DOCSLIB.ORG

2017-2018 Annual Report

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
2017-2018 Annual Report Institute for Computational and Experimental Research in Mathematics Annual Report May 1, 2017 – April 30, 2018 Brendan Hassett, Director Mathew Borton, IT Director Jeff Brock, Associate Director Ruth Crane, Assistant Director Sigal Gottlieb, Deputy Director Elisenda Grigsby, Deputy Director Jeffrey Hoffstein, Consulting Associate Director Caroline Klivans, Associate Director Jill Pipher, Consulting Associate Director Bjorn Sandstede, Associate Director Homer Walker, Consulting Associate Director Ulrica Wilson, Associate Director for Diversity and Outreach Table of Contents Mission ....................................................................................................................................... 6 Core Programs and Events ......................................................................................................... 6 Participant Summaries by Program Type ................................................................................... 9 ICERM Funded Participants ................................................................................................................. 9 All Participants (ICERM funded and Non-ICERM funded) .................................................................. 10 ICERM Funded Speakers ................................................................................................................... 11 All Speakers (ICERM funded and Non-ICERM funded) ...................................................................... 12 ICERM Funded Postdocs ................................................................................................................... 13 All Postdocs (ICERM funded and Non-ICERM funded) ...................................................................... 14 ICERM Funded Graduate Students .................................................................................................... 15 All Graduate Students (ICERM funded and Non-ICERM funded) ....................................................... 16 Additional Participant Data .............................................................................................................. 17 Semester Program Length of Stay ................................................................................................................17 Primary Field of Interest...............................................................................................................................17 Position .......................................................................................................................................................18 Gender ........................................................................................................................................................18 US vs Foreign Based Participants ..................................................................................................................19 Semester Programs .................................................................................................................. 19 Semester Program Process ............................................................................................................... 19 1. Solicitation of Proposals ...........................................................................................................................20 2. Proposal Selection ....................................................................................................................................21 3. Selection of Long-term Visitors/Research Fellows .....................................................................................21 4. Offers to Research Fellows .......................................................................................................................21 5. Semester Workshops ...............................................................................................................................21 6. Application Process ..................................................................................................................................22 7. Applicant Selection ..................................................................................................................................22 Financial Decisions for Semester Programs ...................................................................................... 22 Opening, “Middle” and Closing Events ............................................................................................. 22 2017-2018 Semester Programs ................................................................................................. 24 Fall 2017 Semester Program: Mathematical and Computational Challenges in Radar and Seismic Reconstruction.................................................................................................................................. 24 Research Cluster 1: Wave Propagation and Imaging in Random Media .........................................................27 Workshop 1: Industrial Problems in Radar and Seismic Reconstruction.........................................................29 Workshop 2: Waves and Imaging in Random Media .....................................................................................32 Research Cluster 2: Mathematical and Computational Aspects of Radar Imaging ..........................................35 Workshop 3: Mathematical and Computational Aspects of Radar Imaging ....................................................37 Research Cluster 3: Wave Propagation and Inversion in Seismic Applications ...............................................40 ICERM: 2017-2018 NSF Annual Report 2 Workshop 4: Advances in model reduction for large-scale forward and inverse scattering problems ............42 Workshop 5: Recent Advances in Seismic Modeling and Inversion: From Analysis to Applications .................43 Spring 2018 Semester Program: Point Configurations in Geometry, Physics and Computer Science 46 Workshop 1: Optimal and Random Point Configurations ..............................................................................49 Workshop 2: Fast Algorithms for Generating Static and Dynamically Changing Point Configurations .............54 Workshop 3: Computation and Optimization of Energy, Packing, and Covering.............................................57 Workshop 4: Computational Challenges in the Theory of Lattices .................................................................61 Topical Workshops ................................................................................................................... 64 1. Solicitation of Topical Workshop Proposals...............................................................................................65 2. Proposal Selection ....................................................................................................................................65 3. Recommendation of Speakers ..................................................................................................................65 4. Invitations to Speakers .............................................................................................................................65 5. Application Process ..................................................................................................................................65 6. Applicant Selection ..................................................................................................................................66 Financial Decisions for Topical Workshops ....................................................................................... 66 Topical Workshops in 2017-2018 .............................................................................................. 66 Topical Workshop 1: Probabilistic Scientific Computing: Statistical Inference Approaches to Numerical Analysis and Algorithm Design ........................................................................................ 66 Topical Workshop 2: Robust Methods in Probability and Finance: ................................................... 70 Topical Workshop 3: Women in Data Science and Mathematics Research Collaboration Workshop (WiSDM): .......................................................................................................................................... 72 Topical Workshop 4: LocaliZed Kernel-Based Meshless Methods for Partial Differential Equations . 80 Topical Workshop 5: Pedestrian Dynamics: Modeling, Validation and Calibration ........................... 83 Collaborate@ICERM (C@I) ....................................................................................................... 86 Collaborate@ICERM Process ............................................................................................................ 87 1. Solicitation of Proposals ...........................................................................................................................87 2. Future Proposal Selection.........................................................................................................................87 Hot Topics Workshops: ............................................................................................................. 88 Program Promotions ................................................................................................................ 89 Communications Plan ......................................................................................................................
Load more

Recommended publications
  • Curriculum Vitae
    Curriculum Vitae Larry Guth Education B.S. Mathematics, Yale University, 2000 PhD Mathematics, MIT, 2005 Employment Samelson Fellow, Stanford University 2005-6 Szego Assistant Professor, Stanford University, 2006 - 2008 National Science Foundation Postdoctoral Fellow, 2006 - 2008 Tenure-stream Assistant Professor, University of Toronto, 2008 - 2011 Member, Institute for Advanced Study, 2010 - 2011 Professor, New York University, 2011 - 2012 Professor, MIT, 2012 - Fellowships National Science Foundation Graduate Fellowship, 2001 - 2003 National Science Foundation Postdoctoral Fellowship , 2006 - 2008 Alfred P. Sloan Research Fellowship, 2010 - 2014 Simons Investigator, 2014 - Honors Salem prize 2013 Invited talks Invited sectional speaker at the 2010 International Congress of Mathematics Marston Morse lectures, IAS, 2013 Namboodiri lectures, University of Chicago, 2015 1 Selected publications 1. Lipshitz maps from surfaces, Geom. Funct. Anal. 15 (2005), no. 5, 1052-109 2. The width-volume inequality, Geom. Funct. Anal. 17 (2007) no. 4, 1139-1179 3. Notes on Gromov's systolic estimate, Geom. Dedicata 123 (2006) 113-129 4. Symplectic embeddings of polydisks, Invent. Math. 172 (2008) no. 3, 477-489 5. Minimax problems related to cup powers and Steenrod squares, Geom. Funct. Anal. 18 (2009), no. 6, 1917{1987 6. The endpoint case of the Bennett-Carbery-Tao multilinear Kakeya conjecture, Acta Math. 205 (2010), no. 2, 263-286. 7. Systolic inequalities and minimal hypersurfaces, Geom. Funct. Anal. 19 (2010), no. 6, 1688-1692. 8. Volumes of balls in large Riemannian manifolds, Ann. of Math. (2) 173 (2011), no. 1, 5176. 9. Area-expanding embeddings of rectangles, preprint 10. Algebraic methods in discrete analogs of the Kakeya problem (joint with Nets Katz), Adv.
    [Show full text]
  • Eigenvalue Distributions of Beta-Wishart Matrices
    Eigenvalue distributions of beta-Wishart matrices The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Edelman, Alan, and Plamen Koev. “Eigenvalue Distributions of Beta- Wishart Matrices.” Random Matrices: Theory and Applications 03, no. 02 (April 2014): 1450009. As Published http://dx.doi.org/10.1142/S2010326314500099 Publisher World Scientific Pub Co Pte Lt Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/116006 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike Detailed Terms http://creativecommons.org/licenses/by-nc-sa/4.0/ SIAM J. MATRIX ANAL. APPL. c 2013 Society for Industrial and Applied Mathematics Vol. XX, No. X, pp. XX{XX EIGENVALUE DISTRIBUTIONS OF BETA-WISHART MATRICES∗ ALAN EDELMANy AND PLAMEN KOEVz Abstract. We derive explicit expressions for the distributions of the extreme eigenvalues of the Beta-Wishart random matrices in terms of the hypergeometric function of a matrix argument. These results generalize the classical results for the real (β = 1), complex (β = 2), and quaternion (β = 4) Wishart matrices to any β > 0. Key words. random matrix, Wishart distribution, eigenavalue, hypergeometric function of a matrix argument AMS subject classifications. 15A52, 60E05, 62H10, 65F15 DOI. XX.XXXX/SXXXXXXXXXXXXXXXX 1. Introduction. Recently, the classical real (β = 1), complex (β = 2), and quaternion (β = 4) Wishart random matrix ensembles were generalized to any β > 0 by what is now called the Beta{Wishart ensemble [2, 9]. In this paper we derive the explicit distributions for the extreme eigenvalues and the trace of this ensemble as series of Jack functions and, in particular, in terms of the hypergeometric function of matrix argument.
    [Show full text]
  • Matrix Algorithms: Fast, Stable, Communication-Optimizing—Random?!
    Matrix algorithms: fast, stable, communication-optimizing—random?! Ioana Dumitriu Department of Mathematics University of Washington (Seattle) Joint work with Grey Ballard, James Demmel, Olga Holtz, Robert Kleinberg IPAM: Convex Optimization and Algebraic Geometry September 28, 2010 Ioana Dumitriu (UW) Matrix algorithms September 28, 2010 1 / 49 1 Motivation and Background Main Concerns in Numerical Linear Algebra Size issues 2 Reducing the flops Stability of FMM Stability of FLA Why Randomize? 3 Reducing communication Why is communication bad? Randomized Spectral Divide and Conquer Communication Costs 4 Conclusions Ioana Dumitriu (UW) Matrix algorithms September 28, 2010 2 / 49 Motivation and Background Main Concerns in Numerical Linear Algebra The big four issues in matrix algorithms. Accuracy of computation (how “far” the computed values are from the actual ones, in the presence of rounding error). Stability (how much the computed result will change if we perturb the problem a little bit). Speed/complexity (how many operations they require, e.g., multiplications). Parallelism (how to distribute the computation to multiple processors in order to optimize speed – if possible). Communication complexity (how to minimize the amount of back-and-forth between levels of memory or processors.) Ioana Dumitriu (UW) Matrix algorithms September 28, 2010 3 / 49 Motivation and Background Main Concerns in Numerical Linear Algebra The big four issues in matrix algorithms. Accuracy of computation (how “far” the computed values are from the actual ones, in the presence of rounding error). Stability (how much the computed result will change if we perturb the problem a little bit). Speed/flops complexity (how many operations they require, e.g., multiplications).
    [Show full text]
  • The Random Matrix Technique of Ghosts and Shadows
    The Random Matrix Technique of Ghosts and Shadows Alan Edelman November 22, 2009 Abstract We propose to abandon the notion that a random matrix has to be sampled for it to exist. Much of today's applied nite random matrix theory concerns real or complex random matrices (β = 1; 2). The threefold way so named by Dyson in 1962 [2] adds quaternions (β = 4). While it is true there are only three real division algebras (β=dimension over the reals), this mathematical fact while critical in some ways, in other ways is irrelevant and perhaps has been over interpreted over the decades. We introduce the notion of a ghost random matrix quantity that exists for every beta, and a shadow quantity which may be real or complex which allows for computation. Any number of computations have successfully given reasonable answers to date though diculties remain in some cases. Though it may seem absurd to have a three and a quarter dimensional or pi dimensional algebra, that is exactly what we propose and what we compute with. In the end β becomes a noisiness parameter rather than a dimension. 1 Introduction This conference article contains an idea which has become a technique. Perhaps it might be labeled a conjecture, but I think idea is the better label right now. The idea was discussed informally to a number of researchers and students at MIT for a number of years now, probably dating back to 2003 or so. It was also presented at a number of conferences [3] . As slides do not quite capture a talk, this seemed a good place to write down the ideas.
    [Show full text]
  • Mathematics of Data Science
    SIAM JOURNAL ON Mathematics of Data Science Volume 2 • 2020 Editor-in-Chief Tamara G. Kolda, Sandia National Laboratories Section Editors Mark Girolami, University of Cambridge, UK Alfred Hero, University of Michigan, USA Robert D. Nowak, University of Wisconsin, Madison, USA Joel A. Tropp, California Institute of Technology, USA Associate Editors Maria-Florina Balcan, Carnegie Mellon University, USA Vianney Perchet, ENSAE, CRITEO, France Rina Foygel Barber, University of Chicago, USA Jonas Peters, University of Copenhagen, Denmark Mikhail Belkin, University of California, San Diego, USA Natesh Pillai, Harvard University, USA Robert Calderbank, Duke University, USA Ali Pinar, Sandia National Laboratories, USA Coralia Cartis, University of Oxford, UK Mason Porter, University of Califrornia, Los Angeles, USA Venkat Chandrasekaran, California Institute of Technology, Maxim Raginsky, University of Illinois, USA Urbana-Champaign, USA Patrick L. Combettes, North Carolina State University, USA Bala Rajaratnam, University of California, Davis, USA Alexandre d’Aspremont, CRNS, Ecole Normale Superieure, Philippe Rigollet, MIT, USA France Justin Romberg, Georgia Tech, USA Ioana Dumitriu, University of California, San Diego, USA C. Seshadhri, University of California, Santa Cruz, USA Maryam Fazel, University of Washington, USA Amit Singer, Princeton University, USA David F. Gleich, Purdue University, USA Marc Teboulle, Tel Aviv University, Israel Wouter Koolen, CWI, the Netherlands Caroline Uhler, MIT, USA Gitta Kutyniok, University of Munich, Germany
    [Show full text]
  • Polynomial Methods in Combinatorics
    UNIVERSITY LECTURE SERIES VOLUME 64 Polynomial Methods in Combinatorics Larry Guth American Mathematical Society https://doi.org/10.1090//ulect/064 Polynomial Methods in Combinatorics UNIVERSITY LECTURE SERIES VOLUME 64 Polynomial Methods in Combinatorics Larry Guth American Mathematical Society Providence, Rhode Island EDITORIAL COMMITTEE Jordan S. Ellenberg Robert Guralnick William P. Minicozzi II (Chair) Tatiana Toro 2010 Mathematics Subject Classification. Primary 05D99. For additional information and updates on this book, visit www.ams.org/bookpages/ulect-64 Library of Congress Cataloging-in-Publication Data Names: Guth, Larry, 1977– Title: Polynomial methods in combinatorics / Larry Guth. Description: Providence, Rhode Island : American Mathematical Society, [2016] | Series: Univer- sity lecture series ; volume 64 | Includes bibliographical references. Identifiers: LCCN 2016007729 | ISBN 9781470428907 (alk. paper) Subjects: LCSH: Combinatorial geometry. | Polynomials. | Geometry, Algebraic. | AMS: Combina- torics – Extremal combinatorics – None of the above, but in this section. msc Classification: LCC QA167 .G88 2016 | DDC 511/.66–dc23 LC record available at http://lccn.loc. gov/2016007729 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy select pages for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society. Permissions to reuse portions of AMS publication content are handled by Copyright Clearance Center’s RightsLink service. For more information, please visit: http://www.ams.org/rightslink.
    [Show full text]
  • ANNOUNCEMENT of WINNERS of the Seventy-Ninth Competition Held on December 1, 2018
    ANNOUNCEMENT OF WINNERS of the seventy-ninth competition held on December 1, 2018 WINNING TEAMS Rank School Team Members (in alphabetical order) 1 HARVARD UNIVERSITY Dongryul Kim, Shyam Narayanan, David Stoner 2 MASSACHUSETTS INSTITUTE OF TECHNOLOGY Junyao Peng, Ashwin Sah, Yunkun Zhou 3 UNIVERSITY OF CALIFORNIA, LOS ANGELES Ciprian Mircea Bonciocat, Xiaoyu Huang, Konstantin Miagkov 4 COLUMBIA UNIVERSITY Quang Dao, Myeonhu Kim, Matthew Lerner-Brecher 5 STANFORD UNIVERSITY David Kewei Lin, Hanzhi Zheng, Yifan Zhu The institution with the first-place team receives an award of $25,000, and each member of the team receives $1,000. The awards for second place are $20,000 and $800; for third place, $15,000 and $600; for fourth place, $10,000 and $400; and for fifth place, $5,000 and $200. In each of the following categories, the listing is in alphabetical order. THE PUTNAM FELLOWS — THE FIVE HIGHEST RANKING INDIVIDUALS Each receives an award of $2,500. DONGRYUL KIM Harvard University SHYAM NARAYANAN Harvard University DAVID STONER Harvard University YUAN YAO Massachusetts Institute of Technology SHENGTONG ZHANG Massachusetts Institute of Technology THE NEXT TEN HIGHEST RANKING INDIVIDUALS Each receives an award of $1,000. MURILO CORATO ZANARELLA Princeton University JIYANG GAO Massachusetts Institute of Technology ANDREW GU Massachusetts Institute of Technology JAMES LIN Massachusetts Institute of Technology MICHAEL MA Massachusetts Institute of Technology ASHWIN SAH Massachusetts Institute of Technology KEVIN SUN Massachusetts Institute of Technology DANIELLE WANG Massachusetts Institute of Technology HUNG-HSUN YU Massachusetts Institute of Technology YUNKUN ZHOU Massachusetts Institute of Technology THE WILLIAM LOWELL PUTNAM MATHEMATICAL COMPETITION ELIZABETH LOWELL PUTNAM PRIZE The winner receives an award of $1,000.
    [Show full text]
  • Mathematical Research in High School: the PRIMES Experience
    Mathematical Research in High School: The PRIMES Experience The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Etingof, Pavel, Slava Gerovitch, and Tanya Khovanova. “Mathematical Research in High School: The PRIMES Experience.” Notices of the American Mathematical Society 62, no. 08 (September 1, 2015): 910–918. © American Mathematical Society (AMS) As Published http://dx.doi.org/10.1090/noti1270 Publisher American Mathematical Society (AMS) Version Final published version Citable link http://hdl.handle.net/1721.1/110267 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Mathematical Research in High School: The PRIMES Experience Pavel Etingof, Slava Gerovitch, and Tanya Khovanova Consider a finite set of lines in 3-space. A joint is a point where three of these lines (not lying in the same plane) intersect. If there are L lines, what is the largest possible number of joints? Well, let’s try our luck and randomly choose k planes. Any pair of planes produces a line, and any triple of planes, a joint. Thus, they produce L := k(k − 1)/2 lines and J :=p k(k − 1)(k − 2)/6 joints. If k is large, J is 2 3=2 about 3 L . For many years it was conjectured that one cannot do much better than that, in the 3=2 sense that if L is large, thenp J ≤ CL , where C is a constant (clearly, C ≥ 2 ).
    [Show full text]
  • 2009 Mathematics Newsletter
    AUTUMN 2009 NEWSLETTER OF THE DEPARTMENT OF MATHEMATICS AT THE UNIVERSITY OF WASHINGTON Mathematics NEWS 1 DEPARTMENT OF MATHEMATICS NEWS MESSAGE FROM THE CHAIR As you might imagine, 2009 brought Department’s work continued unabated. We have a string of unusual challenges to our department. good news to share with you in this newsletter, such as the There were uncertainties well into the UW Sophomore Medal awarded to Chad Klumb, the new- spring regarding our 2009-10 aca- found success of our students in the Putnam Competition, demic year budget. Graduate student the election of Gunther Uhlmann to the American Academy recruitment, which takes place across of Arts and Sciences, and the NSF CAREER award to Ioana the nation during the winter, was Dumitriu. Our undergraduate degree programs set new highs conducted without knowing the level at the end of the 2008-09 academic year with 368 Math of our TA funding. Similar scenarios majors, and with a total of 537 majors in Math and ACMS. played out nationally as few educational institutions were Thirteen graduate students completed the PhD, continuing spared by the financial crisis. In a survey conducted by the our recent trend of awarding significantly more PhDs than American Mathematical Society, mathematics departments the Department’s historical annual average of 6.5. reported about 900 expected faculty openings nationally, During the spring and summer, we received a boost of down from about 1,500 in a typical year, despite expecting federal funding, thanks to the excellent research projects to award 1,300 PhDs in 2009 as in recent years.
    [Show full text]
  • Tobias Lee Johnson College of Staten Island, 1S-225 [email protected] 2800 Victory Blvd
    Tobias Lee Johnson College of Staten Island, 1S-225 [email protected] 2800 Victory Blvd. http://www.math.csi.cuny.edu/~tobiasljohnson/ Staten Island, NY 10314 EMPLOYMENT AND EDUCATION Assistant Professor, College of Staten Island (CUNY) Fall 2017– NSF Postdoctoral Fellow New York University; sponsored by Gérard Ben Arous Fall 2016–Spring 2017 University of Southern California; sponsored by Larry Goldstein Fall 2014–Spring 2016 Ph.D. in Mathematics, University of Washington Fall 2008–Spring 2014 Advised by Ioana Dumitriu and Soumik Pal B.A. in Mathematics, Yale University Fall 2003–Spring 2007 RESEARCH Interests: probability theory and combinatorics, with a focus on discrete random structures and interacting particle systems; Stein’s method Papers: 20. Diffusion-limited annihilating systems and the increasing convex order, with Riti Bahl, Philip Barnet, and Matthew Junge. Submitted. arXiv:2104.12797 19. Particle density in diffusion-limited annihilating systems, with Matthew Junge, Hanbaek Lyu, and David Sivakoff. Preprint. arXiv:2005.06018 18. Continuous phase transitions on Galton–Watson trees. Submitted. arXiv:2007.13864 2020 17. Random tree recursions: which fixed points correspond to tangible sets of trees?, with Moumanti Podder and Fiona Skerman. Random Structures Algorithms, 56(3):796–837, 2020. arXiv:1808.03019 2019 16. Cover time for the frog model on trees, with Christopher Hoffman and Matthew Junge. Forum Math. Sigma, 7, e41 1–49, 2019. arXiv:1802.03428 15. Infection spread for the frog model on trees, with Christopher Hoffman and Matthew Junge. Electron. J. Probab., 24 (2019), no. 112, 1–29. arXiv:1710.05884 14. Sensitivity of the frog model to initial conditions, with Leonardo T.
    [Show full text]
  • LARRY GUTH Curriculum Vitae Department Of
    LARRY GUTH Curriculum Vitae Department of Mathematics 617-253-4326 Room 2-278 [email protected] 77 Massachusetts Avenue Cambridge, MA 02139 Degrees: B.S. Mathematics, Yale University, 2000 Ph.D. Mathematics, MIT, 2005 Employment: Samelson Fellow, Stanford University, 2005-2006 Szego Assistant Professor, Stanford University, 2006-2008 National Science Foundation Postoctoral Fellow, 2006-2008 Tenure-stream Assistant Professor, University of Toronto, 2008-2011 Member, Institute for Advanced Study, 2010-2011 Professor, New York University, 2011-2012 Professor, MIT, Department of Mathematics, 2012- Claude Shannon Professor of Mathematics, MIT, 2019- Fellowships: National Science Foundation Graduate Fellowship, 2001-2003 National Science Foundation Postdoctoral Fellowship, 2006-2008 Alfred P. Sloan Research Fellowship, 2010-2014 Simons Investigator, 2014- Honors: Sloan Research Fellowship, 2010 Salem Prize, 2013 Simons Investigator, Simons Fnd, 2014 Clay Research Award, 2015 School of Science Prize for Excellence in Graduate Teaching, 2015 New Horizons in Mathematics Breakthrough Prize, 2015 Fellow of the American Academy of Arts and Sciences, 2018 Best Paper Award, International Consortium of Chinese Math., 2018 Fellow of the American Mathematical Society, 2019 B^ocher Memorial Prize, 2020 Maryam Mirzakhani Prize in Mathematics, 2020 Margaret MacVicar Faculty Fellow, MIT, 2021 Member of the National Academy of Sciences, 2021 1 B.S. Student Thesis Supervised (University of Toronto): Lisha (Janet) Li: University of Toronto: Received a 2017 PhD in Statistics & Machine Learning, from U.C. Berkeley; currently at Amplify Partners, S.F. Bay Area Graduate Students Supervised: University of Toronto: Dominic Dotterrer: PhD, University of Toronto, 2013: Dickson Instr., University of Chicago, 2013-2016; currently: Senior Research Scientist, Goldman Sachs, 2019-.
    [Show full text]
  • 2016-2017 Annual Report
    Institute for Computational and Experimental Research in Mathematics Annual Report May 1, 2016 – April 30, 2017 Brendan Hassett, Director Mathew Borton, IT Director Jeff Brock, Associate Director Ruth Crane, Assistant Director Jeffrey Hoffstein, Consulting Associate Director Caroline Klivans, Associate Director Jill Pipher, Consulting Associate Director Sinai Robins, Deputy Director Bjorn Sandstede, Associate Director Homer Walker, Deputy Director Ulrica Wilson, Associate Director for Diversity and Outreach 1 Table of Contents Mission ......................................................................................................................................................... 5 Core Programs and Events ............................................................................................................................. 5 Participant Summaries by Program Type ....................................................................................................... 8 ICERM Funded Participants .................................................................................................................................................................................. 8 All Participants (ICERM funded and Non-ICERM funded) ....................................................................................................................... 9 ICERM Funded Speakers ....................................................................................................................................................................................
    [Show full text]