Rafail Ostrovsky, professor of Computer Science and Mathematics at UCLA, has been elected as a Foreign Member of Academia Europaea class of 2019! Among his many accomplishments, Ostrovsky is the Director for the Center of Information and Computation Security at the Henry Samueli School of Engineering and Applied Science at UCLA. He has been a core participant for three IPAM long programs and an organizer, speaker, and panelist for numerous workshops. He will be speaking in IPAM’s upcoming workshop on Deep Fakery: Mathematical, Cryptographic, Social, and Legal Perspectives.

Founded in 1988, the Academia Europaea strives for advancement and propagation of excellence in scholarship in the humanities, law, the economic, social, and political sciences, mathematics, medicine, and all branches of the natural and technological sciences anywhere in the world for the public benefit and for the advancement of the education of the public of all ages in aforesaid subjects in Europe. This prestigious membership is by invite only through rigorous peer nomination.

]]>IPAM is pleased to share our annual newsletter featuring Tatiana Toro’s (University of Washington) inspiration for the Latinx in the Mathematical Sciences (LatMath) Conference and Frank Noe’s (Freie Universität Berlin) experience in establishing interdisciplinary collaborations in the dynamic field of machine learning at IPAM. This newsletter also introduces IPAM’s new Industrial Short Course series and highlights one graduate student’s testament of IPAM’s influence on her budding academic career. Keep reading to find short excerpts about IPAM’s diversity and summer programs, as well as accomplishments by IPAM affiliates. Print copies are available at IPAM.

]]>Alex Eskin (University of Chicago) was awarded the 2020 Breakthrough Prize in Mathematics for revolutionary discoveries in the dynamics and geometry of moduli spaces of Abelian differentials, including the proof of the “magic wand theorem” with Maryam Mirzakhani. Known as the “Oscars of Science,” the prize recognizes achievements in the Life Sciences, Fundamental Physics and Mathematics. Tim Austin (UCLA) was awarded the 2020 New Horizons in Mathematics Prize for multiple contributions to ergodic theory, most notably the solution of the weak Pinsker conjecture. Both Austin and Eskin were most recently participants in IPAM’s 2018 workshop on New Methods for Zimmer’s Conjecture, of which Eskin was an organizer. Congratulations to both of them on their remarkable achievements!

Complete list of 2020 Breakthrough Prize and New Horizons Prize Winners

]]>IPAM is pleased to welcome three new members to its Science Advisory Board this fall: Richard Kenyon, Ryan Tibshirani, and Daniela Witten.

- Kenyon is the Erastus L. DeForest Professor of Mathematics at Yale University. His research focuses on mathematical models of crystal formation and phase transitions. Kenyon was an organizer and core participant for IPAM’s 2007 spring long program Random Shapes. He was an organizer and speaker for multiple workshops within Random Shapes and will be a speaker in IPAM’s upcoming 2020 winter workshop Asymptotic Algebraic Combinatorics.

- Tibshirani is an Associate Professor in the Department of Statistics and Machine Learning at Carnegie Mellon University. His research interests lie broadly in statistics, machine learning, and optimization. He is an Associate Editor for multiple journals such as
*Annals of Statistics*and the*Journal of Machine Learning Research*. Tibshirani is also on the Editorial Board for the*Springer Series in Data Sciences*.

- Witten is the Dorothy Gilford Endowed Chair in Mathematical Sciences and a Professor of Statistics and Biostatistics at University of Washington’s School of Public Health. Her research involves the development of statistical machine learning methods for high-dimensional data with applications to genomics and other fields. Witten recently received the Spiegelman Award for outstanding public heath statistician under the age of 40.

IPAM’s Science Advisory Board Meeting convenes in early November to review proposals to determine IPAM’s 2021/2022 programs. Proposals for long and short programs will be accepted until October 1^{st} and should be sent to director@ipam.ucla.edu.

The June/July 2019 issue of *Notices of the American Mathematical Society (Notices)* featured an extensive list of recent recipients of major awards and achievements throughout the global mathematical community. Included in the list are the following IPAM affiliates:

- Dimitris P. Bertsekas (Massachusetts Institute of Technology (MIT)) speaker for both IPAM’s 2014 winter workshop Stochastic Gradient Methods and the upcoming 2020 winter workshop Intersections between Control, Learning and Optimization. Awarded the John von Neumann Theory Prize for “contributions to parallel and distributed computation as well as neurodynamic programming.” This was a joint award with MIT colleague John Tsitsiklis.
- Greg Lawler (University of Chicago) speaker for many IPAM workshops, most recently IPAM’s 2019 winter workshop Analysis and Geometry of Random Shapes. Awarded the 2019 Wolf Prize for “his comprehensive and pioneering research on erased loops and random walks.” This was a joint award with Jean-François Le Gall of Université Paris-Sud Orsay.
- Jeremy Quastel (University of Toronto) speaker for IPAM’s 2014 winter workshop Rough Paths: Theory and Applications. Awarded the 2019 Jeffery-Williams Prize for Research Excellence of the Canadian Mathematical Society (CMS) for his “ground-breaking results in probability and non-equilibrium statistical mechanics, in particular, his recent discovery with Matetski and Remenik of the complete integrability of TASEP, and through a scaling limit, the strong coupling fixed point of the KPZ universality class.”
- Luitgard Veraart (London School of Economics and Political Science (LSE)) speaker for IPAM’s 2015 spring workshop Systemic Risk and Financial Networks. Awarded the 2019 Adams Prize in Mathematics for developing “new tools and concepts relevant for the representation and analysis of financial stability and systemic risk in banking networks.” This was a joint award with Heather Harrington of the University of Oxford.
- Avi Wigderson (Institute for Advanced Study) organizer and speaker for multiple programs including IPAM’s winter 2008 workshop Expanders in Pure and Applied Mathematics, core participant for IPAM’s spring 2014 long program Algebraic Techniques for Combinational and Computational Geometry, and speaker for IPAM’s 2014 Green Family Lecture Series. Awarded the 2019 Donald E. Knuth Prize for “fundamental and lasting contributions in areas including randomized computation, cryptography, circuit complexity, proof complexity, parallel computation, and our understanding of fundamental graph properties.”

*Notices* is produced by American Mathematical Society (AMS). The full electronic version of Volume 66, Number 6 is available here.

The Peter Henrici Prize is awarded for “contributions to applied analysis and numerical analysis and/or for exposition appropriate for applied mathematics and scientific computing.” It is presented every four years by SIAM and ETH Zurich. The prize honors Peter Henrici, a Swiss numerical analyst and teacher at the Eidgenössische Technische Hochschule-Zürich (ETH Zurich) for 25 years.

Congratulations to Weinan E on this great achievement!

]]>As technology advances, there is an ever-increasing demand to acquire, analyze, and generate 3D data. These necessarily large data sets must be amenable to efficient processing, analysis, and implementation in a variety of settings such as multi-dimensional modeling, high-resolution visualization, medical imaging, and the entertainment industry. Beyond 3D shapes, understanding and learning high-dimensional geometric structures is an active area of research. Given the goals of this program, the Core Participants identified four areas of particular interest: (1) 3D shape analysis, (2) graphs and data, (3) optimal transport and Wasserstein information geometry, and (4) practical matters.

3D shape modeling and analysis is critical in efforts to digitize and replicate the world without losing the core geometric information. Several applications like 3D content generation, shape modeling, animation, and manufacturing necessitate novel shape-analysis approaches. Fortunately, recent advances in deep-learning architectures (e.g., Convolutional Neural Networks) have facilitated solutions to many difficult problems in the 2D domain. In this program, a primary motivation was to adapt these advances to the 3D domain and thereby bridge the gap between traditional 3D shape analysis and deep learning methods. An important question emerged: In addition to using machine learning to understand geometry, how can geometry be used to understand machine learning (ML)? We believe that formulations around strong shape priors and shape properties will play a crucial role in understanding complex neural networks. Moreover, it will be essential to develop holistic shape-understanding systems where the analysis goes beyond the 3D geometry to including texture, color, material, and semantic information.

Graph-based analysis methods have been increasingly used for large-scale pattern recognition. Graph neural networks can learn representations of nodes, edges, subgraphs, whole graphs, and spaces of graphs. The generality of these networks allow for neural graph representation learning to be applied to many domains where standard techniques fail. This is especially true for problems that involve heterogeneous data. Graph neural networks explicitly learn lower dimensional graph representations for less computational cost than classical dimensionality-reduction algorithms. Properly defining convolution-like graph operations is fundamental to formulating these networks and is an active area of research. Furthermore, incorporation of topological data-analysis tools (e.g., the study of persistent homologies) may geometrically motivate neural-network architectures.

Optimal transport provides a geometric framework for the study of probability distributions by extending the geometry of the sample space. It defines a similarity measures between (high-dimensional) distributions, providing geometric tools for navigating the space of probability distributions. In contrast to information theoretical divergences that do not consider the geometry of the sample space, this is an inherent consideration in optimal transport. In particular, Wasserstein metrics extend distance functions of sample spaces to distances between distributions. Solution of optimal transport problems is amenable to ML because the approach can be applied to minimize the distance between a probabilistic model and a data population; this should be further investigated. Moreover, potential associations between the geometric structures from optimal transport and other ML methods, such as kernel methods, should be explored.

Finally, the group espoused rigorously deriving the mathematical formalisms required to explain, describe, and predict the performance of ML models. For example, robust mathematical analyses would help to characterize aspects of the behavior of ML (e.g., why transfer learning works, how dropout is so effective in reducing overfitting, etc.). Moreover, because important decisions will increasingly be made with the assistance of AI, ML models must be verified and validated to build confidence in their estimates and predictions (e.g., machine-learning-assisted medical diagnoses and treatments). Perhaps a more thorough mathematical understanding of ML will help address important societal issues identified by the group. As AI systems become increasingly prevalent in everyday life and infrastructure, the social impacts of adversarial attacks, loss of privacy and anonymity, and intentional manipulation must be forefront. Risks include abuse of natural language processors (fake news), subversion of security systems (altered facial recognition), malicious and adversarial attacks on infrastructure (vulnerability of the power grid), and perhaps most importantly, job displacement. It is incumbent upon experts in our field to inform policy makers and decision makers so that proper regulations can be developed and laws enacted to protect individuals, societies, and economies.

Overall, participants in this program thoughtfully identified and outlined some of the fields and tools with the potential to yield significant impacts at the intersection of mathematics and ML. These fields include differential geometry, topology, probability theory, information geometry, optimal transport, partial differential equations, harmonic analysis, graph theory, combinatorics, functional analysis, linear algebra, and optimization, among others.

Read the full report.

]]>On June 15, 2019, the 2018 Association for Computing Machinery (ACM) Fellows were recognized at the annual ACM Awards Banquet in San Francisco. These 56 computing professionals were chosen for their “significant contributions in areas including computer architecture, mobile networks, robotics, and systems security.” IPAM would like to congratulate the following IPAM affiliates:

- Katy Börner (Indiana University), IPAM Board of Trustees member since 2008, organizer and speaker for IPAM’s 2016 workshop Culture Analytics and User Experience Design and core participant for IPAM’s spring 2016 long program Culture Analytics
- Adnan Darwiche (University of Pennsylvania), speaker for IPAM’s 2007 Graduate Summer School: Probabilistic Models of Cognition: The Mathematics of Mind
- Bangalore S. Manjunath (University of California, Santa Barbara), organizer for IPAM’s winter 2002 workshop Mathematical Challenges in Scientific Data Mining
- Fei-Fei Li (Stanford University), organizer and speaker for IPAM’s 2013 Graduate Summer School: Computer Vision
- Amit Sahai (University of California, Los Angeles), speaker for multiple workshops, including IPAM’s 2006 workshop Foundations of Secure Multi-party Computation and Zero-knowledge and Its Applications, of which he was also an organizer and core participant for both IPAM’s fall 2006 and 2007 long programs
- Avi Wigderson (Institute for Advanced Study), organizer and speaker for multiple programs including IPAM’s winter 2008 workshop Expanders in Pure and Applied Mathematics, core participant for IPAM’s spring 2014 long program Algebraic Techniques for Combinational and Computational Geometry, and speaker for IPAM’s 2014 Green Family Lecture Series

The ACM Fellows program was established in 1993 and celebrates the leading members of ACM. ACM is the world’s largest educational and scientific computing society aiming to further collaboration and support among educators, researchers, and professionals to better address today’s challenges in the science of computing.

]]>The Simons Foundation has chosen the 2019 Simons Fellows in Mathematics and Theoretical Physics. These fellows will be funded for up to a year of academic leave, “enabling recipients to focus solely on research for the long periods often necessary for significant advances.” Among the remarkable mathematicians and theoretical physicists are the following IPAM affiliates:

- Federico Ardila (San Francisco State University), organizer for both the 2015 and 2018 Latinx in the Mathematical Sciences Conference and speaker for the 2011 NSF Mathematics Institutes’ Modern Math Workshop (at SACNAS)
- William Duke (University of California, Los Angeles), organizer for IPAM’s 2002 workshop Contemporary Methods in Cryptography
- Nets Katz (California Institute of Technology), organizer and core participant for IPAM’s spring 2014 long program Algebraic Techniques for Combinatorial and Computational Gravity and speaker for many workshops, most recently IPAM’s 2014 workshop Combinatorial Geometry Problems at the Algebraic Interface
- Inwon Kim (University of California, Los Angeles), speaker for two IPAM workshops, including the 2017 workshop Mean Field Games and core participant for IPAM’s spring 2008 long program Optimal Transport
- Tatiana Toro (University of Washington), Board of Trustees member since 2009, organizer for multiple IPAM programs including the 2015 and 2018 Latinx in the Mathematical Sciences Conference, speaker for multiple workshops and most recently IPAM’s 2013 panel discussion “¿Así Que Quieres Ser un Matemático?,” and core participant in IPAM’s spring 2013 long program Interactions Between Analysis and Geometry

The Simons Foundation’s mission is to advance the frontiers of research in mathematics and the basic sciences. The grants are awarded in four areas of research: Mathematics and Physical Sciences, Life Sciences, autism research, and Outreach & Education. The Mathematics and Physical Sciences division was established in 2010.

]]>On April 30, 2019, 125 new members were elected into the National Academy of Sciences (NAS). IPAM is delighted to announce the following affiliates elected this year:

- Russel E. Caflisch (Courant Institute of Mathematical Sciences, New York University), IPAM’s former Director from 2008-2017, an active member of IPAM’s Board of Trustees since 2017, and an organizer and speaker for many long programs and workshops

- Jennifer T. Chayes (Microsoft Research), an organizer and speaker for many workshops, and most recently an organizer for IPAM’s 2018 workshop on HPC for Computationally and Data-Intensive Problems

- Bryna Rebekah Kra (Northwestern University), a member of IPAM’s Board of Trustees from 2011-2015

- Barry Simon (California Institute of Technology), a speaker for IPAM’s 2001 workshop on Oscillatory Integrals and Dispersive Equations and for a 2013 workshop on Semiclassical Origins of Density Functional Approximations

Membership is one of the highest honors for active contributors to the international scientific community. NAS members are peer nominated and elected for their “distinguished and continuing achievements in original research.” Forty percent of this year’s member elects are women—the most ever elected in any one year to date. The NAS is a private, nonprofit institution established in 1863.

]]>Dr. Emily Carter will be returning to UCLA as Executive Vice Chancellor and Provost, effective September 1, 2019. In this role, Carter will be UCLA’s chief academic officer, bringing leadership and a fresh perspective to campus-wide policy, planning, initiatives, and operations. IPAM is particularly thrilled with this appointment as Carter has been involved with IPAM since its inception. She helped establish IPAM, was an organizer and a speaker for many workshops through the years, as well as a keynote speaker in IPAM’s 2013 public lecture, Quantum Mechanics and the Future of the Planet. Carter spent 16 years as a UCLA faculty member before heading to Princeton where she currently serves as dean of the School of Engineering and Applied Sciences, the Gerhard R. Andlinger Professor in Energy and the Environment, and a professor of mechanical and aerospace engineering and of applied and computational mathematics. Welcome back, Dr. Carter!

]]>The American Academy of Arts and Sciences has elected over 200 exceptional individuals for their “outstanding achievements in academia, the arts, business, government, and public affairs.” IPAM is especially proud to congratulate our affiliates: **Mikhail Lyubich** (Stony Brook University), organizer for a 2013 workshop on Dynamics of Groups and Rational Maps; **Claire Tomlin** (UC Berkeley), Science Advisory Board member from 2009-2015 and speaker and organizer for multiple workshops, including an upcoming 2020 spring long program on High Dimensional Hamilton-Jacobi PDE’s; and **Ofer Zeitouni** (Weismann Institute of Science), speaker for a 2018 workshop on Random Matrices and Free Probability Theory. This extraordinary honor was founded in 1780 by John Adams, John Hancock, and others to recognize exceptionally accomplished individuals and engage them in advancing the public good. While the diversity in the fields have increased, the founders’ mission has remained steadfast over two centuries later. The 239^{th} class will have an induction ceremony in October 2019, in Cambridge, Massachusetts.