin

iii. MS graduated in 2014 1. Kurt B. Johnson* 2. Shiva S. Dhandapani 3. Wenling Zhang 4. Qian Zhou 5. Colm Walsh* 6. James Joseph*

*Committee chair or co-chair

Collaboration with TAMU System Researchers (Fall 2014 – Spring 2015) 1. (2015-) Sakhila, Banu, – Dept. of Veterinary Integrative Biosciences 2. (2015-) Snider, Erin, – TAMU Bush School of Government 3. (2014-) Bevans, John, DVM – College of Veterinary Medicine and Central Texas Specialty Hospital 4. (2014) Goldberg, – Dept. of Geography (GIS Study for Cervical Cancer in New Mexico) 5. (2014) Masabni, Joseph, – Dept. of Horticultural Sciences 6. (2014) Morris, Theresa, – Dept. of Sociology 7. (2014) Moyna, Irene, – Dept. of Hispanic Studies 8. (2014) Goldberg, Daniel – Dept. of Geography, College of Geosciences 9. (2014) Lacey, Ron and Faulkner, Brock – AgriLife College Station 10. (2014) Swiger, Sonja, – AgriLife Stephenville, TX 11. (2014) Keith, Verna, M. – Dept. of Sociology 12. (2014) Taylor, Lori, – Dept. Educational Administration

246 MIKYOUNG JUN

Education: Seoul National University Statistics B.S. (1999) UniversityofChicago Statistics Ph.D.(2005) Appointments: Associate Professor (with Tenure) Department of Statistics, Texas A&M University Sep 2012 - Present. AdjunctAssociate Professor Department of Biostatistics,UT MD Anderson Cancer Center Sep 2012- Aug2013 Assistant Professor Department of Statistics, Texas A&M University Aug 2005 - Aug 2011 AdjunctAssistant Professor Department of Biostatistics,UT MD Anderson Cancer Center Apr 2012 - Aug 2012 Visiting Scientist National Center for Atmospheric Research Aug 2005 - Dec 2005 Publications: i. Last five years: 1. Jun, M., Szunyogh, I., Genton, M.G., Zhang, F., Bishop, C.H. (2011). A statistical investigation of the sensitivity of ensemble based Kalman filters to covariance filtering. Monthly Weather Review, Volume 139, pp. 3036-3051. 2. Jun, M. (2011). Nonstationary cross-covariance models for multivariate processes on a globe. Scandinavian Journal of Statistics, Vol 38, pp. 726-747. 3. Sang, H., Jun, M., Huang, J.Z. (2011). Covariance approximation for large multivariate spatial datasets with an application to multiple climate model errors. Annals of Applied Statistics, Volume 5, pp. 2519-2548. 4. Vaughan, A., Jun, M., Park, C. (2012). Statistical inference and visualization in scale-space for spatially dependent images. Journal of Korean Statistical Society, Volume 41, pp. 115-135. 5. Jun, M., Genton, M.G. (2012). A test for stationarity of spatio-temporal random fields on planar and spherical domains. Statistica Sinica, Volume 22, pp. 1737-1764. 6. Park, S., Navratil, S., Gregory, A., Bauer. A., Srinath, I., Jun, M., Szonyi, B., Nightingale, K., Anisco, J., Ivanek, R. Generic Escherichia coli contamination of spinach at the preharvest level: The role of farm management and environmental factors. Applied and Environmental Microbiology, Volume 79, pp. 4347- 4358. 7. Jun, M., Park, E.S. (2013). Multivariate receptor modeling for spatially correlated multi-pollutant data. Tech- nometrics, Volume 55, pp. 309-320. 8. Roh, S., Genton, M.G., Jun, M., Szunyogh, I., Hoteit, I. (2013). Observation Quality Control with a Robust Ensemble Kalman Filter. Monthly Weather Review, Volume 141, pp. 4414-4428. 9. Park, S., Navratil, S., Gregory, A., Bauer, A., Srinath, I.,Szonyi, B., Nightinglgale, K., Ancisco, J., Jun, M., Han, D., Lawhon, S., Ivanek, R. (2014). Farm management, environment and weather factors jointly affect the probability of spinach contamination with generic Escherichia Coli at the preharvest level. Applied and Environmental Microbiology, Volume 80, pp. 2504-2515. 10. Jun, M. (2014). Matérn-based nonstationary cross-covariance models for global processes. Journal of Multi- variate Analysis, Volume 128, pp. 134-146. 11. Jun, M., Katzfuss, M., Hu, J. and Johnson, V.E. (2014). Assessing fit in Bayesian models for spatial processes. Environmetrics, Volume 25, pp. 584-595. 12. Jeong, J., Jun, M.. (2015). A class of Matérn-like covariance functions for smooth processes on a sphere. Spatial Statistics, Volume 11, pp. 1-18.

247 13. Park, S., Navratil, S., Gregory, A., Bauer, A., Srinath, I., Szonyi, B., Nightingale, K., Anciso, J., Jun, M., Han, D., Lawhon, S., and Ivanek, R.. (2015+). Count of generic Escherichia coli on spinach at the preharvest level determined by the interplay of ambient temperature, precipitation, farm management and environmental factors. Applied and Environmental Michro Biology, Accepted. ii. Other Noteworthy Publications: 1. Jun, M. (2011). Discussion of “An explicit link between Gaussian fields and Gaussian Markov random fields: The stochastic partial differential equation approach” by Finn Lindgren, H˚avard Rue and Johan Lindström. Journal of the Royal Statistical Society, Series B, 73, p. 478. 2. Jun, M., Stein, M.L. (2008). Nonstationary covariance models for global data. Annals of Applied Statistics, Volume 2, pp. 1271-1289. 3. Jun, M., Knutti, R., Nychka, D.W. (2008). Spatial Analysis to Quantify Numerical Model Bias and Depen- dence: How Many Climate Models Are There? Journal of the American Statistical Association, Volume 103, pp. 934-947. 4. Jun, M., Knutti, R., Nychka, D.W. (2008). Local eigenvalue analysis of CMIP3 climate model errors. Tellus, 60A, pp. 992-1000. 5. Jun, M., Stein, M.L. (2007). An Approach to Producing Space-time Covariance Functions on Spheres. Tech- nometrics, Volume 49, No. 4, pp. 468-479. 6. Jun, M., Stein, M.L. (2004). Statistical Comparison of Observed and CMAQ Modeled Daily Sulfate Levels. Atmospheric Environment, Volume 38, Issue 27, pp. 4427-4436.

Grants in last ﬁve years:

1. National Science Foundation, $100,000, “In-depth development and assessment of covariance models for multivariate nonstationary processes on a sphere”, (sole-) PI, 2012-2015. 2. National Science Foundation, $75,000, “Nonstationary spatial-temporal covariance models for multivariate processes on a globe”, (sole-) PI, 2009-2012. 3. National Science Foundation, $1,030,000, “Non-Gaussian statistical analysis of large climate datasets and simulations”, co-PI, 2006-2010. 4. KAUST GRP Award, $1,250,000, Investigator, 2008-2013.

Awards and Honors:

1. Elected member of the International Statistical Institute (ISI) 2. Member of Editorial Boards: STAT, (2012-Present). Journal of Agricultural, Biological, and Environmental Statistics. (JABES) (2011-Present). Journal of the Korean Statistical Society. (2008-Present). 3. VisitingScholar: Institute for Applied Mathematics, University of Heidelberg, October-December 2013. Department of Statistics, Seoul National University, June-September 2013. Center for Integrating Statistical and Environmental Science, University of Chicago, Summer 2006 & June-September 2007.

Service: Sessions Organized and Work at National and International Meetings: 1. Program committee for JSM, Seattle, 2015.

248 2. Short course committee for ICSA-KISS joint meeting, Portland, 2014. 3. Program committee for ICSA-KISS joint meeting, Portland, 2014. 4. Co-organizer of summer school in Data Assimilation, NCAR, 2015. 5. Co-organizer of a workshop on spatial statistics, Texas A&M University, 2015. 6. Co-organizer of the workshop on Statistical methods for Climate problem, IAMCS, Texas A&M University, 2012. 7. Co-organizer of the workshop on Data assimilation in the Geosciences, IAMCS, Texas A&M University, 2009. 8. Scientiﬁc advisory board, Spatial Statistics 2013 conference, June 2013. 9. Organizer of invited session: JSM 2015, 3rd IMS-APRM 2014, ISI WSC 2013, IMS-APRM 2012, ENAR 2011, 12th International Conference on Statistics, Combinatorics, Mathematics and Applications 2005 10. Organizer of invited poster session for JSM 2015 11. Organizer of a topic-contributedsession (or special topic session): JSM 2014, ISBA 2012, JSM 2010, 12. ASA/ENVR student award committee for JSM, 2006 - 2008. Other nothworthy service: 1. Node director, STATMOS, 2014-Present. 2. Associate Director, Program in Spatial Modeling, Department of Statistics, Texas A&M University, 2009-2012. 3. National Science Foundation review panel 2012.

Courses taught: STAT 211 (Principle of statistics I) (undergraduate) STAT 647 (Spatial statistics) (graudate, on-campus course as well as a course for business analytics program) STAT 685 (ATMO 685) (graduate, joint course with ATMO)

Students Supervised:

Soojin Roh (2014), Ph.D, Texas A&M University (jointly with Marc Genton) Dissertation: Robust Ensemble Kalman Filter and Localization for Multiple State Variables

Robert Philbin (2014), M.S, Texas A&M University Forrest Womack (2014), M.S, Texas A&M University Paul Reed (2012), M.S, Texas A&M University Justin Chown (2011), M.S, Texas A&M University (jointly with Mike Sherman)

Post-Docs Supervised: Dr. Myoungji Lee, Texas A&M University, 2012-2014. (jointly with Marc Genton)

249 MATTHIAS KATZFUSS

Education: The Ohio State University Statistics M.S. (2008) The Ohio State University Statistics Ph.D. (2011) Appointments: Assistant Professor Texas A&M University 2013-Pres. Akademischer Rat auf Zeit (Postdoc) Universität Heidelberg 2011-2013 Refereed Publications: i. Last five years: 1. Jun, M., Katzfuss, M., Hu, J., and Johnson, V.E. 2014. Assessing fit in Bayesian models for spatial processes. Environmetrics, 25(8), 584–595. 2. Gneiting, T., and Katzfuss, M. 2014. Probabilisticforecasting. Annual Review of Statisticsand its Application, 1, 125–151. 3. Heaton, M.J., Katzfuss, M., Berrett, C., and Nychka, D.W. 2014. Constructing valid spatial processes on the sphere using kernel convolutions. Environmetrics, 25(1), 2–15. 4. Nguyen, H., Katzfuss, M., Cressie, N., and Braverman, A. 2014. Spatio-temporal data fusion for remote- sensing applications. Technometrics, 56(2), 174–185. 5. Katzfuss, M. 2013. Bayesian nonstationary spatial modeling for very large datasets. Environmetrics, 24(3), 189–200. 6. Katzfuss, M., and Cressie, N. 2012. Bayesian hierarchical spatio-temporal smoothing for very large datasets. Environmetrics, 23(1), 94–107. (Student Paper Award, First Place, ASA Section on Statistics and the Environment) 7. Katzfuss, M., and Cressie, N. 2011. Spatio-temporal smoothing and EM estimation for massive remote- sensing data sets. Journal of Time Series Analysis, 32(4), 430–446. 8. Heaton, M.J., Katzfuss, M., Ramachandar, S., Pedings, K., Gilleland, E., Mannshardt-Shamseldin, E., and Smith, R. 2011. Spatio-temporal models for large-scale indicators of extreme weather. Environmetrics, 22(3), 294–303.

Grants in last ﬁve years: i. Last ﬁve years: 1. Visiting Researcher Grant ($13,156) at the National Center for Atmospheric Research (NCAR), awarded by the Research Network for Statistical Methods for Atmospheric and Oceanic Sciences (2015)

Awards and Honors:

1. Poster Award, Fifth IMS–ISBA Joint Meeting, Chamonix, France (2014) 2. Young Investigator Travel Award ($550), Fifth IMS–ISBA Joint Meeting (2014) 3. Student Paper Award, First Place ($1,000), American Statistical Association, Section on Statistics and the Environ- ment (2011)

250 4. Ransom & Marian Whitney Award for Best Dissertation Research ($400), Department of Statistics, The Ohio State University (2011) 5. Young Investigator Travel Award ($650), Fourth IMS–ISBA Joint Meeting (2011) 6. Ransom & Marian Whitney Award for Outstanding Research Associate ($150), Department of Statistics, The Ohio State University (2010) 7. Edward G. Mayers Travel Fellowship ($1,000), Division of Natural and Mathematical Sciences, The Ohio State University (2010) 8. Edward J. Ray Travel Award for Scholarship and Service ($750), Council of Graduate Students, The Ohio State University (2010) 9. Fulbright Scholarship (2007 – 2008) 10. German Academic Exchange Service (DAAD) Semester Scholarship (2007)

Service:

1. Organizing Committee for the Workshop on Spatial Statistics at Texas A&M University (2015) 2. Committees at Department of Statistics, Texas A&M University Faculty Recruitment Committee (2014 – 2015) Department Advisory Committee (2014 – 2015) Website Redesign Committee (2014) 3. Session Organizer, “Spatial Statistics for Big Environmental Datasets” (Invited Session), Joint Statistical Meetings, Montr´eal, Canada (2013) 4. Session Organizer, “Spatial Statistics for Very Large Environmental Data Sets” (Topic-Contributed Session), Joint Statistical Meetings, San Diego, CA (2012) 5. Student-Body President, Department of Statistics, OSU (2009 – 2011) 6. Member, Student Advisory Board, Wiley Series in Probability and Statistics (2009 – 2011)

Students Supervised: Jaehong Jeong (2015 (expected)), Texas A&M University: Committee Member (main advisor: Mikyoung Jun) Patrick Schmidt (2013), Master’s, Universit¨at Heidelberg (with Tilmann Gneiting): “Estimation of loss functions” (2013)

251 ELIZABETH YOUNG KOLODZIEJ

Education: University of Georgia Statistics B.S. (2003) University of Georgia Statistics M.S. (2005) Texas A&M University Statistics Ph.D. (2010)

Appointments: Instructor Department of Mathematics, Robert Morris University Fall 2010-Spring 2012 Senior Lecturer Department of Statistics, Texas A&M University Summer 2012-Present

Presentations: Panel Member, “Analytics and Big Data Survey Review and Interpretation: Panel and Audience Discussion,” Conference on Statistical Practice, American Statistical Association, 2015

Awards and Honors: Distinguished Graduate Student Award for Excellence in Teaching 2010 Fellow, Graduate Teaching Academy 2009 Graduate Merit Fellowship, Texas A&M University 2005 Outstanding Graduate Student Teaching Award, University of Georgia 2005

Service: Member, Undergraduate Degree Committee 2014-2015

Students Supervised:

Committees served on:

1. Kishan Raj (2015 - pending), M.S., INEN 2. Zhou Wang (2015 - pending), M.S., ELEN 3. Teresa Barnett (2015 - pending), M.S., STAT 4. Jonathan Presto (2015 - pending), M.S., STAT 5. Daniela Sakamoto (2015 - pending), M.S., STAT 6. Jeremy Fergason (2015 - pending), M.S., STAT 7. Jin Do (2015 - pending), M.S., STAT 8. Nicholas Darschewski (2015 - pending), M.S., STAT 9. Ulagappa Abinaya (2014), M.S., INEN 10. Kenneth Reed (2014), M.S., MATH 11. Yonatan Negash (2013), M.S., STAT

252

HWA CHI LIANG

Education: Soochow University, Taiwan Business Mathematics B.A. (1979) University of Texas at Austin Mathematics M.A. (1987) University of New Mexico Statistics Ph.D. (2003)

Appointments: Senior Lecturer Department of Statistics, Texas A&M University Fall, 2014 – Pres. Associate Professor Department of Mathematics & Statistics, Washburn University 2010 – 2014 Assistant Professor Department of Mathematics & Statistics, Washburn University 2004 – 2010

Publications: none in the past 5 years

Grants in last five years: none

Collaboration Currently collaborate with Professor Jenn-Tai Liang at the Department of Petroleum Engineering, Texas A&M University in developing proposals that involve statistical applications for research in petroleum engineering.

Awards and Honors: Member of Editorial Boards: Missouri Journal of Mathematical Sciences (MJMS) (2013-Present).

Service: Washburn University Service Record (2004 – 2014)

Supervisor of Math Tutor Center Evaluation committee for the Dean of College of Arts and Sciences Faculty Senate Mentor for new faculty College Faculty Council (CFC) The CFC Curriculum subcommittee The Interdisciplinary Studies Committee

Students Supervised:

253 JAMES P. LONG

Education: Columbia University, New York, USA Statistics and Mathematics B.A. (2008) University of California, Berkeley, USA Statistics Ph.D. (2013) Appointments: Assistant Professor Department of Statistics, Texas A&M University 2013-Pres.

Publications: i. Last five years: 1. (with A. N. Morgan, J. W. Richards, T. Broderick, N. R. Butler, J. S. Bloom) Rapid, machine-learned resource allocation: Application to high-redshift GRB follow-up. The Astrophysical Journal (2012) 746, 170. 2. (with J.S. Bloom, N. El Karoui, J. Rice, J.W. Richards) Classification of poorly time sampled light curves of periodic variable stars. Book chapter in Astrostatistics and Data Mining (2012) 2, 163 – 171. 3. (with N. El Karoui, J. A. Rice, J.W. Richards, and J. Bloom) Optimizing Automated Classification of Periodic Variable Stars in New Synoptic Surveys. Publications of the Astronomical Society of the Pacific (2012) 124. 280 – 295. 4. (with J.W. Richards, D.L. Starr, H. Brink, A.A. Miller, J.S. Bloom, N.R. Butler, J.B. James & J. Rice) Ac- tive learning to overcome sample selection bias: Application to photometric variable star classification. The Astrophysical Journal (2012). 744. 192. 5. (with V. Tilvi, C. Papovich, S.L. Finkelstein, M. Song, M. Dickinson, H.C. Ferguson, A.M. Koekemoer, M. Giavalisco, B. Mobasher.) Rapid Decline of Lyα Emission toward the Reionization Era. The Astrophysical Journal (2014) 794, 5. 6. (with B. Salmon, C. Papovich, et al.) The Relation between Star Formation Rate and Stellar Mass for Galaxies at 3.5 z 6.5 in CANDELS The Astrophysical Journal (2015) 799, 183. Student Committees: Ph.D.

• Shiyuan He (Statistics, Thesis Committee, 2015) • Yi Yang (Physics & Astronomy, Thesis Committee, 2015) M.S.

• Ryan Oelkers (Physics & Astronomy, Thesis Committee, 2014) • Brett Salmon (Physics & Astronomy, Thesis Committee, 2015) • Leo Alcorn (Physics & Astronomy, Thesis Committee, 2015)

254 MICHAEL LONGNECKER

Education:

Michigan Technological University Mechanical Engineering B.S. (1968) Western Michigan University Statistics M.S. (1972) Florida State University Statistics Ph.D. (1976) Appointments:

Interim Department Head Department of Statistics, Texas A&M University 2004-2005 Associate Department Head Department of Statistics, Texas A&M University 2000-Current Director of ConsultingCenter Department of Statistics, Texas A&M University 2000-2012 Professor Department of Statistics, Texas A&M University 1992-Current Visiting Associate Professor Department of Statistics, Univ. of Wisconsin-Madison 1989-90 Associate Professor Department of Statistics, Texas A&M University 1984-1992 Assistant Professor Instituteof Statistics,Texas A&M University-CS 1977-84 Visiting Assistant Professor Department of Statistics, Florida State University 1976-77 Publications: i. Last five years: 1. (with S.B. Sleeba, P. Teel, and O. Strey) Host selection by questing female Amblyomma maculatum Koch, to cattle feeding male ticks in southern Texas, Veterinary Parasitology, 2010, 172, 105-108. 2. (with B.W. Hopkins and P. Pietrantonio) Transcriptional overexpression of CYP6B8/CYP6B28 and CYP6B9 is a mechanism associated with cypermethrin survivorship in field collected Helicoverpazea (Lepidoptera: Noctuidae) moths, Pest Management Science, (2010), 67, 21-25. 3. (with M.T. Nunez De Gonzalez, W.N. Osburn, M.D. Hardin, H.K. Garg, N.S. Bryan, J.T. Keeton) Survey of residual nitrite and nitrate in conventional and organic/natural/uncured/indirectly cured meats available at retail in the United States, Agricultural and Food Chemistry, (2012), 60, 3981-3990. 4. (with Hyeogsun Kwon, Hsiao-Ling Lu, and Patricia Pietrantonio) Role in diuresis of a calcitonin receptor (GPRCAL1) expressed in a distal-proximal gradient in renal organs of the mosquito Aedes aegypti (L.), PLOS ONE, (2013) 7. 5. (with D.R. Tolleson, G. Carstens, T. Welsh, P. Teel, O. Strey, S. Prince, and K. Banik) Plane of Nutrition by Tick Burden Interaction in Cattle: Effect on Growth and Metabolism, Journal of Animal Science, (2013) 90, 3442-3450. 6. (with J.K. Tomberline, T.L. Crippen, A.M. Tarone, B. Singh, K. Adams, Y.H. Rezenom, M.E. Benbow, M. Flores, J.L. Pechal, D.H. Russell, R.C. Beier, T.K. Wood), Interkingdom responses of flies to bacteria mediated by fly physiology and bacterial quorum sensing, Animal Behaviour, (2013) 84(6), 1449-1456. 7. (with D.R. Tolleson, G. Carstens, T. Welsh, P. Teel, O. Strey, S. Prince, and K. Banik) Plane of Nutrition by Tick Burden Interaction in Cattle: Effect on fecal composition , Journal of Animal Science (2013), 91, 3658-3665. 8. (with M. Flores and J.K. Tomberline) Effects of temperature and tissue type on Chrysomay ruifacies (Diptera: Calliphoriadae)(Macquart) development, Forensic Science International, (2014), 245, 24-29. 9. (with J. Thinakaran, E. Peirson, C. Tamborindeguy, D. Henne) Settling and ovipositional behavior of the potato psyllid on solanaceous hosts under field and laboratory conditions, Journal of Economic Entomology, (2015), To appear.

255 10. (with M.T. Nunez De Gonzalez, W.N. Osburn, M.D. Hardin, H.K. Garg, N.S. Bryan, J.T. Keeton) A survey of nitrite and nitrate concentrations in conventional and organic-labeled raw vegetables at retail, Journal of Food Science, (2015), To appear. ii. Textbook: 1. R. L. Ott and M. Longnecker (2015). An Introduction to Statistical Methods and Data Analysis, 7th Ed., Cengage Learning, Belmont, CA.

Grants in last ﬁve years: i. Last ﬁve years: 1. (with P. Teel) National Center for Foreign Animal and Zoonotic Disease, $45,000, An Applicationof Weather Dynamics to Predict Population Changes and Enhanced IPM Stategies for the Gulf Coast Tick, 2013-2014, (Co-P.I.). ii. Other Noteworthy Grants: 1. (with J. Walker, R. Kott, A. Cibilis) USDA, $65,000, Enhancing the Use of Small Ruminants to Control Noxious Weeds, 2004-2007, (Co-P.I.).

Awards and Honors:

1. National Mu Sigma Rho Statistics Education Award, 2011 2. Elected Fellow of American Statistical Association, 2009 3. Western Michigan University Alumni Achievement Award, 2007 4. Finalist for the Texas A&M University Presidential Professor for Teaching Excellence, $10,000 Award, 2004 5. The Association of Former Students of Texas A&M University, Faculty Distinguished Award in Teaching, 1994 6. The Association of Former Students of Texas A&M University, College of Science, Distinguished Teaching Award, 1982 National Service:

1. Associate Editor: Journal of the American Statistical Assoc. (JASA), (1989-92) 2. Associate Editor: The American Statistician, (1987-89) 3. Member of The Committee on Membership Retention and Recruitment, (2010-2014) 4. Co-Chair of The Committee on Membership Retention and Recruitment, (2010-2014)

Students Supervised: (All at Texas A&M University)

Frederic Che-Yuen, Ph.D., (1982) Dissertation: Nonparametric Tests for Homogeneity of the Marginal Distributions of Paired Data

Edgar Wayne Richardson, Ph.D., 1986 Dissetation: Asymptotic Normality of the Parameters of Certain Mixtures of Discrete and Continuous Distributions

Dennis W. King, Ph.D., 1988 Dissertation: Nonparametric Procedures for Process Control

256 Randy Bartlett, Ph.D., 1993 Dissertation: Measures of Capability Under Nonstandard Conditions

Diane Davies, Ph.D., 1994 Dissertation: Statistical Process Control for Correlated Data

Qinli Yue, Ph.D., 1996 Dissertation: Chemometric Calibration and Partial Least Squares

Abeer Al-Khouli, Ph.D., 1999 Dissertation: Robust Estimation and Bootstrap Testing for the Delta Distribution with Applications in the Marine Science

Yibing Zhong, Ph.D., 2000 Dissertation: The Spatial Modeling of a Mixture Distribution

Chair of over 100 Statistics M.S. Committees, 1980-2014

Member of over 80 Statistics Ph.D. Committees, 1980-2014

Member of over 350 non-Statistics M.S. and Ph.D. Committees, 1980-2014

257 BANI K. MALLICK

Education: Presidency College, Calcutta, India Statistics B.S. (1986) Calcutta University, Caluctta,India Statistics M.S. (1988) UniversityofConnecticut Statistics Ph.D.(1994) Appointments: Distinguished University Professor Department of Statistics, Texas A&M University 2011-Present Professor Department of Statistics, Texas A&M University 2003-2011 Director Center for statistical Bioinformatics, Texas A&M University 2010-Present Director, Bayesian Bioinformatics Lab Texas A&M University 2006-Present AdjunctProfessor of Biostatistics MD Anderson Cancer center 2006-Present Adjunct Professor University of Michigan 2008-2010 Associate Professor Department of Statistics, Texas A&M University 2000-2003 Assistant Professor Department of Statistics, Texas A&M University 1998-2000 Permanent Lecturer Department of Mathematics, Imperial College, London 1994-1998 Publications (Last 5 years): 1. Kim, H.-M., Ryu, D., Mallick, B. K., and Genton, M. G. (2014), “Mixtures of skewed Kalman filters”, Journal of Multivariate Analysis, 123, 228-251. 2. Chakraborty, A., De, S., Bowman, K., Sang, H., Genton, M. G., and Mallick, B. (2015), “An adaptive spatial model for precipitation data from multiple satellites over large regions,” Statistics and Computing, 25, 389-405. 3. Baladandydayuthapani, V., Talluri, R., Ji, Y., Coombes, K., Hennessy, B., Davies, M. and Mallick, B. (2014) “Bayesian sparse graphical models for classification with application to protein expression data”, Annals of Applied Statistics, 8, 3, 1443-1468. 4. Mondal, A., Mallick, B., Efendiev, Y. and Datta-Gupta, A. (2014), “Bayesian uncertainty quantification for subsurface inversion using multiscale hierarchical model”, Technometrics, 56:3, 381-392. 5. B. A Konomi, H. Sang, B. K Mallick (2014) “ Adaptive Bayesian nonstationary modeling for large spatial datasets using covariance approximations”, Journal of Computational and Graphical Statistics, 23 (3), 802-829. 6. Sarkar, A., Mallick, B. and carroll, R. (2014), “Bayesian semiparametric regression in the pesence of conditionally heteroscedastic measurement and regression errors”, Biometrics, to appear. 7. Sarkar, A., Mallick, B, Staudenmayer, J., Pati, D. and Carroll, R (2014), “ Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors”, Journal of Computational and Graphical Statistics, to appear. 8. L. Zhang, V. Baladandayuthapani, B.K. Mallick, G.C., Manyam, P.A. Thompson, M.L. Bondy and K. Do (2014) Bayesian hierarchical structured variable selection with application to molecular inversion probe studies in breast cancer. Journal of the Royal Statistical Society: Series C, 63: 595620. 9. Mondal, A., Mallick, B., Efendiev, Y. and Datta-Gupta, A. (2014), “Bayesian uncertainty quantification for subsurface inversion using multiscale hierarchical model”, 56, 3, 381-392, Technometrics. 10. L. Zhang and B.K. Mallick. (2013) “Inferring gene networks from discrete expression data” Biostatistics, 14(4): 708- 722. 11. Chakraborty, A., Mallick, B., McClareren, R., Kuranz, C. and Drake, P. (2013) “Spline based emulators for radiative shock experiments with measurement error”, 108, 411-428 , Journal of the American Statistical Association[Featured Article]. 12. Ryu, D., Liang, F. and Mallick, B. (2013) “A Dynamically particle filter with radial basis function networks for sea surface temperature modeling”, 108, 111-123, Journal of the American Statistical Association. 13. Xun, X., Cao, J., Mallick, B., Carroll, R. and Maity, A. (2013) “Parameter estimation of partial differential equation model”, 108, 1009-1020, Journal of the American Statistical Association. 14. Konomoi, A, Park, C., Huang, J., Huitink, D., Kundu, S., Liang, H. and Ding, Y., Mallick, B. (2013) “Bayesian modeling for analyzing the morphology of gold nanoparticles”, 7, 2, 640-668, Annals of Applied Statistics.

258 15. Bhadra, A. and Mallick, B. (2013) , “Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis”, 69, 2, 447-457, Biometrics [Featured Article]. 16. Zhao, K., Valle, D., Popescu, S., Zhang, X., & Mallick, B. (2013). Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, 102-119. 17. Hartman, B., Talukdar, D. and Mallick, B. (2012) “Investigating cross-country influence dynamics in new product diffusion process”. Annals of Applied Statistics, 6, 625-651. 18. Chakraborty, S., Ghosh, M. and Mallick, B. (2012) “Bayesian Nonlinear Regression for Large p Small n Problems”. Journal of Multivariate Analysis, 108, 28-40. 19. Park, C., Huang, J.Z., Huitink, D., Kundu, S., Mallick, B.K., Liang, J., Ding, Y. (2011), A multi-stage, semi-automated procedure for analyzing the morphology of nanoparticles, IIE Transactions; Special Issue on Nano Manufacturing. 20. Xun, X., Mallick, B., Carroll, R. and Kuchment, P. (2011) “A Bayesian approach to the detection of small low emission sources”. Inverse Problems, 27. 21. Parzen, M., Ghosh, S., Lipsitz, S., Fitzmaurice, Ibrahim, J. and Mallick, B. (2011) “A generalized linear mixed model for longitudinal binary data with a marginal logit link function”. Annals of Applied Statistics, 5, 1,449-467. 22. Ryu, D., Li, E. and Mallick, B. (2011), “Bayesian nonparametric regression analysis when covariates are subject- specific parameters in a random effect model for longitudinal measurement”, Biometrics, 67, 2, 454-466. 23. Lobach, I., Mallick, B., Carroll, R. (2011) “Bayesian analysis of case-control data with gene environment interaction and error in measurement of environmental covariates”,Statistics and its interface, 4, 305-315. 24. Sturino, J., Zorych, I., Mallick, B., Pokusaeva, K., Carroll, R. (2011) “Statistical Methods for Comparative Phenomics using High-throughput Phenotype Microarrays,” The intrenational journal of Biostatistics, 6. 25. McClarren, R., Ryu, D., Drake, P., Bingham, D., Fryxell, B., Mallick, B., Torralva, B. (2011) “A Physical informed emulator for laser-driven radiation shock simulations”, to appear, Reliability engineering and system safety. 26. Holloway, J., Bingham, D., Drake, P., Mallick, B., Nair, V., Ryu, D., Zhang, Z. (2011) “Predictive modeling of a radiative shock system”Reliability engineering and system safety (to appear). 27. Stripling, H., Adams, M., McClarren, R. and Mallick, B. (2011) “The method of manufactured universes for validating quantification methods”, Reliability engineering and system safety (to appear). 28. Dhavala, S., Datta, S., Mallick, B., Carroll, R. and Adams, G. (2010) “Bayesian modeling of MPSS data: Gene expression analysis of Bovine Salmonella infection”,Journal of the American Statistical Association, 105, 956-967. 29. Xia, H., Ding, Y. and Mallick, B. (2010) “Bayesian hierarchical model for combining misaligned two-resolutionmetrol- ogy data” , IIE transactions, 43, 242-258 [Featured Article]. 30. Ghosh, S. and Mallick, B. (2010) “A Hierarchical Bayesian Spatio-temporal Model for Extreme Precipitation Events”. Environmetrics, 22, 2, 192-204. 31. Sinha S, Mallick B.K, Kipnis V, Carroll R.J. (2010) “Semiparametric Bayesian Analysis of Nutritional Epidemiology Data in the Presence of Measurement Error”. Biometrics, 66, 444-454. 32. Huitink, D., Kundu, S., Park, C., Mallick, B., Huang, J. and Liang, H. (2010) “Nanoparticle shape evolution identified through multivariate statistics”, Journal of Physical Chemistry, 114, 5596-5600. 33. Maity, A. and Mallick B. (2010) “Proportional Hazards Regression Using Bayesian Kernel Machines”, In Bayesian Modeling Issues in Bioinformatics and Biostatistics, Wiley (to appear). 34. Efendiev, Y., Datta Gupta, A., Hwang, K., Ma, X. and Mallick, B. (2010) “Bayesian Partition Models for Subsurface Characterization”, In Large-scale inverse problems and quantification of uncertainty, Wiley (to appear). 35. Ray, S. and Mallick, B. (2010), “Model based principal component analysis: Bayesian approaches,” In Frontier of Statistical Decision Making and Bayesian Analysis, Springer. 36. Mondal, A., Efendiev, Y,Mallick, B. and Datta Gupta, A. (2010)“Bayesian Uncertainty Quantification for Flows in Het- erogeneous Porous Media using Reversible Jump Markov Chain Monte Carlo Methods”, Advances in Water resources, 33, 241-256. 37. Efendiev, Y., A. Datta-Gupta, X. Ma, and B. Mallick (2009), Efficient sampling techniques for uncertainty quantification in history matching using nonlinear error models and ensemble level upscaling techniques, Water Resour. Res., 45, W11414, doi:10.1029/2008WR007039.

259 38. Fu, W., Mallick, B. and Carroll, R. (2009) “Why do we observe misclassification errors smaller than the Bayes error”, Journal of statistical computation and simulation,79, 717-722. Books Published in last five years: 1. Mallick, B., Gold, D. and Baladandanayak, V. (2010) Bayesian analysis of gene expression data, Wiley International. 2. Biegler, L., Ghattas, O., Keyes, D., Mallick, B., Tenorio, L., Waanders, V. and Willcox, K. (2011) Large scale inverse problems and quantification of uncertainty, John Wiley and Sons Ltd, U.K. 3. Dey, D., Ghosh, S. and Mallick, B.(2011) Bayesian Modeling Issues in Bioinformatics and Biostatistics, Chapman and Hall/CRC. Grants in last five years: 1. NSF, $690,699 “CMG: Multiscale data integration using facies based hierarchical models”, PI, 2007-2012 2. Norman Hackerman Advanced research program (ARP), ($150,000).“Bayesian Hierarchical Models for Integrating Multi-resolution Information”, PI, 2008-2010 3. NSF, $769,053 “Bayesian Data Mining Approaches for Biological Threat Detection”, PI, 2009-2012 4. NIH, $862,000 “Bayesian models for gene expression with microarray data”, PI, 2005-2010 5. DOE, $347,714 “Bayesian uncertainty quantification in predictions of flows in Highly heterogeneous media and its applications to the CO2 sequestration”, Co-PI 2012-2016 6. Department of Energy (DOE), $3.5 million “Center for Radiative Hydrodynamics (CRASH)”, Co-I, 2008-2013 7. Department of Energy (DOE), $3.4 million,“Center for Predictive computational Sciences (PECOS)”, Co-I, 2008-2013 8. King Abdullah University of Science and Technology (KAUST) Global Research Partnership Center Award, Co-I, 2008-2013 9. National Cancer Institute (NCI), “Measurement error, Nutrition and cancer”, Merit Award, Co-I, 2005-2015 Awards and Honors: Fellow of the American Association for the Advancement of Science (AAAS) Fellow of the Institute of Mathematical Statistics (IMS) Association of Former Students Distinguished Achievement in Research, Texas A&M University, 2006 Fellow of the American Statistical Association (ASA) Elected member of International Statistical Institute (ISI) Fellow of the Royal Statistical Society (RSS) Outstanding Researcher Award, 2007: International Indian Statistical Association Member of Editorial Boards: Journal of Computational and Graphical Statistics (JCGS) (2004-Present) Biostatistics (2009-Present) SIAM/ASA Journal on Uncertainty Quantification (2013-Present) Chemometrics (2013-Present) Journal of Applied Mathematics and Stochastic Analysis (2005-2009) Service: Member of SHRP2: Safety Technical CoordinatingCommittee (TCC), Transportation Research Board, The National Academies Member of Executive Committee of Institute for Applied and Computational Science (IAMCS) Reviewer of Canada Research Chair Program Reviewer of EPSRC Research Proposals, UK Reviewer: Initial Period Review of Professors, Oxford University, UK President (2002-2008), Southeast Texas Chapter Students Supervised: (Total 25 Students, List of a few recent students with current employers) Souparno Ghosh (2009), Assistant Professor, Texas Tech Soma Dhavala (2010), Associate Reserach Scientist, Dow Agroscience Brian Hartman (2010), Assistant Professor, University of Connecticut Bledar Konomoi (2011), Assistant Professor, University of Cincinnati Anirban Mondal (2011), Assistant Professor, Case Western Reserve University Lin Zhang (2012) Assistant Professor, University of Minnesota Abhra Sarkar (2014), Postdoctorate Fellow, Duke University Post-Docs Supervised: (Total 10, List of recent ones with current employer) Anindya Bhadra (2010-2012), Assistant Professor, Purdue University; Avishek Chakraborty (2012-2014), Assistant Profes- sor, University of Arkansas; and Supratik Kundu (2012-2014) Assistant Professor, Emory University.

260 URSULA U. MÜLLER

Education: Freie Universität Berlin, Germany Mathematics Diplom (1993) Universität Bremen, Germany Mathematics Dr. rer. nat. (1997) Universität Bremen, Germany Mathematics Habilitation (2005)

Appointments: Professor Department of Statistics, Texas A&M University 2013-present Assoc. Professor Department of Statistics, Texas A&M University 2009-2013 Assist. Professor Department of Statistics, Texas A&M University 2006-2009 Visiting Assist. Prof. Dept. of Math. & Statistics, Arizona State University 2001-2002 and 2003-2004 Assist. Professor Dept. of Math., Universität Bremen, Germany 1998-2001, 2002-2003, and 2004-2006 Visiting Professor Dept. of Math., Universität Siegen, Germany Oct. 2002-Feb.2003 Post-doc. Researcher Dept. of Math., University of British Columbia Jan.-July 1998

Publications: i. Last five years: 1. (with A. Schick and W. Wefelmeyer) 2015. Estimators in step regression models. To appear in: Statist. Probab. Lett., 10 pp. 2. (with W. Wefelmeyer) 2014. Estimating a density under pointwise constraints on the derivatives. Math. Meth. Statist., 23, 201-209. 3. (with A. Schick and W. Wefelmeyer) 2014. Testing for additivity in partially linear regression with possibly missing responses. J. Multivariate Anal., 128, 51-61. 4. (with I. Van Keilegom) 2014. Efficient quantile regression with auxiliary information. Contemporary Developments in Statistical Theory, Springer Proceedings in Mathematics & Statistics, 68, 365-374. 5. (with A. Schick and W. Wefelmeyer) 2014. Efficient estimators for alternating quasi-likelihood models. J. Indian Statist. Assoc., 52, 1-17. 6. (with J. Chown) 2013. Efficiently estimating the error distribution in nonparametric regression with responses missing at random. J. Nonparametr. Statist., 25, 3, 665-677. 7. (with A. Schick and W. Wefelmeyer) 2013. Non-standard behavior of density estimators for functions of independent observations. In: Stochastic Modeling Techniques and Data Analysis International Conference, Comm. Statist. Theory Methods, 42, 16, 2291-2300. 8. (with A. Schick and W. Wefelmeyer) 2013. Variance bounds for estimators in autoregressive models with constraints. Statistics, 47, 3, 477-493. 9. (with J. Wei, R.J. Carroll, I. Van Keilegom and N. Chatterjee) 2013. Robust Estimation for Homoscedastic Regression in the Secondary Analysis of Case-Control Data. J. R. Stat. Soc. Ser. B Stat. Methodol., 75, 185- 206. 10. (with H.L. Koul and A. Schick) 2012. The transfer principle: A tool for complete case analysis. Ann. Statist., 40, 3031-3049. 11. (with I. Van Keilegom) 2012. Efficient parameter estimation in regression with missing responses. Electron. J. Stat., 6, 1200-1219. 12. 2012. Estimating the density of a possibly missing response variable in nonlinear regression. J. Statist. Plann. Inference, 142, 1198-1214. 13. (with A. Schick and W. Wefelmeyer) 2012. Estimating the error distribution function in semiparametric additive regression models. J. Statist. Plann. Inference, 142, 552-566. 1

261 14. (with A. Schick and W. Wefelmeyer) 2011. Optimal plug-in estimators for multivariate distributions with conditionally independent components. J. Nonparametr. Statist., 23, 1031-1050. ii. Other noteworthy publications: 1. 2009. Estimating linear functionals in nonlinear regression with responses missing at random. Ann. Statist., 37, 2245-2277. 2. 2007. Weighted least squares estimators in possibly misspecified nonlinear regression. Metrika, 66, 39-59. 3. (with A. Schick and W. Wefelmeyer) 2006. Efficient prediction for linear and nonlinear autoregressive models. Ann. Statist., 34, 2496-2533. 4. (with G. Osius) 2003. Asymptotic normality of goodness-of-fit statistics for sparse Poisson data. Statistics, 37, 119-143. 5. 2000. Nonparametric regression for threshold data. Can. J. Stat., 28, 301-310.

Grants in last five years:

1. National Science Foundation, $114,000, “Efficient Estimation in Semiparametric Regression with Possibly Incomplete Data”, 2009-2012, Principal Investigator

Awards and Honors:

1. Member of editorial board: Statistics and Probability Letters (2011-present). 2. Elected member of the International Statistical Institute (ISI),

Service (last five years) Sessions organized and work at national and international meetings:

1. Organized and chaired invited sessions at the 2012 Joint Statistical Meetings (San Diego, CA), and the 2013 IISA conference (Chennai, India). 2. Chaired sessions at Joint Statistical Meetings (Miami Beach, 2011, Montreal, 2013), the 2012 Open Conference on Probability and Statistics (Mainz, Germany), the 2014 ISNPS conference (Cadiz, Spain) and the 2014 IASSL conference (Colombo, Sri Lanka 2014).

Students Supervised:

1. Justin Chown (2014), Ph.D, Texas A&M University Dissertation: New approaches in testing common assumptions for regressions with missing data.

2. Scott D. Crawford (2012), Ph.D, Texas A&M University Dissertation: Efficient estimation in a regression model with missing responses.

3. Member of 10 Ph.D and 24 M.S. advisory committees at Texas A&M University since 2006

262 MOHSEN POURAHMADI

Education: College of Statistics, Tehran, Iran Statistics B.S. (1973) Michigan State University Statistics M.S. (1977) MichiganStateUniversity Statistics Ph.D.(1980) Appointments: Professor (Visiting) Department of Statistics, University of Chicago Fall, 2014 Professor Department of Statistics,Texas A& M University 2008-Pres. Professor Division of Statistics, NIU 1989-2008 Professor (Visiting) Department of Statistics, University of Chicago 2001-2002 Director Division of Statistics, NIU 1994-2001 Associate Professor Division of Statistics, NIU 1985-1989 Associate Professor (Visiting) University of California, Davis 1987-1988 Assistant Professor (Visiting) University of N. Carolina, Chapel Hill 1984-1985 Assistant Professor Northern Illinois University (NIU) 1981-1985 Publications: i. Last ﬁve years: 1. (with M.Daniels) Modeling covariance matrices via partial correlations. Journal MultivariateAnalysis, (2009), 100, 2352-2363. 2. Modeling covariance matrices: The GLM and regularization perspectives, Stat. Sciences, (2011), 26, 369-387. 3. (with M. Maddooliat and J. Z. Huang) Robust estimation of the correlation matrix of longitudinaldata. Statis- tics and Computing,(2011), 23, 1-12. 4. (with P. Dellaportas) The Cholesky-GARCH models with application to ﬁnance. Statistics and Computing, (2012), 22, 849-855. 5. (with P. Kohli and T. Garcia) Regressograms and mean-covariance models for incomplete longitudinal data. The American Statistician, (2012), 66, 85-91. 6. (with J. Huang, M. Chen and M. Maadooliat) A cautionary note on generalized linear models for covariance of unbalanced longitudinal data. Journal of Statistical Planning and Inference, (2012), 142, 743-751. 7. (with F. Ye, T. Garcia and D. Ford) Extension of a Negative Binomial GARCH Model: Analyzing the Effects of Gasoline Price and VMT on DUI Fatal Crashes in Texas. Journal of Transportation Research, (2012), 2279, 31-39. 8. High-Dimensional Covariance Estimation, John-Wiley, 2013. 9. (with L. Chen and M. Madooliat) Regularization of MultivariateRegression Models with Skew Errors, Journal of Statistical Inference and Planning, (2014), 125-139. 10. (with P. Kohli) Some Prediction Problems for Stationary Random Fields with Quarter-Plane Past, Journal of Multivariate Analysis, (2014), 112-125. ii. Other Noteworthy Publications: 1. Journal of Statistical Planning and Inference, Vol. 140, December 2010, Guest Editor (with Richard Davis), Special Issue in honor of Emmanuel Parzen’s 80th Birthday and Retirement from the Department of Statistics, Texas A&M University.

263 2. Pourahmadi, M., Daniels, M.J. and Park, T. (2007). Simultaneous modeling of the Cholesky decompositions of several covariance matrices. J. of MultivariateAnalysis, 98, 568-587. 3. Huang, J., Liu, N., Pourahmadi, M. and Liu, L. (2006). Covariance selection and estimation via penalized normal likelihood. Biometrika, 93, 85-98. 4. Wu, W.B. and Pourahmadi, M. (2003). Nonparametric estimation of large covariance matrices of longitudinal data. Biometrika, 90, 831-844. 5. Pourahmadi, M. (2000). Maximum likelihoodestimation of generalized linear models for multivariate normal covariance matrix. Biometrika, 87, 425-435. 6. Pourahmadi, M. (1999). Joint mean-covariance models with applications to longitudinal data: Unconstrained parameterisation. Biometrika, 86, 677-690. 7. Daniels, M.J. and Pourahmadi, M. (2002). Bayesian analysis of covariance matrices and dynamic models for longitudinal data. Biometrika, 89, 553-566. 8. Pourahmadi, M. (2001). Foundations of Time Series Analysis and Prediction Theory. Wiley, New York. 9. Mohanty, R. and Pourahmadi, M. (1996). Estimation of the generalized prediction error variance of a multiple time series. J. of Amer. Stat. Assoc., 91, 294-299.

Grants in last five years: i. Last five years: 1. National Science Foundation, $120,000, ”Sparse Graphical Models for Multivariate Time Series”, 2013-2015. 2. National Science Foundation, $195,000, ”Generalized Linear Models for Large Correlation Matrices via Par- tial Correlations”, 2009-2012. ii. Other Noteworthy Grants: 1. National Science Foundation, $60,000, ”Model-Based Classification of Longitudinal and Functional Data”, 2005-2007. 2. National Science Foundation, $82,000, “Simultaneous Modelling of Several Large Covariance Matrices”, 2003-2005. 3. NSF-SCREMS (Scientific Computing Research Environments in Mathematical Sciences (1997-98) $75,000. 4. National Security Agency (1996-1998), $42,000, “Topics on Non-Gaussian and Nonlinear Time Series.” 5. Air force Office of Scientific Research (1988-1991), $37,000, “Analysis of NonGaussian, Nonlinear Time Series with Long Memory.” 6. National Science Foundation (1986-1989), $23,967, “Autoregressive Representation of Nonstationary Pro- cesses.” 7. National Science Foundation (1983-1986), $18,000, “Cesaro Summability of the Linear Predictor of a Sta- tionary Time Series.”

Awards and Honors: Please annotate as space allows

1. Elected member of the International Statistical Institute (ISI), 2. Fellow of the American Statistical Association, 3. Member of Editorial Boards: Journal of the American Statistical Assoc. (JASA) (2014-Present). Journal of Business and Economics Statistics (2012-Present). Statistics and Probability Letters (2008-2014). Electronic Journal of Statistics (2010-2012). Journal of Applied Mathematics and Stochastic Analysis (2005-2009).

264 4. VisitingScholar: Department of Mathematics, Hiroshima University, March 2012. Department of Statistics, Pontiﬁcia Universidad Catolica de Chile, May 2011. Melbourne Business School, University of Melbourne, Australia, (May-June, 2009). Australian School of Business, University of New South Wales, Australia, (July, 2009). Department of Mathematics, Hokkaido University, Japan (July-August 2005 and March, 2007) Department of Mathematics and Statistics, Kuwait University, Kuwait (May, 2004). Service: Please annotate as space allows Sessions Organized and Work at National and International Meetings: 1. Chair of the organizing committee for the 2012 NSF-NBER Conference on Time Series Analysis, Texas A&M University (Oct. 26-27). 2. Member of the International Organizing Committee of the Workshop on Correlated Data Modeling, Torino, Italy, 2004. 3. Co-chair (with Ken Berk) of the 31st Symposium on the Interface: Computing Science and Statistics, June, 1999, Schaumburg, IL 4. Organizer of the Longitudinal Data Analysis Workshop, DeKalb, IL, Nov. 6-7, 1997. 5. Chair of the Local Arrangements Committee (LAC) for the joint statistical meetings in Chicago in August 1996.

Students Supervised: Ranye Sun (2014), Ph.D, Texas A&M University Dissertation: Reduced Rank Multivariate Regression and Generalized Matrix Decomposition using Thresholding Meth- ods.

Priya Kohli (2012), Ph.D, Texas A&M University Dissertation: Prediction of Stationary Random Fields. (Co-avdviser, Willa Chen)

Lianfu Chen (2011), Ph.D, Texas A&M University Dissertation: Regularization of Parameters in Multivariate Linear Regression.

M. Al-Rawwash, Ph.D. in Probability and Statistics, Northern Illinois University, 2001.

Tsair-Chuan Lin, Ph.D. in Probability and Statistics, 1996.

Radha Mohanty, Ph.D. in Probability and Statistics, 1992.

Post-Docs Supervised: Dr. Bahram Tarami, Shiraz University, Iran, 2000-2001. Dr. Yukio Kasahara, The University of Tokyo and The Hokkaido University, Japan, Summers 2004 and 2006.

265 HUIYAN SANG

Education: Peking University, Beijing, China Mathematics and Applied Mathematics B.S. (2004) Duke University Statistics Ph.D. (2008) Appointments: Associate Professor Texas A&M University 2014-present Assistant Professor Texas A&M University 2008-2014

Publications: i. Last ﬁve years: 1. (with M. Genton and S. Padoan) Multivariate max-stable spatial processes, Biometrika, (2015), doi: 10.1093/biomet/asu066. 2. Composite likelihoodfor extreme values, Book chapter in Extreme Value Modeling and Risk Analysis: Meth- ods and Applications, (2015), Chapman Hall/CRC. 3. (with W. Han, M. Sheng, J. Li, and S. Cui) Efﬁcient learning of statistical primary patterns via Bayesian network, Proceedings: IEEE International Conference on Communications (ICC), (2015), London, UK. 4. (with B. Zhang and J. Z . Huang) Full-scale approximations of spatio-temporal covariance models for large datasets, Statistica Sinica, (2015), 25, 99-114. 5. (with A. Chakraborty, S. De, K. Bowman, M. Genton and B. K. Mallick) Hierarchical spatial model for precipitation data from multiple satellites, Statistics and Computing, (2015), 25, 389-405. 6. (with B. Konomi and B. K. Mallick) Adaptive Bayesian nonstationarymodeling for large spatial datasets using covariance approximations, Journal of Computational and Graphical Statistics, (2014), 23, 802-829. 7. (with M. Genton) Tapered composite likelihood for spatial extremes, Spatial Statistics, (2014), 8, 86-103. 8. (with J. Z. Huang) A full-scale approximation of covariance functions for large spatial data sets, Journal of the Royal Statistical Society, Series B, (2012), 4, 111-132. 9. (with M. Jun and J. Z. Huang) Covariance approximation for large mutivariate spatial datasets with an application to multiple climate model errors, Annals of Applied Statistics, (2011), 5, 2519-2548. 10. (with M. Genton and Y.Ma) On the likelihoodfunction of Gaussian max-stable processes indexed by Rd, d ≥ 1, Biometrika, (2011), 8, 481-488. 11. (with A. E. Gelfand) Continuous spatial process For extreme values, Journal of Agricultural, Biological and Environmental Statistics, (2010), 15, 49-65. 12. (with A. M. Latimer, S. Banerjee, E. Mosher, and J. A. Silander), Hierarchical models facilitate spatial analysis of large data sets: A case study on invasive plant species in the northeastern United States, Ecological Letters, (2009),12, 144-154. 13. (with A. O. Finley, S. Banerjee, and A. E. Gelfand), Improving the performance of predictiveprocess modeling for large datasets, Computational Statistics and Data Analysis, (2009), I53, 2873-2884. 14. (with A. E. Gelfand) Hierarchical Modeling for Extreme Values Observed over Space and Time. Environmen- tal and Ecological Statistics, (2009), 16, 407-426. ii. Other Noteworthy Publications:

266 1. (with A. E. Gelfand, C. Lennard, G. Hegerl and B. Hewitson) Interpretingself organizingmaps throughspace- time models, Annals of Applied Statistics, (2008), 2,1194-1216. 2. (with S. Banerjee, A. E. Gelfand and A. O. Finley) Gaussian predictive process models for large spatial datasets, Journal of the Royal Statistical Society, Series B, (2008), 70, 825-848.

Grants in last five years: i. Last five years: 1. National Science Foundation, co-PI, $459,200, “Large-Scale Statistical Learning based Spectrum Sensing and Cognitive Networking”, 2014-2017 2. National Science Foundation, PI, $179,660, “A New Approach of Statistical Modeling and Analysis of Mas- sive Spatial Data Sets”, 2010-2014, 3. IAMCS-KAUST Innovative Research Award, PI, $25,000, “Spatio-temporal Models of Extreme Values: An Application to Sea Surface Temperatures in the Red Sea”, 2013-2014 4. IAMCS-KAUST Innovative Research Award, co-PI, $35,000, “ComputationallyTractable Approximate Like- lihood Inference for Irregularly Spaced Massive Spatial Data Sets”, 2010-2011 5. IAMCS-KAUST Innovative Research Award, PI, $20,000, “Arbitrary Feature Identification in Protein Mass Spectrometry Using Prior Knowledge of Feature Interrelationships”, 2008-2009. 6. KAUST GRP award, Investigator, “Institute for Applied Mathematics and Computational Science (IAMCS)”, 2008-2013

Awards and Honors: Please annotate as space allows

1. ISBA Young Researcher Award, Google, 2012 2. NSF INI Travel Award, National Science Foundation, 2008 3. Member of Editorial Boards: STAT (2013-Present).

Teaching: Courses Taught 1. Statistics 211: Principles of Statistics (I). Fall 2008, Spring and Fall 2009, Spring 2010, Spring 2011, Fall 2012, Spring 2013, Fall 2014 2. Statistics 610: DistributionTheory. Fall 2010 3. Statistics 611: Statistical Inference. Spring 2013 4. Statistics 647: Spatial Statistics. Fall 2013, Fall 2014

Service: Please annotate as space allows Sessions Organized and Work at National and International Meetings: 1. Session Organizer for: IMS-China, 2015; SRCOS, 2012; ICSA, 2012; ISBA, 2012. 2. Co-organizer for the IAMCS workshop on Spatial Statistics and Climate Sciences, 2012. 3. Co-organizer of the Spatial Statistics Workshop, TAMU, TX, Jan, 2015.

267 Students Supervised:

Xinxin Zhu (2013), Ph.D, Texas A&M University Dissertation: Wind Forecasting for Power System Operation Blemar Konomi (2011), Ph.D, Texas A&M University Dissertation: Bayesian Modeling of Spatial and Spatial-Temporal Data Bohai Zhang(expected in 2015), Ph.D, Texas A&M University Dissertation: Computational Methods for Large Spatial and Spatial-Temporal Data

Post-Docs Supervised: Dr. Irma Hernandez, UC-Berkeley, CA, 2014-present.

268 HENRIK SCHMIEDICHE

Education: Texas A&M University Computer Science B.S. (1987) Texas A&M University Statistics M.S. (1989) Texas A&M University Statistics Ph.D. (1993)

Appointments: Lecturer Department of Statistics, Texas A&M University 1993-1997 Senior Lecturer Department of Statistics, Texas A&M University 1997-Pres. Director IT College of Science, Texas A&M University 2014-Pres.

Current Job duties:

• Director of information technology for the College of Science. • Supervise, maintain and administer the information technology infrastructure of the Dept. of Statistics at Texas A&M University. • Supervisor of two “Senior Microcomputer/LAN Administrators” in the Dept. of Statistics.

Service:

• Information Technology Advisory Committee (2008-Pres.) University wide committee to advise Texas A&M on IT matters. • Information Policy Committee (2008-Pres.). University wide committee to propose and review Texas A&M IT policy. • Member of the Brazos Architecture and Oversight Committee. Brazos is a 300 node HPC cluster.

Course Taught:

• Engineering Statistics (STAT 2011). 1996-2007. • Advanced Topics in Computational Statistics (STAT 605).

269 SIMON SHEATHER

Education: University of Melbourne Statistics B.S. 1st class honors (1981) La Trobe University Statistics Ph.D. (1986)

Appointments: Professor Department of Statistics, Texas A& M University 2005-Present Professor AGSM, University of NSW 1998-2005 Associate Professor AGSM, University of NSW 1994-1997 Lecturer / Senior Lecturer AGSM, University of NSW 1987-1993 Professor (Visiting) Stern School of Business, NYU 2001 Associate Professor (Visiting) Department of Statistics, Penn State 1987

Publications: i. Last five years (10 selected from a total of 17): 1. Savchuk, O., Hart, J., & Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the American Statistical Association, 489, 415-423. 2. Lindsey, C., & Sheather, S. (2010). Power transformation via multivariate Box–Cox. Stata Journal, 10, 69-81. 3. Phisitkul1, S., Khanna, A., Simoni, J., Broglio, K.R., Sheather, S.J., Rajab, M.H. & Wesson, D.E. (2010). Amelioration of metabolic acidosis in patients with low GFR reduced kidney endothelin production and kidney injury, and better preserved GFR. Kidney International, 77, 617–623. 4. Mahajan, A., Simoni, J., Sheather, S.J., Broglio, K.R., Rajab, M.H. & Wesson, D.E. (2010). Daily oral sodium bicarbonate preserves glomerular filtration rate by slowing its decline in early hypertensive nephropathy. Kidney International, 78, 303-309. 5. Wesson, D.E., Simoni, J., Broglio, K.R. & Sheather, S.J., (2011). Acid retention accompanies reduced GFR in humans and increases plasma levels of endothelin and aldosterone. American Journal of Physiology – Renal Physiology, 300, 830-837. 6. Sheather, S.J. & South, J. (2012). Texas A&M Department of Statistics, Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., Agresti and X.-L. Meng (eds.), Springer, New York, 301-316. 7. Prendergast, L. and Sheather, S.J. (2013). On sensitivity of inverse response plot estimation and the benefits of a robust estimation approach. Scandinavian Journal of Statistics, 40, 219-237. 8. Savchuk, O., Hart, J., & Sheather, S.J. (2013). One-sided cross-validation for non-smooth regression functions. Journal of Nonparametric Statistics, 25, 889-904. 9. Lindsey, C., Sheather, S.J. & McKean, J.W. (2014). Using Sliced Mean Variance-Covariance Inverse Regression for classification and dimension reduction. Computational Statistics, 29, 769-798. 10. Lindsey, C.D. and Sheather, S.J. (2014). Building valid regression models for biological data. Biological Knowledge Discovery Handbook. Wiley, New York, 441-476.

ii. Other Noteworthy Publications: 1. Staudte, R.G. & Sheather, S.J. (1990). Robust Estimation and Testing. Wiley, New York. 2. Sheather, S.J. & Jones, M.C. (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society, Series B, 53, 683–690. 3. Hettmansperger, T.P. & Sheather S.J. (1992). A cautionary note on the method of least median squares. American Statistician, 46, 79-83. 4. Ruppert, D., Sheather, S.J. & Wand, M.P. (1995). An effective bandwidth selector for local least squares regression. Journal of the American Statistical Association, 90, 1257-1270. 5. Barnett, G., Kohn, R. & Sheather, S. (1996). Robust estimation of an autoregressive model using Markov chain Monte Carlo. Journal of Econometrics, 74, 237-254. 6. Hettmansperger, T.P., McKean, J.W., and Sheather, S.J. (2000). Robust nonparametric methods. Journal of the American Statistical Association, 95, 1308-1311. 7. Sheather, S.J. (2004). Density estimation, Statistical Science, 19, 588-597.

270 8. *Spiegelman, C., Tobin, W. A., James, Sheather, S.J., Wexler, S.& Roundhill, D. M. (2007). Chemical and forensic analysis of JFK assassination bullet lots: Is a second shooter possible? Annals of Applied Statistics, 1, 287–301. 9. Lauziere, I., Sheather, S. and Mitchell, F. (2008). Seasonal abundance and spatio-temporal distribution of dominant xylem fluid-feeding Hemiptera in vineyards of Central Texas and surrounding habitats. Environmental Entomology, 37, 925-937. 10. Sheather, S. J. (2009). A Modern Approach to Regression with R. Springer, New York.

Grants in last five years: 1. NIH, $100,000, “Lipoprotein Density Profiling for Clinical Studies”, 2008-2011. 2. NSF, $300,000, “Texas Census Data Research Center”, 2011-2014. 3. SAS, $1,000,000, “Development of a new MS (Analytics) degree program”, 2013-2014.

Awards and Honors: 1. Australian Graduate School of Management (AGSM) Alumni Association Award for Excellence in Teaching (1991, 1997, 2000) 2. University of New South Wales Vice Chancellor’s Award for Teaching Excellence (1994) 3. Fellow of the American Statistical Association (2001) 4. Listed on ISIHighlyCited.com among the top one-half of one percent of all mathematical scientists, in terms of citations (2001-2013). According to Google scholar, 7827 citations as of 3/8/15 (including 697 in 2014). 5. Inaugural AGSM Award for Excellence in Research (2002) 6. American Statistical Association, Statistics in Chemistry Award (2008) (based on publication * above) 7. Fish Camp Namesake, Texas A&M University (2012) 8. Mentor of the winning student teams in the 2012 & 2014 Capital One National Statistical Modeling Competitions 9. Texas A&M University Association of Former Students Distinguished Achievement College-Level Teaching Award (2013)

Service: (last 5 years) Major Administrative Roles: 1. Head of the Department of Statistics (2005-2014) 2. Director of Online Programs, Department of Statistics (2011 – present) 3. Academic Director of MS Analytics Program, Department of Statistics (2013- present) 4. President, Texas A&M Statistical Services, LP (2012 – present)

Selected National/International Service: 1. Chair of the External Review Committee for the Department of Statistics at the University of Kentucky (2012) 2. External Review Committee for the Department of Mathematics and Statistics at the University of Cyprus (2012) 3. External Review Committee for the Department of Statistics at the University of British Columbia (2013)

University committees: 1. Chair, Faculty Evaluation Task Force on Teaching, President’s Task Force on Faculty Evaluations (2009-2010) 2. Massive Open Online Course (MOOC) Exploration Committee (2012-2013) 3. Core Curriculum Technology Enhanced Grant Committee (2012-2015 4. Activity leader for the ADVANCE leadership development program for Department Heads (2012-2014) 5. Member (2011-2013) and Chair of the Department Head Council (2013-2014) 6. Member of the President’s Council on Climate and Diversity (2013-2014) 7. Email Selection Advisory Committee (2013-2014) 8. Massive Open Online Course (MOOC) Advisory Committee (2013-2014 9. Strategic Re-allocation Sub-Council (2013-2014) 10. Price Waterhouse Coopers Advisory Committee (2013-2014) 2

271 11. College of Science Selection Committee for The Association of Former Students' College-Level Teaching Awards (2014) 12. Search Advisory Committee for the Dean of Science (2014-2015)

Community Service: 1. Member of the Board of the Boys and Girls Club of the Brazos Valley (2011 - present)

Students Supervised (last 5 years): Ph D – 4 students 1. Olga Savchuk (2009), Choosing a Good Kernel for Cross-Validation (co-chair with J. Hart) 2. Charles Lindsey (2010), SMVCIR Dimensionality Test (chair) 3. Bradley Barney (2011), Bayesian Joint Modelling of Binomial and Rank Response Data (co-chair with V. Johnson) 4. Dominic Jann (2012), Bayesian Methods for Record Matching (co-chair with M. Speed)

MS (Statistics) – 50 students 1. Clarissa La (2010), Retaining Loyal, High-Value Hilton Honors Members (co-chair with M. Speed) 2. Shira Hetz (2011), Comparison of Bandwidth Selectors for Kernel Density Estimates (chair) 3. Jack Bennett (2012), Play Testing Games using Statistical Methods (chair) 4. Stephanie Platt (2013), Red, red wine: Model selection using Portuguese wine (chair) 5. Kathleen Hosek (2014), Modeling residence hall utilities consumption (chair) 6. Lisa Szydziak (2014), Data.Medicare.gov – Statistical modeling of Hospital Compare data (chair) 7. Taylor Davis (2014), Predicting changes in customer satisfaction (chair) 8. Alex Bessinger, Joel Galang, Joseph Magagnoli, Jennifer Morse and Hung Tran (2014), A model for opening weekend box office revenue based on Wikipedia activity (co-chair with A. Dabney) 9. Daniel Evert, Michael Knous, Christopher Rodriguez and Samuel Temple (2014), Logistic regression models for predicting the probability of a birdie or better on the PGA tour (co-chair with A. Dabney) 10. Daniel Byler, Jonathan Goodhue, Warren Roane and Kelvin Li (2014), A model for predicting price of Toyota certified preowned Camry vehicles (co-chair with M. Katzfuss) 11. Dan Liu, Alex Pestrikov, Richard Chapman, Lance Costello and Uday Hejmadi (2014), Predicting daily usage in the Capital Bikeshare system (chair) 12. Sydney Anuskiewicz, Patrick Clark, Thomas Duffy, Andrea Ferris, Raymond Kui, Alana Moczydlowski, Wenxin Pang, Johannes Roijen, Eric Talarico and Sui Zhang (2015), Predicting credit events in 30 year mortgages using the Freddie Mac loan performance data (chair) 13. Teresa Barnett, Nicholas Darschewski, Jin Do, Jeremy Fergason, Jonathan Presto and Daniela Sakamoto (2015), Predicting US gross movie box office receipts along with days in release (chair) 14. Lynetta Campbell, Felipe Chacon, John Czarnek, Jeffrey Kirk and Susan Uland (2015), Predicting sound pressure levels using a data set from NASA (chair) 15. Garrett Anderson, Wenhoung Fan, Paul Garrett and Shuhua Xia (2015), Predicting daily utility consumption in residence halls at TAMU (chair)

MS (Analytics) – 8 students 1. Steve Bowden (2015), Predicting churn (chair) 2. Aaron Agnew (2015), Modeling credit events (chair) 3. Lauren Engle (2015), Modeling loyalty program usage (chair) 4. Danny Leonard (2015), Modeling the effect of price on demand (chair) 5. Erin Parrott (2015), Predicting future demand (chair) 6. Mike Bergeron (2015), A pricing model (co-chair with E. Jones) 7. Bora Tarhan (2015), Modeling gasoline prices across the US (co-chair with M. Speed) 8. Salsawit Shifarraw (2015), Modeling in-patient ratings of hospital care (co-chair with E, Jones)

272 MICHAEL SHERMAN

Education: Department of Mathematics, University of Massachusetts, Amherst Mathematics B.A. (1987) Department of Statistics, Universityof NorthCarolinaat Chapel Hill Statistics M.S. (1990) Department of Statistics, University of North Carolinaat Chapel Hill Statistics Ph.D. (1992) Appointments: Professor Department of Statistics, Texas A&M University 2008–present Associate Professor Department of Statistics, Texas A&M University 1999–2008 Assistant Professor Department of Statistics, Texas A&M University 1994–1999 Postdoctoral Fellow Department of Biostatistics, University of Rochester 1992–1994

Publications: i. Last five years: 1. (with K. Lennox) Efficient experimental design for binary matched pairs data, Statistics in Medicine, (2009), 28, 2952–2966. 2. (with Y. Parmet and E. Schechtman) Factor analysis revisited: how many factors are there?, Communications in Statistics, (2010), 39, 1893–1908. 3. (with K. Baum et al.) Spatial distributionof Africanized honey bees in an urban landscape, Urban Landscape and Planning, (2011), 100, 153-162. 4. Spatial Statistics and Spatio-Temporal Data: Covariance Functions and Directional Properties, (2011), John Wiley & Sons, Ltd., Chichester, UK. 5. (with A. Maity and S. Wang) Inferences for the ratio: Fiellers interval, log ratio, and large sample based confidence intervals, Advances in Statistical Analysis, (2011). 6. (with A. Maity) Testing for spatial isotropy under general designs, Journal of Statistical Planning and Infer- ences, (2012), 42, 1081–1091. 7. (with J. Lim et al.) Parameter estimation in the spatial auto-logisticmodel with varying independent subblocks, Computational Statistics and Data Analysis, (2012) 56, 4421–4432. 8. (with J. Lim et al.) A 2-dimensional fused lasso, Journal of Multivariate Analysis, (2015) under review. ii. Other Noteworthy Publications: 1. Sherman, M., and Carlstein, E. (1996). Replicate histograms. Journal of the American Statistical Association, 91, 566–576. 2. Sun, Y., and Sherman, M. (1996). Some permutation tests for survival data, Biometrics, 52, 87–97. 3. Sherman, M. (1996). Variance estimation for statistics computed from spatial lattice data, Journal of the Royal Statistical Society, Series B, 58, 509–523. 4. Sherman, M. (1997). Subseries methods in regression, Journal of the American Statistical Association, 92, 1041–1048. 5. Politis, D., and Sherman, M. (2001). Moment estimation for statistics from marked point processes, Journal of the Royal Statistical Society, Series B, 63, 261–275. 6. Guan, Y., Sherman, M., and J.A. Calvin(2004). A Nonparametric test for isotropyusing subsampling, Journal of the American Statistical Association, 99, 810–821.

273 7. Guan, Y., Sherman, M. (2007). On least squares ﬁtting for stationary spatial point processes, Journal of the Royal Statistical Society, Series B, 69, 31–49. 8. Li, B., Genton, M., and Sherman, M. (2007). A Nonparametric assessment of properties of space-time covariance functions, Journal of the American Statistical Association, 102, 736–744. 9. Li, B., Genton, M., and Sherman, M. (2008). Testing the covariance structure of multivariate random ﬁelds Biometrika, 95, 813–829.

Grants in last ﬁve years: i. Last ﬁve years:

1. National Institute of Health R01 Award, “Fetal Alcohol Exposure and Neurodevelopment”, AA-13440-04, Collaborator, Rajesh Miranda P.I., 2002–2012. ii. Other Noteworthy Grants: 1. National Institute of Health R01 Award, “Risk of ChildhoodCancers Associated with Agricultural Use”, CA- 92670, Co-PI, 2001-2008. 2. 1996–2002 National Institute of Health FIRST Award, “Subsampling Methods for Spatial and Longitudinal Data”, CA-72015. P.I. 1996-2002.

Awards and Honors:

1. Elected member of the International Statistical Institute (ISI), 2. College of Science Distinguished Achievement Award from the Association of Former Students at Texas A&M University, 2002 3. Member of Editorial Boards: Journal of the American Statistical Assoc. (JASA) (2005-2014). Biometrics (1998-2000).

Service: Member of Site Visit Team for the Carolina Population Center, March 2000.

Refereed Papers (Proposals) for: Annals of the Institute of Statistical Mathematics, Annals of Statistics, Biometrics, Biometrical Journal, Communications in Statistics, Environmental and Ecological Statistics, Journal of the American Statistical Association, Journal of Compu- tational Statistics and Data Analysis, Journal of Pediatric Oncology, Journal of the Royal Statistical Society, Journal of Statistical Planning and Inference, Mathematical Methods of Statistics, National Science Foundation, National Security Agency, Simulation, South African Research Foundation, State of Louisiana, Statistica Neerlandica, Statistics and Proba- bility Letters.

Students Supervised: Ph.D. Students mentored at Texas A&M: Yongtao Guan (advised jointly with J.A. Calvin) Eric Hintze Bo Li (advising jointly with R.J. Carroll) Elizabeth Young Master’s Students mentored at Texas A&M: Susan Gao Xiaoqi Li

274 Min Chen Justin Chown Lei Wang Todd Napier Celeste Wilson Stephanie Berland Served on Master’s or Ph.D. Students mentored at Texas A&M 2006-present: Shuo Feng Negin Alemazkoor Nishal Kaﬂe Zachary Scott Melissa Lee Jincheol Park Jason Poole Hisham Almohammadi Angela Brown Soutir Bandyopadhyay Eric Talbot Dlonglin Han Xiaso Zeng Ying Sun Roma Garg Yanru Zhang Siqi Li

275 SAMIRAN SINHA

Education: Kalyani University, West-Bengal, India Statistics B.Sc. (1997) Calcutta University, West-Bengal, India Statistics M.Sc. (1999) UniversityofFlorida,Florida,USA Statistics Ph.D. (2004) Appointments: Visiting Associate Professor Michigan State University 2011 Associate Professor Texas A&M University 2010–present VisitingAssistant Professor Michigan State University 2009-2010 Assistant Professor Texas A&M University 2004-2010 Publications: i. Last five years (max 10): 1. Sinha, S. and Ma, Y. (2014). Semiparametric analysis of linear transformation models with covariate measurement errors. Biometrics, 70, 21–32. 2. Sinha, S., Saha, K. K., and Wang, S. (2014). Semiparametric approach for non-monotone missing covariates in a parametric regression model. Biometrics, 70, 299–311. 3. Maiti, T., Ren, H. and Sinha, S. (2014). Prediction error of small area predictors with shrinking both mean and variances. Scandinavian Journal of Statistics, 41, 775–790. 4. Sinha, S. and Yoo, S. (2013). Score tests in the presence of errors in covariate in matched case-control studies. Journal of Multivariate Analysis, 115, 157–171. 5. Sinha, S. (2012). A functional method for conditional logistic regression with errors-in-covariates. Journal of Nonparametric Statistics, 24, 577–595. 6. Sinha, S., Mallick, B. K., Kipnis,V., and Carroll,R. J. (2010). Semiparametric Bayesian analysis of nutritional epidemiology data in the presence of measurement error, Biometrics, 66, 444–454. 7. Chatterjee, N., Sinha, S., Diver, W. R., and Feigelson, H. S. (2010). Analysis of cohort studies with multivariate, partially observed, disease classification data, Biometrika, 97, 683–698. 8. Sun, J. X., Sinha, S., Wang, S., and Maiti, T. (2010). Bias reduction in conditional logistic regression. Statistics in Medicine, 30, 348–355. 9. Sinha, S. (2010). An estimated-score approach for dealing with missing covariate data in matched case-control studies, The Canadian Journal of Statistics, 38, 680–697. 10. Ahn, J., Mukherjee, B., Gruber, S. B., and Sinha, S. (2010). Missing exposure data in stereotype regression model: application to matched case-control study with disease subclassification, Biometrics, 67, 546–558. ii. Other Noteworthy Publications: 1. Dass, S. C., Maiti, T., Ren, H. and Sinha, S. (2012). Confidence interval estimation of small area parameters shrinking both mean and variances. Survey Methodology, 38, 173–187. 2. Sinha, S. and Wang, S. (2009). A new semiparametric procedure for matched case-control studies with missing covariates, Journal of Nonparametric Statistics, 21, 889–905 . 3. Sinha, S. and Maiti, T. (2008), Analysis of matched case-control data in presence of nonignorable missing data, Biometrics, 64, 106–114.

276 4. Sinha, S., Gruber, S. B., Mukherjee, B., and Rennert, G. (2008), Inference of haplotype effect in matched case-control study using unphased genotype data, International Journal of Biostatistics, 4, Issue 1, Article 6. 5. Sinha, S., Mukherjee, B., and Ghosh, M. (2007), Modelling association among multivariate exposures in case-control studies, Sankhya, 69, 379–404. 6. Mukherjee, B., Zhang, L., Ghosh, M., and Sinha, S. (2007), Semiparameteric Bayesian analysis of case- control data under gene-environment independence and population stratiﬁcation, Biometrics, 63, 834–844. 7. Mukherjee, B., Liu, I., and Sinha, S. (2007), Analyzing matched case-control data with multiple ordered disease states, possible choices, and comparisons, Statistics in Medicine, 26, 3240–3257. 8. Sinha, S., and Mukherjee, B. (2006), A score test for determining sample size in matched case-control studies with categorical exposure, Biometrical Journal, 48, 35–53. 9. Sinha, S., Mukherjee, B., Ghosh, M., Mallick, B. K., Carroll, R. J. (2005), Semiparametric Bayesian Analysis of Matched case-control studies with missing exposure, Journal of the American Statistical Association, 100, 591–601. 10. Sinha, S., Mukherjee, B., and Ghosh, M. (2004), Bayesian semiparametric modeling for matched case-control studies with multiple disease states, Biometrics, 60, 41–49.

Grants in last ﬁve years: i. Last ﬁve years: 1. National Institute of Health, $150,000, “Innovative approaches for analyzing SEER breast cancer data”, 2013- 2015. 2. National Science Foundation, $44,500, “Statistical Methods based on parametric and semiparametric hierarchical models to solve problems related to socio-economic-demographic deprivation measure”, 2010-2013. 3. National Science Foundation, $26,858, “The 13th New Researcher Conference in Statistics and Probability”, 2010.

4. National Institute of Health, $20,000, “The 13th New Researcher Conference in Statistics and Probability”, 2010.

5. National Security Agency, $12,700, “The 13th New Researcher Conference in Statistics and Probability”, 2010. Service: Sessions organized in conferences in the last 5 years: 1. Organizer of one invited session in the IISA 2014. Title of the session: “Inverse problems with application in statistics”. Speakers: Xiaofeng Wang, Jean-Pierre Florens, and Samiran Sinha. 2. Chaired the session “Bayes estimation in Modern Cancer Epidemiological Studies” in the IISA 2014, Riverside, CA. 3. Organized one invited session in the ENAR meeting 2011. Title of the session: ”Disease mapping and spatial regression as emerging tools for surveillance epidemiology”. Speakers: Peter Congdon, Lance Waller, Tapabrata Maiti, and Andrew Lawson. 4. Chaired the session ”Disease mapping and spatial regression as emerging tools for surveillance epidemiology” in the ENAR 2011 meeting. 5. Chair of the IMS new researchers conference organizing committee for the year of 2010 which was held in Vancou- ver, Canada. The details of the conference can be found at http://www.stat.tamu.edu/˜sinha/nrc2010-ims.html.

277 6. Organizer of one invited session in the ENAR meeting 2010. Title of the session: “Shrinkage estimation in Mi- croarray data analysis”. Speakers: James Booth, Marina Vannucci, Dan Nettleton, and Tapabrata Maiti. 7. Organizer of one invited session in the Biometrics Section for the 2009 Joint Statistical Meeting (JSM). Title of the session: The issue of high dimensionality and missing data in complex epidemiological studies. Speakers: Rebecca Betensky, Nicholas P. Jewell, Bin Nan, and John Neuhaus. Discussant: Samiran Sinha.

Students Supervised: Ph.D students: Jiangang Miao (2014); Dissertation was on missing data and measurement errors in epidemiological studies.

Jenny X. Sun (2010); Dissertation was on small sample bias corrections in the conditional logistic regression.

Master’s students: Seungyoon Yoo (2010) Minkyung Oh (2011) Charles Gordon (2012) Jenn Hanley-Burkhart (2012) Stacie Blaskowski (2012) Abigail Green (2013) Craig Kreisler (2013)

278 CLIFFORD H. SPIEGELMAN

Education: SUNY at Buffalo Statistics/Mathematics/Economics B.S (1970) Northwestern University Managerial Economics M.S. (1973) Northwestern University Applied Math/Statistics Ph.D. (1976)

Appointments: Distinguished Professor Department of Statistics, Texas A& M University 2009-Pres. Professor Department of Statistics, Texas A& M University 1990-2008 Senior Research Scientist Texas A&M Transportation Institute (TTI) 2004-Pres.

Selected Publications out of 13: i. Last five years: 1. Nagyvary, Joseph, Guillemette, Ray, and Spiegelman, Clifford (2009). “Mineral Preservatives in the Wood of Stradivari and Guarneri”, PLoS ONE, http://dx.plos.org/10.1371/journal.pone.0004245 (see awards and honors section for coverage of this paper) 2. Paulovich, … Spiegelman, C., Stein, S., Tempst, P., Liebler, D. (2009). “A CPTAC Inter-laboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance”, http://www.mcponline.org/cgi/reprint/M900222-MCP200v1 3. Rudnick, … Spiegelman, C., Tempst, P., Liebler, D., and Stein, S. (2009). “Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomic Analyses and Evaluation by the CPTAC Network”, MCP Papers in Press, http://www.mcponline.org/cgi/reprint/M900223-MCP200v2 4. Addona, T., … Spiegelman, … Carr, S. (2009). “Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma”, Nature Biotechnology, 27, 633 – 641. 5. Tabb, D., … Spiegelman, C.H. (Communicating Author) “Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography- Tandem Mass Spectrometry”. Journal of Proteome Research,9, 761- 776 6. Nell Sedransk, … Cliff Spiegelman “Make Research Data Public?-Not Always so Simple”: A Dialogue for Statisticians and Science Editors; Statist. Volume 25, Number 1 (2010), 41-50. 7. Rudnick, P.A., …Spiegelman, C., Tempst, P., Liebler, D.C., Stein, S.E., Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses, Mol. Cell Proteomics, 2010 Feb., 9(2), pp. 225-241. 8. Tarone, A. M.; Picard, C. J.; Spiegelman, C.; et al. (2011). Population and Temperature Effects on Lucilia sericata (Diptera: Calliphoridae) Body Size and Minimum Development Time. Journal Of Medical Entomology (48) 5,1062-1068, DOI: 10.1603/ME11004 9. A Nonparametric Approach Based on a Markov like Property for Classification- Review Article Chemometrics and Intelligent Laboratory Systems, Volume 108, Issue 2, 15 October 2011, Pages 87-92 Eun Sug Park, Clifford Spiegelman, Jeongyuon Ahn 10. Lahiri, S. N., Spiegelman, C., Appiah, J., and Rilett. L. Gap Bootstrap Methods for Massive Data Sets With An Application To Transportation Engineering. The Annals of Applied Statistics Vol. 6, No. 4, 1552–1587. 11. Spiegelman C, and Tobin W A. Analysis of experiments in forensic firearms/toolmarks practice offered as support for low rates of practice error and claims of inferential certainty. Law, Probability and Risk; 12:115-133. 12. Park E.S., Hopke P. K., Oh M. S., Symanski E., Han D., Spiegelman C. H. Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach., Biostatistics 15, 3, 484 -497. 13. Owings Charity G., Spiegelman Cliff, Tarone Aaron M. and Tomberlin Jeffery K., Developmental variation among Cochliomyia macellaria Fabricius (Diptera: Calliphoridae) populations from three ecoregions of Texas, USA, Int J Legal Med, DOI 10.1007/s00414-014-1014-0. ii. Other selected Noteworthy Publications: 1. Spiegelman, C., Tobin, W.A., James, W.D., Sheather, S., Wexler, S., & Roundhill, D.M. (2007). Chemical and Forensic Analysis of JFK Assassination Bullet Lots: Is a Second Shooter Possible, Annals of Applied Statistics. (1)2, 287-301. Feature on national and international television, and print media on all continents, see the honors and awards section.

279 Grants/Cooperative Agreements in last five years. Spiegelman as PI: i. Last five years: 1. (NASS/USDA), $ 419,306, Census Calibration Weighting, 2014-2017 2. TAMU/Weizmann, $88,000 A non-parametric Markov approach to classification and regression, 2012-2015 3. Southwestern University Transportation Research Center (SWUTC/USDOT), $135,253, “Write a transportation textbook and associated course creation, 2008-2014 ii. Southwestern University Transportation Research Center (SWUTC/USDOT), How do Travelers Perceive the Value of Travel Time Reliability? $45,000. (Joint PIs Burris from TAMU Civil Engineering and Spiegelman) 2013-2014. iii. Grants where Spiegelman was Co-PI, Heath Effects Institute, $251,814 (through TTI) Development of enhanced statistical methods for assessing health effects associated with an unknown number of major sources of multiple air pollutants 2009-2014. iv. Other Noteworthy Grants/Cooperative Agreements: 1. NCI 2006-2009, SAIC-Frederick-NCI-Proteomic Technology”, $2,170,547 for helping run the NCI proteomics program, particularly the statistical aspects.

Awards and Honors: i. NRC noteworthy awards: 1. 2002 and 2008- Statistics in Chemistry Awards for Best Paper by the ASA 2. 1991- W. J. Youden Award given by the American Statistical Association for the best paper on Interlaboratory Comparisons 3. 2015-2016 Co-chair SAMSI program on forensic science. 4. 2012-Present. Member of 9 person Technical Advisory Board for the Houston Forensic Science LGC (The city of Houston crime lab.) 5. 2014-Fellow of the American Association for the Advancement of Science (AAAS), 6. 2013-Honor University wide lecture on the forensic aspects of the JFK assassination 50-year anniversary lecture. All of the networks ABC, NBC, and CBS covered the talk. The work was also cited extensively in 7. 2012-2013 Invited to write a series of editorials for the Austin American Statesman on the state of forensic science in this country. Three were written and featured on the first page of the editorial section and 2 were above the fold. 8. 2009- Paper with Nagyvary covered by international print media including Time Magazine and the Christian Science Monitor 9. 2008-2014-National Institute of Statistical Sciences (NISS) Board of Directors (term limited off), and Department representative 2004-present. 10. 2007- Jerome Sacks Award for Cross-Disciplinary Research. This award is given to an individual whose work is cross-disciplinary and encompasses innovation in the statistical sciences. Preference will be given to work that creates new research relationships or substantially buttresses extant relationships. 11. 2007- Honor- Interviewed by NBC Nightly News, CNN Situation Room, Geraldo at Large, The Washington Post, and may other national radio and newspapers about the JFK paper. It was a worldwide story and the lead story on Fox News for 2 days. 12. 1994-Distinguished Achievement Award, ASA Section on the Environment 13. 1993-Elected member of the International Statistical Institute (ISI) 14. 1992-Fellow of the American Statistical Association (ASA), 15. 1990-Fellow of the Institute of Mathematical Statistics (IMS) 16. 1985-Presant. 30 year long coeditor (founding) Chemometrics and Intelligent Laboratory Systems 17. Various editorial boards including JASA (one moth as acting T&M editor), Environmetrics, J. Chemometrics, J. of Proteomics (an ACS journal), Journal of Transportation Statistics and its successor The Journal of Transportation and Statistics. Service: ii. Sessions Organized and Work at National and International Meetings: 1. Co-organizer of 3 International Chemometrics Meetings (1985 in Gaithersburg NBS (now called NIST) 1991 at TAMU, 1995 and 2000 in Las Vegas)

280 2. 1987 - 1991 Head ASA Committee on Statistics in Chemistry. 3. 2002-2003 Head and Co-organizer of Transportation Interest Group with the ASA Editorial. 4. 2003-2004 NRC committee for the FBI Bullet Lead Analysis. 5. 2002-2012 Member, Committee on Statistical Methodology and Statistical Computer Software in Transportation Research, Transportation Research Board, Division of NRC. I was term limited off. 6. Numerous JSM-ASA sessions on Forensic Science, Transportation, Environmetrics, and Chemometrics. I did not keep records, but they should be available from JSM programs. Also, I organized at least 2 Transportation Research Board (TRB) sessions and in 2012 with Larry Rilett gave a full day short course on micro simulation at the Transportation Research Board. (It should be apparent that I organize meetings and sessions for effect and not vita entries.) 7. AAAS Annual meeting 2013 session on Forensics Science 8. AAAS Annual meeting 2014 session on Data Availability (a featured session selected for web broadcasting around the world.)

Students Supervised: Ph.D. Students Chaired: 1991 Chyon-Hwa Yeh 1997 Eun Sug Park 2000 Byron Gajewski 2001 Jacqueline Kiffe (Co-Chair) 2002 Naijun Sha (Co-Chair) 2012- Mary Frances Dorn

MS Students (During the last 4 years): Lacy Brown - PhD in CVEN Zehra Yalcin - MS in BAEN Xiduo Wang - MS in CVEN Robert E. Saw (current) - MS in STAT Raymond Kui - MS in STAT Chong Chin Heo - PhD in ENTO Melissa Lee (Chair) - MS in STAT Santosh Rao R. Danda (Did extensive work with him and on the supporting grant)- MS in CVEN Liteng, Zha - MS in CVEN Ryan Brady (Chair) - MS in STAT Nicholas Nimchuk (Chair) - MS in STAT Ernesto Ramos (Doing extensive work with him and expect a joint paper) - MS in ENTO Zhi Chen - MS in CVEN Tao Zhang - MS in CVEN Nathan Shetty (joint chair) - MS in STAT Bo Wang - MS in CVEN Yiyi Wang (worked a lot with him) - PhD in STAT Siamak Saliminejad - PhD in CVEN Shuo Feng - PhD in STAT Brian Shollar - MS in CVEN Gregory Joseph Cepluch- MS in STAT Benjamin Robert Sperry (Worked extensively with him) - PhD in CVEN Nathaniel Allen Joy – (worked extensively with him) MS in AGEC Jinpeng Lv - PhD in CVEN Mehdi Azimi - PhD in CVEN

281 SUHASINI SUBBA RAO

Education: Universityof Bristol Mathematics Ph.D. (2001)

Appointments: Associate Professor Texas A&M, USA 2010-present Assistant Professor Texas A&M, USA 2006-2010 Lecturer UniversityofBristol,UK 2005-2006 Postdoctoral Fellow, Universität Heidelberg, Germany 2001-2005 Publications: i. Last five years: 1. A test for stationarity of a Multivariate time series (Carsten Jentsch and Suhasini Subba Rao) (2015) Journal of Econometrics, 185, pages 124–161. 2. BaSTA: consistent multiscale multiple change-point detection for piecewise-stationary. (Piotr Fryzlewicz and Suhasini Subba Rao) (2014) JRSS(B), 76, pages 903–924. 3. The Handbook of Statistics, vol 30 (Time Series Analysis: Methods and Applications) (co-Editor) (2012). 4. Statistical inference for Stochastic Coefficient Regression models (2012). Handbook of Statistics, vol 30. 5. A test for second order stationarity of a time series based on the Discrete Fourier Transform (Yogesh Dwivedi and Suhasini Subba Rao) (2011) Journal of Time Series Analysis, 32, pages 68–91. 6. On mixing properties of ARCH and time-varying ARCH processes, (Piotr Fryzlewicz and Suhasini Subba Rao) (2011) Bernoulli. 7. Nonparametric estimation for dependent data (Jan Johannes and Suhasini Subba Rao), (2010), Journal of Nonparametric Statistics, 23, pages 661–681. ii. Before 2010: 1. Statistical analysis of a spatio-temporal model with location dependent parameters and a test for spatial stationarity. (Suhasini Subba Rao) (2008), Journal of Time Series Analysis (29) pages 673–694. 2. Normalised least squares estimation for time-varying ARCH processes. (Piotr Fryzlewicz, Theofanis Sapati- nas and Suhasini Subba Rao), (2008), Annals of Statistics, 36, pages 742–786. 3. Statistical analysis of time series models for minimum/maximum temperatures in the Antarctic Peninsula (Gillian Hughes, Suhasini Subba Rao and Tata Subba Rao), (2007) Proceedings of the Royal Society (A), 463, pages 241–259 4. A recursive online algorithm for the estimation of time-varying ARCH parameters. (Rainer Dahlhaus and Suhasini Subba Rao), (2007), Bernoulli, 13, pages 389–422. 5. On some nonstationary, nonlinear random processes and their stationary approximations. (Suhasini Subba Rao) (2007), Advances in Applied Probability 38, pages 1155-1172. 6. A Haar-Fisz technique for locally stationary volatility estimation. (Piotr Fryzlewicz, Theofanis Sapatinas and Suhasini Subba Rao), (2006), Biometrika 93, pages 687-704. 7. A note on uniform convergence of an ARCH(∞) estimator. (Suhasini Subba Rao) (2006) Sankhya, 68, pages 600–620.

282 8. Statistical inference of time-varying ARCH processes (Rainer Dahlhaus and Suhasini Subba Rao), (2006), Annals of Statistics 34, pages 1074-1114. 9. On multiple regression models with nonstationary correlated errors. (Suhasini Subba Rao) (2004) Biometrika 91, pages 645-659.

Grants and visits in the past 5 years: i. Grants: 1. NSF: P.I. for grant titled: Fourier based methods for analysing nonstationary and nonlinear time series [2011- 2014]. 2. NSF: P.I. for grant titled: Beyond Stationarity: Statistical inference for nonstationary processes [2008-2011]. ii. Academic visits: Universit¨at Heidelberg, June 2010 and November, 2011, Institute of Mathematical Science, Sin- gapore, June 2012, Isaac Newton Institute, Cambridge, January 2014. Service:

1. Member of Editorial Board: Statistics (2012-Present). 2. Proposal Reviewer: NSF (2008), FONDECYT - Chile Research Foundation (2010), NSA (2012), NSA (2013). 3. Proposal Panelist: NSF Statistics (Jan, 2010), NSF FRG (Nov, 2012). PhD Students Supervised and committee:

1. Advised: Jun Bum Lee (2012) 2. Committee: Lianfu Chen (2011), Priya Kohli (2012). Others whose name I cannot remember.

283 SUOJIN WANG

Education: Zhejiang University Mathematics B.S. (1982) University of Texas at Austin Statistics Ph.D. (1988) Appointments: Professor Department of Statistics, Texas A&M University 1998–present Joint Professor Department of Epidemiology and Biostatistics, Texas A&M University Health Science Center 1998–present Visiting Professor Australian National University; University of Wollongong; Monash University Fall 2013 VisitingProfessor King AbdullahUniversityofScience and Technology Fall 2011 VisitingProfessor Universityof Wollongong;Australian National University Fall 2010, Fall 2006 Visiting Professor University of Southampton; Swiss Federal Institute of Technology; University of Geneva 1999 Associate Professor Department of Statistics, Texas A&M University 1993–1998 Senior Research Fellow Survey Methods Research, Bureau of Labor Statistics, Washington, D.C. 1994 Assistant Professor Department of Statistics, Texas A&M University 1990–1993 Research Associate Department of Statistical Science, Southern Methodist University 1988–1990 Selected Publications (from about 140 refereed publications): i. Last five years: 1. “Semiparametric GEE analysis in partially linear single-index models for longitudinal data,” Annals of Statis- tics, to appear. With J. Chen, et al. 2. “A new nonparametric stationarity test of time series in time domain,” Journal of the Royal Statistical Society, Ser. B, to appear. With L. Jin and H. Wang. 3. “Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study,” Briefings in Bioinformatics, to appear. With M. Fan, et al. 4. “Children’s active commuting to school: an interplay of self-efficacy, social economic disadvantage, and environmental characteristics,” InternationalJournal of Behavioral Nutritionand Physical Activity, to appear. With W. Lu, et al. 5. “A Laplace method for under-determined Bayesian experimental designs,” Computer Methods in Applied Mechanics and Engineering, (2015), 285, 849–876. With Q. Long, et al. 6. “Semiparametric approach for non-monotone missing covariates in a parametric regression model,” Biomet- rics, (2014), 70, 299–311. With S. Sinha and K. K. Saha. 7. “A framework for scalable parameter estimation of gene circuit models using structural information,” Bioin- formatics, (2013), 29, i98–i107. With H. Kuwahara, et al. 8. Maximum Likelihood Estimation for Sample Surveys, (2012), Chapman & Hall, New York. With R. L. Cham- bers, et al. 9. “A goodness-of-fit test of logistic regression models for case-control data with measurement errors,” Biometrika, (2011), 98, 877–886. With G. Xu.

284 10. “Generalized empirical likelihood methods for analyzing longitudinal data,” Biometrika, (2010), 97, 79–93. With L. Qian and R. L. Carroll. ii. Other Noteworthy Publications: 1. “Partially linear models with missing response variables and error-prone covariates,” Biometrika, (2007), 94, 185–198. With H. Liang and R. J. Carroll. 2. “Estimation in partially linear models with missing covariates,” Journal of the American Statistical Associa- tion, (2004), 99, 357–367. With H. Liang, et al. 3. “Smoothing spline estimation in varying coefficient models,” Journal of the Royal Statistical Society, Ser. B, (2004), 66, 653–667. With R. L. Eubank, et al. 4. “Saddlepoint approximations as smoothers,” Biometrika, (2002), 89, 933–938. With A. C. Davison. 5. “High-order accurate methods for retrospective sampling problems,” Biometrika, (1999), 86, 881–897. With R. J. Carroll. 6. “Limited information likelihood analysis of survey data,” Journal of the Royal Statistical Society, Ser. B, (1998), 60, 397–411. With R. L. Chambers and A. H. Dorfman. 7. “Weighted semiparametric estimation in regression analysis with missing covariate data,” Journal of the Amer- ican Statistical Association, (1997), 92, 512–525. With C. Y. Wang, et al. 8. “A new estimator for the finite population distribution function,” Biometrika, (1996), 83, 639–652. With A. H. Dorfman. 9. “Saddlepoint expansions in finite population problems,” Biometrika, (1993), 80, 583–590. 10. “Tail probability approximations in the first-order noncircular autoregression,” Biometrika, (1992), 79, 431– 434.

Grants in last ﬁve years: i. Last ﬁve years: 1. U.S. Food and Drug Administration (2014–2015, Co-I.) 2. Scott&White Healthcare Research Grants Program Vision Award (2014–2015, Co-I.) 3. Robert Wood Johnson Foundation Childhood Obesity Prevention Program (2008–2015, Co-I.) 4. TAMU Institute of Applied Mathematics and Computational Science Innovation Award (2012–2013, P.I.) 5. Scott&White Healthcare Research Grants Program Vision Award (2012–2014, Co-I.) 6. NIH National Center on Minority Health and Health Disparities (2007–2012, Co-I.) 7. NIH National Institute of Mental Health (2009–2011, Co-P.I.) 8. National Space Biomedical Research Institute (2008–2012, Co-I.) ii. Other Noteworthy Grants: 1. National Multiple Sclerosis Society (subcontract) (2003–2006, P.I.) 2. National Institute of Environmental Health Sciences Center Grant (1998–2007, Co-P.I.) 3. National Multiple Sclerosis Society (subcontract) (2003–2005, P.I.) 4. National Multiple Sclerosis Society (2001–2003, Co-P.I.) 5. Texas Advanced Research Program (2000–2002, P.I.) 6. National Multiple Sclerosis Society (2000–2003, Co-P.I.) 7. TAMU Interdisciplinary Research Initiatives Program (1998–1999, P.I.) 8. National Security Agency (1996–1998, P.I.)

285 9. National Science Foundation (1995–1997, P.I.) 10. TAMU Program to Enhance Scholarly and Creative Activities (1995–1996, P.I.) 11. ASA/NSF/BLS Senior Research Fellowship (1994, P.I.) 12. National Science Foundation (1992–1994, P.I.) 13. Texas Advanced Research Program (1991–1994, P.I.)

Awards and Honors: Please annotate as space allows 1. Australian National University Mathematical Sciences Research Visiting Fellowship Award, 2013 2. Texas A&M University Student Led Award for Teaching Excellence, 2011 3. Texas A&M University System-wide Teaching Excellence Award, 2010 4. University-level Distinguished Achievement Award in Teaching, Texas A&M University, 2005 5. Texas A&M University Faculty Fellow, 2002-2007 6. Elected Fellow of the Institute of Mathematical Statistics, 2001 7. Elected Member of the International Statistical Institute, 2000 8. Elected Fellow of the American Statistical Association, 2000 9. College-level Distinguished Achievement Award in Teaching, Texas A&M University, 1997 10. ASA/NSF/BLS Senior Research Fellowship, 1994 11. Editor-in-Chiefof Journal of Nonparametric Statistics (2007–2012) 12. Member of Editorial Boards: Biometrics (1997–2005) Communications in Statistics (1995–2001) InterStat (1995–2009) Journal of Nonparametric Statistics (2004–2007, 2013–) Statistics & Probability Letters (2014–)

Service: Please annotate as space allows 1. Review Panelist for the National Science Foundation (multiple times, most recent in 2015) 2. Chairof theASA Journal of Nonparametric Statistics Editor-in-Chief Search Committee, 2015 3. Board of Directors of the International Chinese Statistical Association, 2005–2008 4. Board of Governors of the Zhejiang University Alumni Association, 2011–2016 5. President, Vice-President, Secretary of the Southeast Texas Chapter of the American Statistical Association, 1991– 94 6. External Examiner for a Habilitation thesis at University of Bern, Switzerland 7. External Examiner for Ph.D. theses at Monash University, Australia, University of Geneva, Switzerland, Mangalore University, India, University of Sydney, Australia, and University of Wollongong, Australia

Students Supervised:

Supervised or co-supervised 21 Ph.D. students and 20 M.S. students.

On over 90 other graduate student supervisory committees.

286 THOMAS WEHRLY

Education: University of Michigan–AnnArbor Mathematics B.S. (1969) University of Wisconsin–Madison Mathematics M.S. (1970) UniversityofWisconsin–Madison Statistics Ph.D.(1976) Appointments: Professor Department of Statistics,Texas A& M University 1988-Pres. Visiting Research Fellow Stat. Research Sect., Australian National University 1990 Associate Professor (Visiting) Department of Statistics, University of North Carolina 1985 Associate Professor Department of Statistics, Texas A&M University 1982-1988 Assistant Professor Department of Statistics, Texas A&M University 1976-1982 Publications: i. Last ﬁve years: 1. Chen, Hsiang-Chun and Wehrly, Thomas, E. (2015), “Assessing Correlation of Clustered Mixed Outcomes from a Multivariate Generalized Linear Mixed Model,” Statistics in Medicine, 34, 704-720. ii. Other Noteworthy Publications: 1. Yu, J. and Wehrly, T. E., (2004)“An approach to the residence time distributionfor stochasticmulti-compartment models”, Mathematical Biosciences, 191, 185-205. 2. Matis, J. H. and Wehrly, T. E. (1998), “A General Approach to Non-Markovian Compartmental Models”, Journal of Pharmacokinetics and Biopharmaceutics, 26, 437-456 3. Cardwell, K. F. and Wehrly, T. E. (1997), “A Rank Test for Distinguishing Environmentally and Genetically Induced Disease Resistance in Plant Varieties,” Biometrics, 53, 195-206. 4. Chambers, R. L., Dorfman, A. H. and Wehrly, T. E. (1993). “Bias Robust Estimation in Finite Populations using Nonparametric Calibration,” Journal of the American Statistical Association, 88, 268-277. 5. J. Baek and T. E. Wehrly, (1993), “Kernel Estimation for Additive Models under Dependence,” Stochastic Processes and Their Applications, 47, 95–112. 6. Hart, J. D. and Wehrly, T. E. (1992). “Kernel regression estimation when the boundary region is large with an application to testing the adequacy of polynomial models,” Journal of the American Statistical Association, 87, 1018–1024. 7. Hall, P. G. and Wehrly, T. E. (1991). “A geometrical method for removing edge effects from kernel-type nonparametric regression estimators,” Journal of the American Statistical Association, 86, 665-672. 8. Hart, J.D. and Wehrly, T.E. (1986). “Kernel regression estimation using repeated measurements data,” Journal of the American Statistical Association, 81, 1080-1088. 9. LaRiccia, V.N. and Wehrly, T.E. (1985). “Asymptotic properties of a family of minimum quantile distance estimators, Journal of the American Statistical Association, 80, 742-747.

Grants in last ﬁve years: i. Last ﬁve years: 1. “UBM Integrated Undergraduate Experiences in Biological and Mathematical Sciences”, Vincent Cassone, P.I., Thomas Wehrly one of 4 co-PIs, $499646, 5%, 9/15/04-8/31/11.

287 ii. Other Noteworthy Grants: 1. “Frontiers of Statistical Research: Forty Years of Statistics at Texas A&M University,” National Science Foundation, $11250, T. E. Wehrly, P.I, 10/11/02-10/12/02. 2. “Nonparametric Estimation of Functions Based Upon Correlated Observations,” Ofﬁce of Naval Research, 9/1/85-8/31/88, Renewed to 9/30/90. J. D. Hart, T. E. Wehrly, Co-Principal Investigators.

Awards and Honors: Please annotate as space allows 1. Member of Editorial Boards: The American Statistician (1987–1993). Statistics and Probability Letters (1982–2007).

2. VisitingScholar: Australian National University, Canberra, Australia, (January–May 1990).

Service:

1. Chair, Undergraduate Committee, Department of Statistics, 2013–14, chaired the committee responsible for the proposal to Texas A&M University for an undergraduate degree in statistics. 2. Chair, Personnel and Tenure Committee 2009–13 3. Chair, Parzen Prize Committee, 2010–14. 4. Chair, Athletics Council, Texas A&M University, 2004–15. 5. Treasurer, Texas Kappa Chapter of Phi Beta Kappa at Texas A&M University, 2007–14. 6. Member, SEC Validation of Academic Credentials Review Committee, 2012–15 7. Member, University Disciplinary Appeals Panel, 2008–14. 8. Member, Faculty and Staff Interaction Team (multidepartment committee), 2013–14. 9. Member, Implementation Task Force for Athletics (President’s committee), 2010–11 10. Member, Vision 2020, Midterm Review Task Force: Imperative 4 Study Team, 2010–11 11. Member, President’s Task Force for Athletics, 2009–11 12. Member of departmental committees including Graduate Service Committee (2004–15), Graduate Program Com- mittee (2005–14), Graduate Admissions Committee (2014–15), Department Head Search Committee (2013–14) 13. Speaker, Faculty Senate, Texas A&M University, 1999–2000.

Students Supervised: 1. Hsiang-chun Chen, Ph. D., August 2013. Inference for Clustered Mixed Outcomes from a MultivariateGeneralized Linear Mixed Model. 2. Nai-Wei Chen, Ph. D., December 2011. Goodness-of-Fit Test Issues in Generalized Linear Mixed Models. 3. Daniel Glab, Ph. D., May 2011. Testing Lack-of-Fit of Generalized Linear Models Via Laplace Approximation 4. Jihnhee Yu, Ph.D., August 2003. Approaches to the Multivariate Random Variables Associated with Stochastic Processes.

288 5. Shao-Hung Wang, Ph.D., May 1995. A Data-Driven Smoothing Parameter Selection for Robust Nonparametric Regression. 6. Shenq-Nah (Christine) Yang, Ph.D., December 1991. A Matrix Exponential and Bootstrap Analysis of Nonlinear Least Squares Estimation for Compartmental Models. 7. Jangsun Baek, Ph.D., August 1991, Kernel Estimation for Nonparametric Additive Models. 8. Joey Ensor, Ph.D., August 1989, A Two-Compartment, Irreversible Flow Model with Clustering. 9. Eileen King, Ph.D., December 1988. A Test for the Equality of Two Regression Curves based on Kernel Smoothers. (co-chair, J. D. Hart) 10. Joshua Baker, Ph.D., May 1985. ConditionalLeast Squares Estimation and Design for Continuous-TimeStochastic Processes.

11. Vincent LaRiccia, Ph.D., December 1979. A Family of Minimum Quantile Distance Estimators.

Master’s students supervised over the last 5 years (13 Master’s students supervised during previous years):

1. Emily Seem, M.S., expected August 2015 2. Zachary Scott, M.S., May 2014 3. Huiwen Wilkerson, M.S., May 2014 4. Tara Cope, M.S., August 2013 5. Angela Brown, M.S., May 2013 6. Jennifer Whitten, M.S., December 2012 7. Michael Yingling, M.S., December 2012 8. Alexander Little, M.S., May 2012 9. Cynthia Franklin, M.S., May 2012 10. Karen Connelly, M.S., May 2012

289 LAN ZHOU

Education: University of California at Berkeley Statistics Ph.D. (1997) Beijing University, China Probabilityand Statistics M.A. (1992) Beijing University, China Probabilityand Statistics B.A. (1989) Appointments: Associate Professor Department of Statistics, Texas A&M University 2014-Present Assistant Professor Department of Statistics, University of Pennsylvania 2008-2014 Research Assistant Professor Department of Statistics, University of Pennsylvania 2005-2008 Research Assistant Professor Department of Statistics, University of Pennsylvania 2005 Biostatistician Department of Biostatistics, CCEB, University of Pennsylvania 1998-2004 Statistical Consultant Analysis and Inference, Inc., Swarthmore, PA 1998 Research Expertise: Statistical methodology and application in bioinformatics, nutrition and epidemiology, spline/nonparametric smoothing, functional and longitudinal data analysis

Publications: i. Last five years: 1. Guo, M.†, Zhou, L.†, Huang, J. Z. and Härdle W. K. (2015) Functional data analysis of generalized quantile regressions. Statistics and Computing, 25, 189–202. († contributed equally) 2. Assaad, H., Hou, Y., Zhou, L., Carroll, R. J., and Wu, G. (2015). Rapid publication-ready MS-word tables for two-way ANOVA. SpringerPlus, 4:33. 3. Zhou, L. and Pan, H.∗, (2014). Smoothing noisy data for irregular regions using penalized bivariate splines on triangulations. Computational Statistics, Vol 29, 263–281. (∗ graduate student) 4. Zhou, L. and Pan, H.∗ (2014). Principal component analysis of two-dimensional functional data. Journal of Computational and Graphical Statistics, Vol 23, 779–801. (∗ graduate student) 5. Cheng, G., Zhou, L., Chen, X. and Huang, J.Z. (2014). Efficient estimation of semiparametric copula models for bivariate survival data. Journal of Multivariate Analysis, Vol 123, 330–344. 6. Cheng, G., Zhou, L. and Huang, J.Z. (2014). Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data. Bernoulli, Vol 20, 141–163. 7. Assaad, H., Yao, K., Tekwe, C.D., Feng, S., Bazer, F. W., Zhou, L., Carroll, R. J., Meininger, C. J. and Wu, G. (2014). Analysis of energy expenditure in diet-induced obses rats. Frontiers in Bioscience, Vol 19: 967–985. 8. Assaad, H., Zhou, L., Carroll, R. J., and Wu, G. (2014). Rapid publication-ready MS-word tables for one-way ANOVA. SpringerPlus, 3:474. 9. G. Wu, J. Zhu, J. Yu, L. Zhou, J. Z. Huang, and Z. Zhang (2014). Evaluation of five methods for genome-wide circadian gene identification. Journal of Biological Rhythms, Vol 29, 231–242. 10. Jia, Q., Ivanov, I., Zlatev, Z. Z., Alaniz, R. C., Weeks, B. R., Callaway, E. S., Goldsby, J. S., Davidson, L. A., Fan, Y., Zhou, L., Lupton, J. R., McMurray, D. N., Chapkin, R. S. (2011) Dietary fish oil and curcumin combine to modulate colonic cytokinetics and gene expression in DSS-treated mice. British Journal of Nutrition, Vol 106(4), 519–29. 11. Zhou, L., Huang, J. Z., Martinez, J. G., Maity, A., Baladandayuthapani, V., Carroll., R. J.(2010) Reduced rank mixed effects models for spatially correlated hierarchical functional data. Journal of American Statistical Associ- ation, Vol 105, 390–400.

290 12. Martinez, J. G., Liang, F., Zhou, L., Carroll, R. J. (2010) Longitudial functional principal component selection via Stochastic Approximation Monte Carlo. Canadian Journal of Statistics, Vol 38, 256–270. 13. Wei, J.∗ and Zhou, L. (2010) Model selection using modified AIC and BIC in joint modeling of paired functional data. Statistics & Probability Letters, Vol 80, 1918–1924. (∗ graduate student) ii. Publications Before 2010: 1. Miki, A., Liu, G. T., Goldsmith, Z. G., Zhou, L., Siegfried, J., Hulvershorn, J., Raz, J., Haselgrove, J.C. (2001) Effects of check size on visual cortex activation studied by functional magnetic resonance imaging. Ophthalmic Research, 33, 180–184. 2. Huang, J. Z., Wu, C. O., Zhou, L. (2002) Varying coefficient models and basis function approximations for the analysis of repeated measurements. Biometrika, 89, 111–128. 3. Renbaum L., Ufberg D., Sammel M., Zhou L., Jabara S., Barnhart K. T. (2002)Reliabilityof hysterosalpingogram (HSG): Clinicians vs radiologists. Fertility and Sterility, 78, 614–618. 4. Hennessy S., Bilker, W. B., Zhou L., Weber, A. I., Brensinger C., Wang, Y., Strom, B. L. (2003) Retrospective drug utilization review, prescribing errors, and clinical outcomes. The Journal of the American Medical Association, 29, 1494–1499 5. Norman, S., Localio, A. R., Zhou, L., Bernstein, L., Coates, R., Flagg, E., Marchbanks, P., Malone, K., Weiss, L., Lee, N., Nadel, M. (2003) Validation of self-reported screening mammography histories among women with and without breast cancer. American Journal of Epidemiology, 158, 264–271. 6. Barnhart, K., Sammel, M. D., Rnaudo, P. F., Zhou, L., Guo, W., Hummel, A. C. (2004). BhCG doubling time in symptomatic patients with an early intrauterine pregnancy: The curves redefined. Obstetrics and Gynecology, 104, 50–55. 7. Barnhart, K., Sammel, M. D., Chung, K., Zhou, L., Hummel, A. C., and Guo, W. (2004). Decline of serum human chorionic gonadotropin and spontaneous complete abortion: defining the normal curve. Obstetrics and Gynecology, 104, 975–981. 8. Huang, J. Z., Wu, C. O. and Zhou, L. (2004). Polynomial spline estimation and inference for varying coefficient models with longitudinal data. Statistica Sinica, 14, 763–788. 9. Foulkes, A. S., Reilly, M., Zhou, L., Wolfe, M. and Rader, D. J. (2005) Mixed modelling to characterize genotype- phenotype associations. Statistics in Medicine, 24, 775-789. 10. Norman, S. A., Localio, A. R., Zhou, L., Weber, A. L., Coates, R. J., Malone, K. E., Bernstein, L., Marchbanks, P. A., Liff, J. M., Lee, N. C., Nadel, M. R. (2006) Benefit of screening mammography in reducing the rate of late-stage breast cancer diagnosis (United States). Cancer Causes Control, 17, 921–929. 11. Chung K., Sammel M. D., Zhou L., Hummel A. C., Guo W., Barnhart K. (2006). Defining the curve when initial levels of human chorionic gonadotropin in patients with spontaneous abortions are low. Fertility and Sterility, 85, 508–510. 12. Localio A. R., Zhou L., Norman S. A. (2006) Measuring screening intensity in case-control studies of the efficacy of mammography. American Journal of Epidemiology, 164, 272–281. 13. Seeber B., Sammel M. D., Guo W., Zhou L., Hummel A. C., Barnhart K. T. (2006) Application of redefined hCG curves for the diagnosis of women at risk for ectopic pregnancy. Fertility and Sterility, 86, 454–459. 14. Silva C., Sammel M. D., Zhou L., Gracia C., Guo W., Hummel A. C., Barnhart K. T. (2006) hCG profile for Women with an Ectopic Pregnancy. Obstetrics and Gynecology, 107, 605–610. 15. Zhang P., Kim W., Zhou L., Wang N., Ly L. H., McMurray D. N., Chapkin R. S. (2006). Dietary fish oil inhibits antigen-specific murine Th1 cell development by suppression of clonal expansion. Journal of Nutrition, 136(9), 2391–2398. 16. Azzoni L., Chehimi, J., Zhou, L., Foulkes, A. S., June, R., Maino, V. C., Landay, A., Rinaldo, C., Jacobson, L. P., Montaner, L. J. (2007) Early and delayed benefits of HIV-1 suppression: Timeline of recovery of innate immunity effector cells. AIDS, 21, 293–305.

291 17. Huang, J. Z., Zhang, L., Zhou, L. (2007) Efficient estimation in marginal partially linear models for longitudinal/clustered data using splines. Scandinavian Journal of Statistics, 34, 451–477. 18. Matis, J. H., Zhou, L., Kiffe T. R., Matis T. I. (2007) Fitting cumulative size mechanistic models to insect population data: A nonlinear random effects model analysis. Journal of Indian Society of Agricultural Statistics, 61, No. 2, 147-155. 19. Zhou, L., Huang, J. Z. Carroll, R. J. (2008) Joint modeling of paired sparse functional data using principal components. Biometrika, 95, No. 3, 601-619 20. Fan Y. Y., Kim W., Callaway E., Smith R., Jia Q., Zhou L., McMurray D. N., Chapkin R. S. (2008) Fat-1 transgene expression prevents cell culture-induced loss of membrane n-3 fatty acids in activated CD4(+) T-cells. Prostaglandins Leukot Essent Fatty Acids, 2008, 79, 209–214. 21. Qiao, Z.∗, Zhou, L. and Huang, J. Z. (2008) Effective linear discriminant analysis for high dimensional, low sample size data. Proceedings of 2008 World Congress of Engineering (WCE 2008), 1070–1075. (The Certificate of Merit Award for The 2008 International Conference of Computational Statistics and Data Engineering, WCE 2008) (∗ graduate student) 22. Qiao, Z.∗, Zhou, L. and Huang, J. Z. (2009) Sparse linear discriminant analysis for high dimensional, low sample size data. IAENG International Journal of Computer Science, Vol 39, 48–60. (∗ graduate student) 23. Fan, Y. Y., Zhan, Y., Aukema, H. M., Davidson, L. A., Zhou, L., Callaway, E., Tian, Y., Weeks, B. R., Lupton, J. R., Toyokuni, S., Chapkin, R. S. (2009) Proapoptotic effects of n-3 fatty acids are enhanced in colonocytes of manganese-dependent superoxide dismutase knockout mice. Journal of Nutrition, Vol 139, 1328–1332. Grants in last five years: i. Last five years: 1. National Science Foundation (2009-2013), $262,106, “Statistical Methods for Complex Functional Data,” (PI) Awards and Honors: 1. The Certificate of Merit Award, International Conference of Computational Statistics and Data Engineering, World Congress of Engineering, 2008 for the paper “Effective linear discriminant analysis for high dimensional, low sample size data” 2. General Program Prize Paper, American Society for Reproductive Medicine, 2003 for the paper “Decline of serum human chorionic gonadotropin and spontaneous complete abortion: defining the normal curve” 3. University of California, Berkeley: University Fellowship, 1992-1993 Service: 1. Referee for 18 journals 2. Organizer of Invited Session: Recent Advances in Longitudinal and Functional Data Analysis International Chinese Statistical Association 2012 Applied Statistics Symposium, Boston, June 23-26, 2012. Course Taught: STAT 211 (Principles of Statistics), STAT 302 (Statistical Methods), STAT 627 (Nonparametric Function Estimation)

Ph.D. student advising committee: Shuai Chen (Chair), Huijun Pan (Co-Chair), Andrew Middleton Redd, Adrian Barquero Sanchez, Yei Eun Shin, Ya Su (Co- Chair), Jiawei Wei (Co-Chair), Tae Ho Yoon

M.S. student advising committee: Michael James Alzubaydi, Deron Aucoin (Chair), Dai Chen (Chair), Shuai Chen (Co-Chair), Cody Cox, Eric Frederiksen, John J. Gosink (Chair), Barney Govan, Zhuoya He, Ming Jia, Geoffrey M. Lucas (Chair), Jennifer Phan, Eric Przybylinski (Chair), Yiyi Wang, Yuen Sum S. Wong, Mi Zhang, Tinyi Zhu

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