Martin J. Strauss April 22, 2015
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Anna C. Gilbert
Anna C. Gilbert Dept. of Mathematics University of Michigan 530 Church Street Ann Arbor, MI 48109-1109 [email protected] 734-763-5728 (phone) http://www.math.lsa.umich.edu/~annacg 734-763-0937 (fax) Revision date: 30 October, 2017. Research • General interests: analysis, probability, signal processing, and algorithms. • Specialization: randomized algorithms with applications to massive datasets and signal processing. Education • Ph.D., Mathematics, Princeton University, June 1997, Multiresolution homogenization schemes for differential equations and applications, Professor Ingrid Daubechies, advisor. • S.B., Mathematics (with honors), University of Chicago, June 1993. Positions Held • Herman H. Goldstine Collegiate Professor. Department of Mathematics, University of Michigan, 2014{ present. • Full Professor (Courtesy appointment). Division of Electrical and Computer Engineering, University of Michigan, 2010{present. • Full Professor. Department of Mathematics, University of Michigan, 2010{present. • Associate Professor (Courtesy appointment). Division of Electrical and Computer Engineering, Uni- versity of Michigan, 2008{2010. • Associate Professor. Department of Mathematics, University of Michigan, 2007{2010. • Assistant Professor. Department of Mathematics, University of Michigan, 2004{2007. • Principal technical staff member. Internet and Network Systems Research Center, AT&T Labs-Research, 2002{2004. • Senior technical staff member. Information Sciences Research Center, AT&T Labs-Research, 1998{ 2002. • Visiting instructor. Department of Mathematics, Stanford University, Winter quarter 2000. • Postdoctoral research associate. Yale University and AT&T Labs-Research, 1997{1998. • Intern. Lucent Technologies Bell Laboratories, summer 1996. • Research assistant. Princeton University, 1994{1995. • Intern. AT&T Bell Laboratories, summers 1993{1995. Publications Refereed Journal Publications • F. J. Chung, A. C. Gilbert, J. G. Hoskins, and J. C. Schotland, \Optical tomography on graphs", Inverse Problems, Volume 33, Number 5, 2017. -
Project Summary for ARO MURI Topic
Project Summary for ARO MURI Topic #28 “Model Classes, Approximation, and Metrics for Dynamic Processing of Urban Terrain Data” Terrain models are a rich resource to both military and civilian sectors including such applications as autonomous navigation, mission planning, battlefield assessment, and emer- gency preparedness. Their usefulness depends on succinct encoding of terrain data not only for fast query and retrieval but also for efficient and accurate transmission of this data over restricted communication channels. Some applications demand real-time conversion of point cloud data to a continuous terrain representation. Unfortunately, the development of processing tools for terrain surfaces has been ad hoc and too often simply borrowed from image processing. Terrain maps are not conventional images and most image processing tools fail to extract the essential geometry and topology in terrains and fail to adhere to particular demands in the typical terrain application settings. While newer terrain modeling algorithms are meeting some success in capturing and priori- tizing geometry through techniques from differential geometry, they fail to capture high order topology because they treat terrains as functional surfaces. This is particularly damaging in urban terrain where man-made structures such as overhangs, bridges, arches, towers, and light poles, are not captured correctly. In addition, the metrics used to make decisions on bit allocation and accuracy of fit do not always match well with the targeted applications. Meeting these application demands requires substantially new metrics to measure distortion and new representation systems (explicit/implicit) that capture topology and geometry of surfaces. Implicit representations provide a simple way to capture higher genus topology, sig- nificantly reduce the number of bits needed to encode terrain (especially in urban settings), and allow for fast assimilation of line-of-sight and no-fly regions for navigation. -
Focm 2017 Foundations of Computational Mathematics Barcelona, July 10Th-19Th, 2017 Organized in Partnership With
FoCM 2017 Foundations of Computational Mathematics Barcelona, July 10th-19th, 2017 http://www.ub.edu/focm2017 Organized in partnership with Workshops Approximation Theory Computational Algebraic Geometry Computational Dynamics Computational Harmonic Analysis and Compressive Sensing Computational Mathematical Biology with emphasis on the Genome Computational Number Theory Computational Geometry and Topology Continuous Optimization Foundations of Numerical PDEs Geometric Integration and Computational Mechanics Graph Theory and Combinatorics Information-Based Complexity Learning Theory Plenary Speakers Mathematical Foundations of Data Assimilation and Inverse Problems Multiresolution and Adaptivity in Numerical PDEs Numerical Linear Algebra Karim Adiprasito Random Matrices Jean-David Benamou Real-Number Complexity Alexei Borodin Special Functions and Orthogonal Polynomials Mireille Bousquet-Mélou Stochastic Computation Symbolic Analysis Mark Braverman Claudio Canuto Martin Hairer Pierre Lairez Monique Laurent Melvin Leok Lek-Heng Lim Gábor Lugosi Bruno Salvy Sylvia Serfaty Steve Smale Andrew Stuart Joel Tropp Sponsors Shmuel Weinberger 2 FoCM 2017 Foundations of Computational Mathematics Barcelona, July 10th{19th, 2017 Books of abstracts 4 FoCM 2017 Contents Presentation . .7 Governance of FoCM . .9 Local Organizing Committee . .9 Administrative and logistic support . .9 Technical support . 10 Volunteers . 10 Workshops Committee . 10 Plenary Speakers Committee . 10 Smale Prize Committee . 11 Funding Committee . 11 Plenary talks . 13 Workshops . 21 A1 { Approximation Theory Organizers: Albert Cohen { Ron Devore { Peter Binev . 21 A2 { Computational Algebraic Geometry Organizers: Marta Casanellas { Agnes Szanto { Thorsten Theobald . 36 A3 { Computational Number Theory Organizers: Christophe Ritzenhaler { Enric Nart { Tanja Lange . 50 A4 { Computational Geometry and Topology Organizers: Joel Hass { Herbert Edelsbrunner { Gunnar Carlsson . 56 A5 { Geometric Integration and Computational Mechanics Organizers: Fernando Casas { Elena Celledoni { David Martin de Diego . -
Program Committee ICM 2010 Hendrik W. Lenstra (Chair), Universiteit Leiden, Netherlands Assistant to the Chair: Jeanine Daems, Universiteit Leiden,Netherlands Louis H
Program Committee ICM 2010 Hendrik W. Lenstra (chair), Universiteit Leiden, Netherlands assistant to the chair: Jeanine Daems, Universiteit Leiden,Netherlands Louis H. Y. Chen, National University of Singapore, Singapore Dusa McDuff, Barnard College, Columbia University, New York,U.S.A. Etienne´ Ghys, CNRS – Ecole´ Normale Sup´erieure de Lyon, France Ta-Tsien Li, Fudan University, Shanghai, China Jos´eAntonio de la Pe˜na, Universidad Nacional Aut´onoma deM´exico,Mexico Alfio Quarteroni, Ecole´ Polytechnique F´ed´erale de Lausanne, Switzerland and Politecnico di Milano, Italy S. Ramanan, Chennai Mathematical Institute, India Terence Tao, University of California, Los Angeles, U. S. A. Eva´ Tardos, Cornell University, Ithaca, U. S. A. Anatoly Vershik, St. Petersburg branch of Steklov Mathematical Institute, St. Petersburg, Russia Panel 1, Logic and foundations Core members: Theodore Slaman (University of California, Berkeley, U. S. A.) (chair) Alain Louveau (Universit´ede Paris VI, France) Additional members : Ehud Hrushovski (Hebrew University, Jerusalem, Israel) Alex Wilkie (University of Manchester, U. K.) W. Hugh Woodin (University of California, Berkeley, U. S. A.) Panel 2, Algebra Core members: R. Parimala (Emory University, Atlanta, U. S. A.) (chair) Vladimir L. Popov (Steklov Institute, Moscow, Russia) Raphael Rouquier (University of Oxford, U. K.) Additional members : David Eisenbud (University of California, Berkeley, U. S. A.) Maxim Kontsevich (Institut des Hautes Etudes´ Scientifiques, Bures-sur-Yvette, France) Gunter Malle (Universit¨at -
Focm 2017 Foundations of Computational Mathematics Barcelona, July 10Th-19Th, 2017 Organized in Partnership With
FoCM 2017 Foundations of Computational Mathematics Barcelona, July 10th-19th, 2017 http://www.ub.edu/focm2017 Organized in partnership with Workshops Approximation Theory Computational Algebraic Geometry Computational Dynamics Computational Harmonic Analysis and Compressive Sensing Computational Mathematical Biology with emphasis on the Genome Computational Number Theory Computational Geometry and Topology Continuous Optimization Foundations of Numerical PDEs Geometric Integration and Computational Mechanics Graph Theory and Combinatorics Information-Based Complexity Learning Theory Plenary Speakers Mathematical Foundations of Data Assimilation and Inverse Problems Multiresolution and Adaptivity in Numerical PDEs Numerical Linear Algebra Karim Adiprasito Random Matrices Jean-David Benamou Real-Number Complexity Alexei Borodin Special Functions and Orthogonal Polynomials Mireille Bousquet-Mélou Stochastic Computation Symbolic Analysis Mark Braverman Claudio Canuto Martin Hairer Pierre Lairez Monique Laurent Melvin Leok Lek-Heng Lim Gábor Lugosi Bruno Salvy Sylvia Serfaty Steve Smale Andrew Stuart Joel Tropp Sponsors Shmuel Weinberger Wifi access Network: wifi.ub.edu Open a Web browser At the UB authentication page put Identifier: aghnmr.tmp Password: aqoy96 Venue FoCM 2017 will take place in the Historical Building of the University of Barcelona, located at Gran Via de les Corts Catalanes 585. Mapa The plenary lectures will be held in the Paraninf (1st day of each period) and Aula Magna (2nd and 3rd day of each period). Both auditorium are located in the first floor. The poster sessions (2nd and 3rd day of each period) will be at the courtyard of the Faculty of Mathematics, at the ground floor. Workshops will be held in the lecture rooms B1, B2, B3, B5, B6, B7 and 111 in the ground floor, and T1 in the second floor. -
40 IS10 Abstracts
40 IS10 Abstracts IP1 age and video restoration. I will present the framework Approximate Inference in Graphical Models: The and provide numerous examples showing state-of-the-art Fenchel Duality Perspective results. I will then briefly show how to extend this to im- age classification, deriving energies and optimization pro- Quite a number of problems involving inference from data, cedures that lead to learning non-parametric dictionaries whether visual data or otherwise, can be set as a prob- for sparse representations optimized for classification. I lem of finding the most likely setting of variables of a will conclude by showing results on the extension of this to joint distribution over locally interacting variables. These sensing and the learning of incoherent dictionaries. Models include stereopsis, figure-ground segmentation, model-to- derived from universal coding are presented as well. The image matching, super-resolution, and so forth. Inference work I present in this talk is the result of great collabo- over locally interacting variables can be naturally repre- rations with J. Mairal, F. Rodriguez, J. Martin-Duarte, I. sented by a graphical model, however exact inference over Ramirez, F. Lecumberry, F. Bach, M. Elad, J. Ponce, and general graphs is computationally unwieldy. In the context A. Zisserman. of approximate inference, I will describe a general scheme for message passing update rules based on the framework Guillermo Sapiro of Fenchel duality. Using the framework we derive all University of Minnesota past inference algorithms like the Belief Propagation sum- Dept Electrical & Computer Engineering product and max-product, the Tree-Re-Weighted (TRW) [email protected] model as well as new convergent algorithms for maximum- a-posteriori (MAP) and marginal estimation using ”convex free energies”. -
Future Directions in Compressed Sensing and the Integration of Sensing and Processing What Can and Should We Know by 2030?
Future Directions in Compressed Sensing and the Integration of Sensing and Processing What Can and Should We Know by 2030? Robert Calderbank, Duke University Guillermo Sapiro, Duke University Workshop funded by the Basic Research Office, Office of the Assistant Prepared by Brian Hider and Jeremy Zeigler Secretary of Defense for Research & Engineering. This report does not Virginia Tech Applied Research Corporation necessarily reflect the policies or positions of the US Department of Defense Preface OVER THE PAST CENTURY, SCIENCE AND TECHNOLOGY HAS BROUGHT REMARKABLE NEW CAPABILITIES TO ALL SECTORS of the economy; from telecommunications, energy, and electronics to medicine, transportation and defense. Technologies that were fantasy decades ago, such as the internet and mobile devices, now inform the way we live, work, and interact with our environment. Key to this technological progress is the capacity of the global basic research community to create new knowledge and to develop new insights in science, technology, and engineering. Understanding the trajectories of this fundamental research, within the context of global challenges, empowers stakeholders to identify and seize potential opportunities. The Future Directions Workshop series, sponsored by the Basic Research Office of the Office of the Assistant Secretary of Defense for Research and Engineering, seeks to examine emerging research and engineering areas that are most likely to transform future technology capabilities. These workshops gather distinguished academic and industry researchers from the world’s top research institutions to engage in an interactive dialogue about the promises and challenges of these emerging basic research areas and how they could impact future capabilities. Chaired by leaders in the field, these workshops encourage unfettered considerations of the prospects of fundamental science areas from the most talented minds in the research community. -
Computational Methods for Sparse Solution of Linear Inverse Problems Joel A
PROCEEDINGS OF THE IEEE. SPECIAL ISSUE ON APPLICATIONS OF SPARSE REPRESENTATION AND COMPRESSIVE SENSING, VOL. XX, NO. YY, MONTH 20091 Computational Methods for Sparse Solution of Linear Inverse Problems Joel A. Tropp, Member, IEEE and Stephen J. Wright Abstract—The goal of the sparse approximation problem is find good solutions to large sparse approximation problems in to approximate a target signal using a linear combination of a reasonable time. few elementary signals drawn from a fixed collection. This paper In this paper, we give an overview of algorithms for sparse surveys the major practical algorithms for sparse approximation. Specific attention is paid to computational issues, to the circum- approximation, describing their computational requirements stances in which individual methods tend to perform well, and to and the relationships between them. We also discuss the the theoretical guarantees available. Many fundamental questions types of problems for which each method is most effective in electrical engineering, statistics, and applied mathematics in practice. Finally, we sketch the theoretical results that can be posed as sparse approximation problems, making these justify the application of these algorithms. Although low- algorithms versatile and relevant to a plethora of applications. rank regularization also falls within the sparse approximation Index Terms—Sparse Approximation, Compressed Sensing, framework, the algorithms we describe do not apply directly Matching Pursuit, Convex Optimization to this class of problems. Subsection I-A describes “ideal” formulations of sparse I. INTRODUCTION approximation problems and some common features of algo- INEAR inverse problems arise throughout engineering rithms that attempt to solve these problems. Section II provides L and the mathematical sciences. -
Mathematics People
people.qxp 10/30/01 1:59 PM Page 1341 Mathematics People SIAM Prizes Awarded MAA Writing Awards The Society for Industrial and Applied Mathematics (SIAM) Presented awarded several prizes at its annual meeting in San Diego in July 2001. The Mathematical Association of America (MAA) presented EDUARDO D. SONTAG of Rutgers University received the several awards for excellence in expository writing at its W. T. and Idalia Reid Prize. This prize is given for research Summer Mathfest in Madison, Wisconsin, in August 2001. in or other contributions to the areas of differential equa- The Carl B. Allendoerfer Awards are given for articles tions and control theory. It carries a cash award of $10,000. published in Mathematics Magazine and carry a cash award WILLIAM W. SYMES of Rice University was awarded the of $500. The award for 2001 was given to JAMES N. BRAWNER, Ralph Kleinman Prize, which carries a cash award of $5,000. Armstrong Atlantic State University, for his article “Din- The Kleinman Prize is awarded to one individual for out- ner, Dancing, and Tennis, Anyone?”, Mathematics Magazine, standing research or other contributions that bridge the Vol. 73, 2000, and to RAPHAEL FALK JONES, Brown University, gap between mathematics and applications. and JANICE L. PEARCE of Berea College for their joint article THOMAS Y. HOU of the California Institute of Technology “A Postmodern View of Fractions and the Reciprocals of was awarded the James H. Wilkinson Prize in Numerical Fermat Primes”, Mathematics Magazine, Vol. 73, 2000. Analysis and Scientific Computing. This prize is awarded The Trevor Evans Award is given to authors of excep- for research in or other contributions to numerical analy- tional articles that are accessible to undergraduates and sis and scientific computing during the six years preced- that were published in Math Horizons. -
Department of Mathematics University of South Carolina Self-Study November 2002
Department of Mathematics University of South Carolina Self-Study November 2002 Short Curricula Vitæ and The Publications of the Mathematics Faculty George Androulakis Graduate Education: University of Texas, Austin Ph.D. August 1996; Thesis Advisor: Haskell P. Rosenthal Undergratuate Education: University of Crete, Greece. Professional Employment Permanent Positions 2000-present Assistant Professor University of South Carolina, Columbia Visiting Positions 1998-2000 Visiting Assistant Professor Texas A & M University 1996-1998 Postdoctoral Fellow University of Missouri, Columbia 1994-1996 Assistant Instructor University of Texas, Austin Awards and Honors 1998 NSF Young Investigator Award 1995-1996 Professional Development Award University of Texas, Austin Publications: 14 articles (8 in print, 2 accepted, 1 submitted, 3 in preparation) Invited Addresses and External Colloquia/Seminars: 22 in 14 different institutions in 2 countries. Grant Support: 1 NSF research grant: 1999-2002. Conference Organizing or Program Committees: 1 regional conference. Refereeing and Reviewing: Referee for 6 professional journals. Reviewer for 1 funding agency. Re- viewer for Mathematical Reviews. November 15, 2002 George Androulakis The Publications of George Androulakis 1. G. Androulakis and T. Schlumprecht, Strictly singular, non-compact operators exist on the space of Gowers and Maurey, J. London Math. Soc. (2) 64 (2001), 655–674. 1 843 416 2. George Androulakis, Peter G. Casazza, and Denka N. Kutzarova, Some more weak Hilbert spaces, Canad. Math. Bull. 43 (2000), 257–267. MR 2002h:46012 3. George Androulakis and Stamatis Dostoglou, Positivity results for the Yang-Mills-Higgs Hessian, Pacific J. Math. 194 (2000), 1–17. MR 2001h:58015 4. G. Androulakis and E. Odell, Distorting mixed Tsirelson spaces, Israel J. -
Annual Report 2013
DEPARTMENT OF SURGERY Annual Report 2013 Mary C. McCarthy, MD, FACS Elizabeth Berry Gray Chair and Professor For the period including January 1, 2013 – December 31, 2013 Table of Contents Statement from the Chair Faculty Group Photo Division Reports Programs Graduating Chiefs Residents Resident Awards Fully Affiliated Faculty Clinical Professional Associates Clinical Faculty Teaching Scholarly Activity Faculty Service Activity Patient Care Summary Staff Honors and Awards Hosted Events Other Stewardship Statement from the Chair_______________________________ The Wright State University Department of Surgery is one of the leading providers of advanced clinical care in the greater Dayton area, and a nationally recognized residency training program. Collaboration with basic and clinical scientists at the university has resulted in several “firsts” for our department this year, particularly in the area of robotic vascular surgery. We have developed an academic environment focused on our mission of excellent patient care, research and medical education: • Multidisciplinary clinical programs in Surgical Oncology at the new Miami Valley Hospital Cancer Center • A surgical training program that focuses on graduating excellent general surgeons, capable of practicing in a rural, urban, or global community, or competing for top-notch fellowships • WSU, leading in the development of endovascular surgery, has the third Magellan vascular robot in the country at Miami Valley Hospital, through the generous gift of Mr. Robert Brethen, • Research teams addressing questions of clinical and translational importance • Departmental stewardship, building the department to meet the complex and challenging needs of healthcare in our community. Recruitment of surgical oncologists and vascular surgeons has been supported by John Berry, Jr. Our patients, however, require more than technical expertise and advanced technology. -
Anna C. Gilbert
Anna C. Gilbert Dept. of Mathematics University of Michigan 530 Church Street Ann Arbor, MI 48109-1109 [email protected] 734-763-5728 (phone) http://www.math.lsa.umich.edu/~annacg 734-763-0937 (fax) Revision date: 10 August, 2017. Research • General interests: analysis, probability, signal processing, and algorithms. • Specialization: randomized algorithms with applications to massive datasets and signal processing. Education • Ph.D., Mathematics, Princeton University, June 1997, Multiresolution homogenization schemes for differential equations and applications, Professor Ingrid Daubechies, advisor. • S.B., Mathematics (with honors), University of Chicago, June 1993. Positions Held • Herman H. Goldstine Collegiate Professor. Department of Mathematics, University of Michigan, 2014{ present. • Full Professor (Courtesy appointment). Division of Electrical and Computer Engineering, University of Michigan, 2010{present. • Full Professor. Department of Mathematics, University of Michigan, 2010{present. • Associate Professor (Courtesy appointment). Division of Electrical and Computer Engineering, Uni- versity of Michigan, 2008{2010. • Associate Professor. Department of Mathematics, University of Michigan, 2007{2010. • Assistant Professor. Department of Mathematics, University of Michigan, 2004{2007. • Principal technical staff member. Internet and Network Systems Research Center, AT&T Labs-Research, 2002{2004. • Senior technical staff member. Information Sciences Research Center, AT&T Labs-Research, 1998{ 2002. • Visiting instructor. Department of Mathematics, Stanford University, Winter quarter 2000. • Postdoctoral research associate. Yale University and AT&T Labs-Research, 1997{1998. • Intern. Lucent Technologies Bell Laboratories, summer 1996. • Research assistant. Princeton University, 1994{1995. • Intern. AT&T Bell Laboratories, summers 1993{1995. Publications Refereed Journal Publications • F. J. Chung, A. C. Gilbert, J. G. Hoskins, and J. C. Schotland, \Optical tomography on graphs", Inverse Problems, Volume 33, Number 5, 2017.