DOCSLIB.ORG

2011 Annual Report Alfred P

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
2011 Annual Report Alfred P Alfred P. Sloan Foundation 2011 Annual Report alfred p. sloan foundation $ 2011 annual report Contents Mission Statement 2 President’s Letter 3 2011 Grants by Program 13 2011 Financial Review 84 Audited Financial Statements and Schedules 86 Board of Trustees 113 Staff 114 Index of 2011 Grant Recipients 115 1 alfred p. sloan foundation $ 2011 annual report Mission Statement The ALFRED P. SLOAN FOUNDATION makes grants primar- ily to support original research and broad-based education related to science, technology, economic performance, and the quality of American life. The Foundation is unique in its focus on science, technology, and economic institutions—and the scholars and prac- titioners who work in these fields—as chief drivers of the nation’s health and prosperity. The Foundation has a deep-rooted belief that carefully reasoned systematic understanding of the forces of nature and society, when applied inventively and wisely, can lead to a bet- ter world for all. The Foundation’s endowment provides the finan- cial resources to support its activities. The investment strategy for the endowment is to invest prudently in a diversified portfolio of assets with the goal of achieving superior returns. In each of our grants programs, we seek proposals for original proj- ects led by outstanding individuals or teams. We are interested in projects that have a high expected return to society, and for which funding from the private sector, government, or other foundations is not yet widely available. 2 alfred p. sloan foundation $ 2011 annual report President’s Letter Dr. Paul L. Joskow am pleased to introduce the 2011 Annual Report of the Alfred P. Sloan Foundation. The report contains descriptions of our I grantmaking programs, a list of all grants made by the Founda- tion in 2011, a financial review and audited financial statements, and the names of the Foundation’s Trustees and staff. My letter pro- vides an overview of the Foundation’s grant activity in 2011—focus- ing on new programs or those gaining momentum, as well as those that were restructured or came to an end—and concludes with some general reflections on grantmaking strategies for a founda- tion of our size and mission.1 The Alfred P. Sloan Foundation’s mission is to make grants to support research and broad-based education in science, technology, economic performance, and the quality of American life. We also look for special opportunities to support projects that benefit the residents of the New York metropolitan area, where our staff and their families live, work, and attend school, and to fund select projects that reflect critical national needs. The funds available to the Foundation to support its grantmaking and manage- ment come from our endowment, which was created by gifts from Alfred P. Sloan Jr., and which is managed by the Foundation’s investment team with the support of our Investment Committee. Our investment team performed well under challenging market conditions and earned a 2.3% percent rate of return during calendar year 2011. As of December 31, 2011, the value of the Founda- tion’s endowment stood at approximately $1.6 billion. Basic Research One of the most rewarding aspects of the Sloan Foundation’s grantmaking is its support of new and emerging fields of scientific inquiry. New areas of science and technology research are often perceived to be too risky to attract fund- ing from major federal agencies like the National Science Foundation and the National Institutes of Health or have difficulty finding a funding “slot” between established programs which have budget lines reserved for them. The Founda- tion focuses its research grants in emerging areas and community-building infrastructure to support pioneering researchers as they attempt to develop 1 This letter is a collective effort that has relied on contributions of many members of the Sloan Foundation’s staff. I want to thank Nate Williams, Anne McKissick, Gail Pesyna, Jesse Ausubel, Kathleen Christensen, Danny Goroff, Liz Boylan, Josh Greenberg, Paula Olsiewski, Doron Weber, Sibo Lu, and Sonia Epstein for their contributions. 3 alfred p. sloan foundation $ 2011 annual report and test new theories, build new instruments, cre- accurately characterizing the attributes of the in- ate new data sets, and publish their research in top door microbial environment and how it is affected academic journals. In this way the Foundation has by building attributes, building use, the external played a vital role in the development of the now- environment, and other factors. Initial research thriving disciplines of computer science, compu- results make clear that indoor environments are as tational biology, theoretical neurobiology, and be- complex and interrelated as savannahs, swamps, havioral economics. In addition, Foundation grants and rainforests, supporting thriving invisible com- supporting infrastructure and community-building munities of bacteria, fungi, and other microbes have led to new templates, technologies, and stan- that live alongside humans in the buildings where dards for the collection, organization, and open we work, rest, and play. In 2011, the Foundation access of scientific research and data. The Sloan committed over $3 million in grants for research Digital Sky Survey, the Census of Marine Life, and and community-building to researchers studying the Encyclopedia of Life are good examples. the microbiology of built environments, including an exciting project by the University of Colorado The newest entrant in this longstanding Founda- to study microbial populations in municipal water tion tradition is the emerging field of indoor micro- systems, a grant to Yale University to study air- bial ecology. Americans spend about 90% of their borne bacterial communities, and funds to expand time indoors2, yet most research and policy has DNA barcoding libraries to identify the staggering focused on the outdoor environment. The Founda- array of fungi that can be found inside buildings. tion’s program supporting research on the indoor microbial environment, led by Program Director Initiated with Sloan funds in 2009 and led by Vice Paula Olsiewski, is supporting research focused on President Jesse Ausubel, the Deep Carbon Ob- servatory (DCO)—an exciting multidisciplinary, 2 The Inside Story: A Guide to Indoor Air Quality. U.S. EPA/ decade-long, international scientific research pro- Office of Air and Radiation. Office of Radiation and Indoor Air (6609J) Cosponsored with the Consumer Product Safety gram headquartered at the Carnegie Institution of Commission, EPA 402-K-93-007. http://www.cpsc.gov/cpsc- Washington—is devoted to revolutionizing our un- pub/pubs/450.html derstanding of the abundance, distribution, move- 4 alfred p. sloan foundation $ 2011 annual report ment, and properties of carbon under the earth’s try, computational and evolutionary molecular bi- surface. With $13 million in Foundation support ology, computer science, economics, mathematics, thus far, DCO’s structure is now complete with the neuroscience, and physics. In 2011 the first nomi- launch of four scientific directorates—Reservoirs nations in the field of ocean sciences were solicited, and Fluxes, Deep Energy, Deep Life, and Physics with the first awards made in early 2012. and Chemistry of Extreme Environments. STEM Higher Education In most of our basic research programs and most 2011 was a year of transition for the Foundation’s of our educational initiatives, we expect that our programs that focus on higher education in science, grants will help catalyze new areas of inquiry, and technology, engineering, and mathematics (STEM). that these funds will be leveraged with funding In February, I invited Dr. Elizabeth S. Boylan to from other government, foundation, and private join the Foundation as our new program director sources as the value of the research program be- overseeing the Foundation’s education-related comes more widely recognized. For programs like grantmaking. As the former provost of Barnard the Sloan Digital Sky Survey, neurobiology, com- College, Dr. Boylan—a biologist by training—has putational biology, the Census of Marine Life, the organized, supported, and advanced student and Encyclopedia of Life, etc., Sloan funds represented faculty diversity for 16 years. Under her leadership, a small fraction of the funding as these programs the Foundation is conducting an inventory of its reached maturity. Once the programs reached STEM Higher Education grantmaking programs maturity or achieved their goals, the Foundation and reviewing how well the programs’ strategy gradually withdrew its financial support. and structure advance the Foundation’s goals of increasing the quality and diversity of American Responsible scientific research practices must higher education in STEM fields. Plans for the fu- incorporate an understanding of both the potential ture include an expansion of the Foundation’s goals benefits and the potential adverse effects of this to include promoting diversity all along the aca- research on society. Acceptable research practices demic career path while focusing on high-quality, should apply protocols that minimize the potential hypothesis-driven research on the factors driving risks in ways that are not excessively burdensome student outcomes and retention in STEM fields at on scientific inquiry. The Foundation’s program the undergraduate and graduate levels. in Synthetic Biology, also led by Dr. Olsiewski, partners with scientists, ethicists, and policymak- Public Understanding of Science,
Load more

Recommended publications
  • HONGLAK LEE 2260 Hayward St, Beyster Building Room 3773, Ann Arbor, MI 48109 [email protected]
    HONGLAK LEE 2260 Hayward St, Beyster Building Room 3773, Ann Arbor, MI 48109 http://www.eecs.umich.edu/~honglak [email protected] EDUCATION 9/2010 Stanford University, Stanford, CA Ph.D. in Computer Science Thesis title: Unsupervised Feature Learning via Sparse Hierarchical Representations Thesis advisor: Professor Andrew Y. Ng 6/2006 Stanford University, Stanford, CA M.S. in Computer Science M.S. in Applied Physics 2/2003 Seoul National University, Seoul, Korea B.S. in Physics and Computer Science, GPA 4.14/4.30, Summa Cum Laude PROFESSIONAL EXPERIENCE 9/2010 – Present Assistant Professor, CSE division, EECS department, University of Michigan, Ann Arbor, MI 1/2005 – 8/2010 Research Assistant, Stanford AI Lab, Stanford University, Stanford, CA 8/1999 –1/2002 Software Engineer, ECO Co. Ltd., Seoul, Korea AWARDS & HONORS National Science Foundation CAREER Award, 2015 AI’s 10 to Watch, IEEE Intelligent Systems, 2013 Google Faculty Research Award, 2011 Research Highlights in Communications of the ACM, 2011 Best Paper Award: Best Application Paper, International Conference on Machine Learning (ICML), 2009 Best Student Paper Award, Conference on Email and Anti-Spam (CEAS), 2005 Stanford Graduate Fellowship, Stanford University, 2003–2006 Graduate Fellowship from Korea Foundation for Advanced Studies (KFAS), 2003–2008 College Student Scholarship from Korea Foundation for Advanced Studies (KFAS), 1997–2001 Honorable Mention in the 16th University Students Contest of Mathematics, 1997 Undergraduate Scholarship from Korea Science and Engineering Foundation (KOSEF), 1996–1999 The First Place in the Entrance Exam of College of Natural Sciences, Seoul National University, 1996 The 12th place out of 344,780 applicants in the College Scholastic Ability Test (CSAT), Korea, 1996 Silver Medal in the 26th International Physics Olympiad, Canberra, Australia, 1995 REFEREED CONFERENCE AND JOURNAL PUBLICATIONS 1.
    [Show full text]
  • Make3d: Learning 3D Scene Structure from a Single Still Image Ashutosh Saxena, Min Sun and Andrew Y
    1 Make3D: Learning 3D Scene Structure from a Single Still Image Ashutosh Saxena, Min Sun and Andrew Y. Ng Abstract— We consider the problem of estimating detailed 3-d structure from a single still image of an unstructured environment. Our goal is to create 3-d models which are both quantitatively accurate as well as visually pleasing. For each small homogeneous patch in the image, we use a Markov Random Field (MRF) to infer a set of “plane parame- ters” that capture both the 3-d location and 3-d orientation of the patch. The MRF, trained via supervised learning, models both image depth cues as well as the relationships between different parts of the image. Other than assuming that the environment is made up of a number of small planes, our model makes no explicit assumptions about the structure of the scene; this enables the algorithm to capture much more detailed 3-d structure than does prior art, and also give a much richer experience in the 3-d flythroughs created using image-based rendering, even for scenes with significant non-vertical structure. Using this approach, we have created qualitatively correct 3-d models for 64.9% of 588 images downloaded from the internet. We have also extended our model to produce large scale 3d models from a few images.1 Fig. 1. (a) An original image. (b) Oversegmentation of the image to obtain Index Terms— Machine learning, Monocular vision, Learning “superpixels”. (c) The 3-d model predicted by the algorithm. (d) A screenshot depth, Vision and Scene Understanding, Scene Analysis: Depth of the textured 3-d model.
    [Show full text]
  • Probabilistic Models on Fibre Bundles by Shan Shan
    Probabilistic Models on Fibre Bundles by Shan Shan Department of Mathematics Duke University Date: Approved: Ingrid Daubechies, Supervisor Sayan Mukherjee, Chair Doug Boyer Colleen Robles Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Mathematics in the Graduate School of Duke University 2019 ABSTRACT Probabilistic Models on Fibre Bundles by Shan Shan Department of Mathematics Duke University Date: Approved: Ingrid Daubechies, Supervisor Sayan Mukherjee, Chair Doug Boyer Colleen Robles An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Mathematics in the Graduate School of Duke University 2019 Copyright c 2019 by Shan Shan All rights reserved Abstract In this thesis, we propose probabilistic models on fibre bundles for learning the gen- erative process of data. The main tool we use is the diffusion kernel and we use it in two ways. First, we build from the diffusion kernel on a fibre bundle a projected kernel that generates robust representations of the data, and we test that it outperforms regular diffusion maps under noise. Second, this diffusion kernel gives rise to a nat- ural covariance function when defining Gaussian processes (GP) on the fibre bundle. To demonstrate the uses of GP on a fibre bundle, we apply it to simulated data on a M¨obiusstrip for the problem of prediction and regression. Parameter tuning can also be guided by a novel semi-group test arising from the geometric properties of dif- fusion kernel. For an example of real-world application, we use probabilistic models on fibre bundles to study evolutionary process on anatomical surfaces.
    [Show full text]
  • 2. Superoscillations.Pdf
    When the Whole Vibrates Faster than Any of its Parts Computational Superoscillation Theory Nicholas Wheeler December 2017 Introduction. The phenomenon/theory of “superoscillations”—brought to my attention by my friend Ahmed Sebbar1—originated in the time-symmetric formulation of quantum mechanics2 that gave rise to the theory of “weak measurements.” Recognition of the role that superoscillations play in that work was brought into explicit focus by Aharonov et al in 1990, and since that date the concept has found application to a remarkable variety of physical subject areas. Yakir Aharonov took his PhD in 1960 from the University of Bristol, where he worked with David Bohm.3 In 1992 a conference was convened at Bristol to celebrate Aharonov’s 60th birthday. It was on that occasion that the superoscillation phenomenon came first to the attention of Michael Berry (of the Bristol faculty), who in an essay “Faster than Fourier” contributed to the proceedings of that conference4 wrote that “He [Aharonov] told me that it is possible for functions to oscillate faster than any of their Fourier components. This seemed unbelievable, even paradoxical; I had heard nothing like it before. ” Berry was inspired to write a series of papers relating to the theory of superoscillation and its potential applications, as also by now have a great many other authors. 1 Private communication, 17 November 2017. 2 Y. Aharonov, P. G. Bergmann & J. L. Libowitz, “Time symmetry in the quantum meassurement process,” Phys. Rev. B 134, 1410–1416 (1964). 3 It was, I suspect, at the invitation of E. P Gross—who had collaborated with Bohm when both were at Princeton—that Aharonov spent 1960–1961 at Brandeis University, from which I had taken the first PhD and departed to Utrecht/CERN in February of 1960, so we never met.
    [Show full text]
  • EMS Newsletter September 2012 1 EMS Agenda EMS Executive Committee EMS Agenda
    NEWSLETTER OF THE EUROPEAN MATHEMATICAL SOCIETY Editorial Obituary Feature Interview 6ecm Marco Brunella Alan Turing’s Centenary Endre Szemerédi p. 4 p. 29 p. 32 p. 39 September 2012 Issue 85 ISSN 1027-488X S E European M M Mathematical E S Society Applied Mathematics Journals from Cambridge journals.cambridge.org/pem journals.cambridge.org/ejm journals.cambridge.org/psp journals.cambridge.org/flm journals.cambridge.org/anz journals.cambridge.org/pes journals.cambridge.org/prm journals.cambridge.org/anu journals.cambridge.org/mtk Receive a free trial to the latest issue of each of our mathematics journals at journals.cambridge.org/maths Cambridge Press Applied Maths Advert_AW.indd 1 30/07/2012 12:11 Contents Editorial Team Editors-in-Chief Jorge Buescu (2009–2012) European (Book Reviews) Vicente Muñoz (2005–2012) Dep. Matemática, Faculdade Facultad de Matematicas de Ciências, Edifício C6, Universidad Complutense Piso 2 Campo Grande Mathematical de Madrid 1749-006 Lisboa, Portugal e-mail: [email protected] Plaza de Ciencias 3, 28040 Madrid, Spain Eva-Maria Feichtner e-mail: [email protected] (2012–2015) Society Department of Mathematics Lucia Di Vizio (2012–2016) Université de Versailles- University of Bremen St Quentin 28359 Bremen, Germany e-mail: [email protected] Laboratoire de Mathématiques Newsletter No. 85, September 2012 45 avenue des États-Unis Eva Miranda (2010–2013) 78035 Versailles cedex, France Departament de Matemàtica e-mail: [email protected] Aplicada I EMS Agenda .......................................................................................................................................................... 2 EPSEB, Edifici P Editorial – S. Jackowski ........................................................................................................................... 3 Associate Editors Universitat Politècnica de Catalunya Opening Ceremony of the 6ECM – M.
    [Show full text]
  • April 2017 Table of Contents
    ISSN 0002-9920 (print) ISSN 1088-9477 (online) of the American Mathematical Society April 2017 Volume 64, Number 4 AMS Prize Announcements page 311 Spring Sectional Sampler page 333 AWM Research Symposium 2017 Lecture Sampler page 341 Mathematics and Statistics Awareness Month page 362 About the Cover: How Minimal Surfaces Converge to a Foliation (see page 307) MATHEMATICAL CONGRESS OF THE AMERICAS MCA 2017 JULY 2428, 2017 | MONTREAL CANADA MCA2017 will take place in the beautiful city of Montreal on July 24–28, 2017. The many exciting activities planned include 25 invited lectures by very distinguished mathematicians from across the Americas, 72 special sessions covering a broad spectrum of mathematics, public lectures by Étienne Ghys and Erik Demaine, a concert by the Cecilia String Quartet, presentation of the MCA Prizes and much more. SPONSORS AND PARTNERS INCLUDE Canadian Mathematical Society American Mathematical Society Pacifi c Institute for the Mathematical Sciences Society for Industrial and Applied Mathematics The Fields Institute for Research in Mathematical Sciences National Science Foundation Centre de Recherches Mathématiques Conacyt, Mexico Atlantic Association for Research in Mathematical Sciences Instituto de Matemática Pura e Aplicada Tourisme Montréal Sociedade Brasileira de Matemática FRQNT Quebec Unión Matemática Argentina Centro de Modelamiento Matemático For detailed information please see the web site at www.mca2017.org. AMERICAN MATHEMATICAL SOCIETY PUSHING LIMITS From West Point to Berkeley & Beyond PUSHING LIMITS FROM WEST POINT TO BERKELEY & BEYOND Ted Hill, Georgia Tech, Atlanta, GA, and Cal Poly, San Luis Obispo, CA Recounting the unique odyssey of a noted mathematician who overcame military hurdles at West Point, Army Ranger School, and the Vietnam War, this is the tale of an academic career as noteworthy for its o beat adventures as for its teaching and research accomplishments.
    [Show full text]
  • AAAI-12 Conference Committees
    AAAI 2012 Conference Committees Chairs and Cochairs AAAI Conference Committee Chair Dieter Fox (University of Washington, USA) AAAI­12 Program Cochairs Jörg Hoffmann (Saarland University, Germany) Bart Selman (Cornell University, USA) IAAI­12 Conference Chair and Cochair Markus Fromherz (ACS, a Xerox Company, USA) Hector Munoz‐Avila (Lehigh University, USA) EAAI­12 Symposium Chair David Kauchak (Middlebury College, USA) Special Track on Artificial Intelligence and the Web Cochairs Denny Vrandecic (Institute of Applied Informatics and Formal Description Methods, Germany) Chris Welty (IBM Research, USA) Special Track on Cognitive Systems Cochairs Matthias Scheutz (Tufts University, USA) James Allen (University of Rochester, USA) Special Track on Computational Sustainability and Artificial Intelligence Cochairs Carla P. Gomes (Cornell University, USA) Brian C. Williams (Massachusetts Institute of Technology, USA) Special Track on Robotics Cochairs Kurt Konolige (Industrial Perception, Inc., USA) Siddhartha Srinivasa (Carnegie Mellon University, USA) Turing Centenary Events Chair Toby Walsh (NICTA and University of New South Wales, Australia) Tutorial Program Cochairs Carmel Domshlak (Technion Israel Institute of Technology, Israel) Patrick Pantel (Microsoft Research, USA) Workshop Program Cochairs Michael Beetz (University of Munich, Germany) Holger Hoos (University of British Columbia, Canada) Doctoral Consortium Cochairs Elizabeth Sklar (Brooklyn College, City University of New York, USA) Peter McBurney (King’s College London, United Kingdom)
    [Show full text]
  • Ingrid Daubechies Receives NAS Award in Mathematics
    Ingrid Daubechies Receives NAS Award in Mathematics INGRID DAUBECHIES has received the 2000 National well as the 1997 Ruth Lyttle Academy of Sciences (NAS) Award in Mathematics. Satter Prize. From 1992 to The $5,000 award, established by the AMS in com- 1997 she was a fellow of the memoration of its centennial in 1988, is presented John D. and Catherine T. every four years for excellence in published math- MacArthur Foundation. ematical research. Daubechies was chosen “for fun- The previous recipients damental discoveries on wavelets and wavelet ex- of the NAS Award in Math- pansions and for her role in making wavelet methods ematics are Robert P. Lang- a practical basic tool of applied mathematics.” lands (1988), Robert D. Ingrid Daubechies received both her bachelor’s MacPherson (1992), and An- and Ph.D. degrees (in 1975 and 1980) from the drew J. Wiles (1996). Free University in Brussels, Belgium. She held a re- —Allyn Jackson search position at the Free University until 1987. From 1987 to 1994 she was a member of the tech- nical staff at AT&T Bell Laboratories, during which time she took leaves to spend six months (in 1990) at the University of Michigan and two years (1991–93) at Rutgers University. She is now a pro- fessor in the Mathematics Department and in the Program in Applied and Computational Mathematics at Princeton University. Her research Ingrid Daubechies interests focus on the mathematical aspects of time-frequency analysis, in particular wavelets, as well as applications. In 1993 Daubechies was elected as a member of the American Academy of Arts and Sciences, and in 1998 she was elected as a member of the NAS and as a fellow of the Institute of Electrical and Electronics Engineers.
    [Show full text]
  • Ashesh Jain 142 Gates Building, Stanford University, CA 94305 [email protected]
    Ashesh Jain 142 Gates Building, Stanford University, CA 94305 [email protected], www.cs.cornell.edu/~ashesh Interests My research interest lies at the intersection of machine learning, robotics and computer vision. Broadly, I build machine learning systems & algorithms for agents { such as robots, cars etc. { to learn from informative human signals at a large-scale. Most of my work has been in multi-modal sensor-rich robotic settings, for which I have developed sensory fusion deep learning architectures. I have developed and deployed algorithms on multiple robotic platforms (PR2, Baxter etc.), on cars, and crowd-sourcing systems. Education Cornell University, New York, USA (2012-2016 (Exptd)) Ph.D. student, Computer Science • PhD committee: Ashutosh Saxena (advisor), Thorsten Joachims, Doug James, Robert Kleinberg, and Bart Selman. • Learning from large-scale human signals for robots and assistive cars • First author papers in NIPS, ICCV, SIGKDD, ICRA, ISRR, and IJRR Indian Institute of Technology Delhi, India (2007-2012) B.Tech. Electrical Engineering & M.Tech. Information and Communication Technology • Advisor: Prof. Manik Varma and Prof. S.V.N. Vishwanathan • Thesis: Large-scale Algorithms for Multiple Kernel Learning Experience Stanford University, California, USA (2014-Present) Visiting Ph.D. student, Computer Science • Working with Prof. Ashutosh Saxena and Prof. Silvio Savarese • Leading Brain4Cars and Machine Learning lead on RoboBrain. Purdue University, Indiana, USA (Summer 2011) Research Intern, Statistics Department with Prof. S. V. N. Vishwanathan • Developed Multiple Kernel Learning algorithms to scale to Millions of kernels The Royal Bank of Scotland, India (Summer 2010) • Developed software to automate testing of web application GUI Software NeuralModels: A deep learning framework for quick prototyping of structures of Recurrent Neural Networks, Sensory-fusion architectures, and deep learning on graph structured data.
    [Show full text]
  • Unsupervised Structured Learning of Human Activities for Robot Perception
    UNSUPERVISED STRUCTURED LEARNING OF HUMAN ACTIVITIES FOR ROBOT PERCEPTION A Dissertation Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Chenxia Wu August 2016 © 2016 Chenxia Wu ALL RIGHTS RESERVED UNSUPERVISED STRUCTURED LEARNING OF HUMAN ACTIVITIES FOR ROBOT PERCEPTION Chenxia Wu, Ph.D. Cornell University 2016 Learning human activities and environments is important for robot perception. Human activities and environments comprise many aspects, including a wide variety of human actions and various objects that interact with humans, which make their modeling very challenging. We observe that these aspects are re- lated to each other spatially, temporally and semantically. They form sequen- tial, hierarchical or graph structures. Understanding these structures is key to the learning algorithms and systems of robot perception. Therefore, this thesis focuses on structured modeling of these complex hu- man activities and environments using unsupervised learning. Our unsupervised learning approaches can detect hidden structures from the data itself, without the need for human annotations. In this way, we enable more useful applica- tions, such as forgotten action detection and object co-segmentation. While structured models in supervised settings have been well-studied and widely used in various domains, discovering latent structures is still a chal- lenging problem in unsupervised learning. In this work, we propose unsuper- vised structured learning models, including causal topic models and fully con- nected Conditional Random Field (CRF) auto-encoders, which have the ability to model more complex relations with less independence. We also design effi- cient learning and inference optimizations that maintain the tractability of com- putations.
    [Show full text]
  • Ashesh Jain 142 Gates Building, Stanford University, CA 94305 [email protected]
    Ashesh Jain 142 Gates Building, Stanford University, CA 94305 [email protected], www.cs.cornell.edu/~ashesh Interests My research interest lies at the intersection of machine learning, robotics, and computer vision. Broadly, I build machine learning systems & algorithms for agents { such as robots, cars etc. { to learn from informative human signals at a large-scale. Most of my work has been in multi-modal sensor-rich robotic settings, for which I have developed sensory fusion deep learning architectures. I have developed and deployed algorithms on multiple robotic platforms (PR2, Baxter etc.), on cars, and crowd-sourcing systems. Education Cornell University, New York, USA (2012-2016) Ph.D. Computer Science • Specializing in Machine Learning, Robotics, and Computer Vision • Learning from large-scale human signals for robots and assistive cars • First author papers in NIPS, CVPR, ICCV, SIGKDD, ICRA, ISRR, and IJRR • PhD committee: Ashutosh Saxena, Bart Selman, Thorsten Joachims, Doug James, Robert Kleinberg. Indian Institute of Technology Delhi, India (2007-2012) B.Tech. Electrical Engineering & M.Tech. Information and Communication Technology • Advisor: Prof. Manik Varma and Prof. S.V.N. Vishwanathan • Thesis: Large-scale Algorithms for Multiple Kernel Learning Experience Stanford University, California, USA (2014-2016) Visiting Ph.D. Computer Science • Working with Prof. Ashutosh Saxena and Prof. Silvio Savarese • Leading Brain4Cars and Machine Learning lead on RoboBrain. Purdue University, Indiana, USA (Summer 2011) Research Intern, Statistics Department with Prof. S. V. N. Vishwanathan • Developed Multiple Kernel Learning algorithms to scale to Millions of kernels The Royal Bank of Scotland, India (Summer 2010) Software NeuralModels: A deep learning framework for quick prototyping of structures of Recurrent Neural Networks, Sensory-fusion architectures, and deep learning on graph structured data.
    [Show full text]
  • Meetings of the MAA Ken Ross and Jim Tattersall
    Meetings of the MAA Ken Ross and Jim Tattersall MEETINGS 1915-1928 “A Call for a Meeting to Organize a New National Mathematical Association” was DisseminateD to subscribers of the American Mathematical Monthly and other interesteD parties. A subsequent petition to the BoarD of EDitors of the Monthly containeD the names of 446 proponents of forming the association. The first meeting of the Association consisteD of organizational Discussions helD on December 30 and December 31, 1915, on the Ohio State University campus. 104 future members attendeD. A three-hour meeting of the “committee of the whole” on December 30 consiDereD tentative Drafts of the MAA constitution which was aDopteD the morning of December 31, with Details left to a committee. The constitution was publisheD in the January 1916 issue of The American Mathematical Monthly, official journal of The Mathematical Association of America. Following the business meeting, L. C. Karpinski gave an hour aDDress on “The Story of Algebra.” The Charter membership included 52 institutions and 1045 inDiviDuals, incluDing six members from China, two from EnglanD, anD one each from InDia, Italy, South Africa, anD Turkey. Except for the very first summer meeting in September 1916, at the Massachusetts Institute of Technology (M.I.T.) in CambriDge, Massachusetts, all national summer anD winter meetings discussed in this article were helD jointly with the AMS anD many were joint with the AAAS (American Association for the Advancement of Science) as well. That year the school haD been relocateD from the Back Bay area of Boston to a mile-long strip along the CambriDge siDe of the Charles River.
    [Show full text]