# Prize and Invited Lectures

Contents

- 1 Prize
- 2 Invited Lectures
- 2.1 Prof. Cynthia Dwork
- 2.2 Prof. Youssef Marzouk
- 2.3 Prof. Tamara Kolda
- 2.4 Prof. Kavita Ramanan
- 2.5 Prof. Lior Horesh
- 2.6 Prof. Rachel Ward
- 2.7 Prof. Andrew Stuart
- 2.8 Prof. Eva Tardos
- 2.9 Prof. Jose Antonio Carrillo de la Plata
- 2.10 Prof. Gitta Kutyniok
- 2.11 Prof. Albert Cohen
- 2.12 Prof. Martin Burger
- 2.13 Prof. Francis Bach
- 2.14 Prof. Monique Laurent
- 2.15 Prof. Endre Süli
- 2.16 Prof. Michele Benzi
- 2.17 Prof. Antonin Chambolle
- 2.18 Prof. Xiaoyun Wang
- 2.19 Prof. Lei Guo
- 2.20 Prof. Ichiro Hagiwara
- 2.21 Prof. Yasuaki Hiraoka
- 2.22 Prof. Satoru Iwata
- 2.23 Prof. Gary Froyland
- 2.24 Prof. Alicia Dickenstein

## Prize

TBA

## Invited Lectures

### Prof. Cynthia Dwork

TBA

### Prof. Youssef Marzouk

TBA

### Prof. Tamara Kolda

Tamara G. Kolda is an independent mathematical consultant under the auspices of her company MathSci.ai based in California. She is also a Distinguished Visiting Professor in the Department of Industrial Engineering & Management Science at Northwestern University in Evanston, Illinois. From 1999-2021, she was a researcher at Sandia National Laboratories in Livermore, California. She specializes in mathematical algorithms and computation methods for tensor decompositions, tensor eigenvalues, graph algorithms, randomized algorithms, machine learning, network science, numerical optimization, and distributed and parallel computing. She is serves as the founding editor-in-chief for the SIAM Journal on Mathematics of Data Science (SIMODS) and as the Chair of the Illustrating the Impact of the Mathematical Sciences study for the U.S. National Academies. She is a member of the National Academy of Engineering (NAE), Fellow of the Society for Industrial and Applied Mathematics (SIAM), and Fellow of the Association for Computing Machinery (ACM).

### Prof. Kavita Ramanan

TBA

### Prof. Lior Horesh

TBA

### Prof. Rachel Ward

Rachel Ward is the W.A. “Tex” Moncrief Distinguished Professor in Computational Engineering and Sciences — Data Science and Professor of Mathematics at UT Austin. She is recognized for her contributions to stochastic gradient descent, compressive sensing, and randomized linear embeddings. From 2017-2018, Dr. Ward was a visiting researcher at Facebook AI Research. Prior to joining UT Austin in 2011, Dr. Ward received the PhD in Computational and Applied Mathematics at Princeton in 2009 and was a Courant Instructor at the Courant Institute, NYU, from 2009-2011. Among her awards are the Sloan research fellowship, NSF CAREER award, 2016 IMA prize in mathematics and its applications, 2020 Simons fellowship in mathematics. She is also an invited speaker at the 2022 International Congress of Mathematicians.

### Prof. Andrew Stuart

TBA

### Prof. Eva Tardos

TBA

### Prof. Jose Antonio Carrillo de la Plata

José A. Carrillo is currently Professor of the Analysis of Nonlinear Partial Differential Equations at the Mathematical Institute and Tutorial Fellow in Applied Mathematics at The Queen’s College, University of Oxford associated to the OxPDE and WCMB groups. He was previously Chair in Applied and Numerical Analysis at Imperial College London from October 2012 till March 2020 and ICREA Research Professor at the Universitat Autònoma de Barcelona during the period 2003-2012. He was a lecturer at the University of Texas at Austin 1998-2000; and held assistant and associate professor positions at the Universidad de Granada 1992-1998 and 2000-2003, where he also did his PhD. He works on kinetic equations and nonlinear nonlocal diffusion equations. He has contributed to the theoretical and numerical analysis of PDEs, and their simulation in different applications such as granular media, semiconductors and lately in collective behaviour. His main scholarship contributions in analysis of PDEs are in aggregation-diffusion problems, i.e. nonlinear Fokker-Planck type equations; the use of optimal transport techniques and entropy methods to analyse theoretically and numerically gradient-flow structures for PDEs and their singularities; the analysis of kinetic models for self-organization, and their implications in mathematical biology, control engineering and global optimization. He has also developed numerical schemes for nonlinear aggregation-diffusions and gradient flows preserving the free energy decay property and thus the equilibrium measures and is lately interested in extending these properties to phase transitions. His interests in mathematical biology include the understanding of cell sorting by differential adhesion and synchronization phenomena in neuroscience.

He served as chair of the Applied Mathematics Committee of the European Mathematical Society 2014-2017. He was the chair of the 2018 Year of Mathematical Biology. He was the Program Director of the SIAM activity group in Analysis of PDE 2019-2020. He is vice-president of the European Society for Mathematical and Theoretical Biology 2021-2023; and member of the Scientific Committee of the Spanish National Science Agency 2021-2024. He was elected as member of the European Academy of Sciences, Section Mathematics in 2018, SIAM Fellow Class 2019, Fellow of the Institute of Mathematics and its Applications, and Foreign Member of the Royal Academy of Sciences of Spain since 2021. He is currently the head of the Division of the European Academy of Sciences, Section Mathematics. He was recognised with the SEMA prize (2003) and the GAMM Richard Von-Mises prize (2006) for young researchers, a Wolfson Research Merit Award by the Royal Society 2012-2017, and the 2016 SACA award for best PhD supervision at Imperial College London. He has been Highly Cited Researcher in 2015, 2016, 2017, 2018, 2019, and 2020 by Web of Science. He has been awarded an ERC Advanced Grant 2019 to pursue his investigations in complex particle dynamics: phase transitions, patterns, and synchronization.

### Prof. Gitta Kutyniok

TBA

### Prof. Albert Cohen

My early research works (from my PhD of 1990, supervised by Yves Meyer, until 1998) were concerned with the development of the theory of wavelet bases in relation with algorithms used in signal and image processing, or in computer aided geometric design. One significant achievement was the derivation, together with Ingrid Daubechies and Jean-Christophe Feauveau, of biorthogonal wavelet bases which are used in the state of the art image compression standard JPEG 2000.

Since 1998, my research is oriented in various applicative directions, with as a common denominator its theoretical foundations in nonlinear approximation theory and harmonic analysis. In particular, it has led to the development and analysis of adaptive and sparsity-based numerical methods in various application contexts such as (i) data compression, (ii) statistical estimation and learning theory or (iii) discretizations of partial differential equations.

I am often joining forces with my colleagues Wolfgang Dahmen and Ronald DeVore. Some of our most significant results are concerned with the analysis of adaptive methods for PDE’s, the space BV, greedy algorithms, and statistical learning theory. A topic of particular interest the present time is high-dimensional approximation problems arising in learning theory and in the numerical treatment of parametric and stochastic PDE’s.

My current research is in particular concerned with problems that involve a very large number of variables, and whose efficient numerical treatment is therefore challenged by the so-called curse of dimensionality, meaning that computational complexity increases exponentially in the variable dimension. Such problems are ubiquitous in an increasing number of applicative areas, among which statistical or active learning theory, parametric and stochastic partial differential equations, parameter optimization in numerical codes, with a high demand from the industrial world of efficient numerical methods. Central scientific objectives in this context are (i) to identify fundamental mathematical principles behind overcoming the curse of dimensionality, (ii) to understand how these principles enter in relevant instances of the applications described above, and, (iii) based on these principles to develop broadly applicable concrete adaptive numerical strategies that benefit from such mechanisms.

This research has been supported by the Advanced ERC grant BREAD (Breaking the Curse of Dimensionality in Analysis and Simulation) awarded in 2014.

### Prof. Martin Burger

Martin Burger is a Professor of Applied Mathematics at the Department of Mathematics, Friedrich-Alexander University Erlangen-Nürnberg. His interests include nonlinear partial differential equations, inverse problems, and variational techniques in imaging. In particular, he is known for the development and mathematical analysis of nonlinear regularization methods for inverse and imaging methods. His further interests include the development of mathematical models in life and social sciences, which together drive interdisciplinary research developments, e.g., in biomedical imaging. Martin Burger has received several awards and honors for his scientific contributions, such as the Calderon prize for distinguished contributions in the field of inverse problems.

He serves on editorial boards of several journals and is one of the editors-in-chief of the European Journal of Applied Mathematics.

### Prof. Francis Bach

TBA

### Prof. Monique Laurent

TBA

### Prof. Endre Süli

The work of Endre Süli is concerned with the analysis of numerical algorithms for the approximate solution of partial differential equations and the mathematical analysis of nonlinear partial differential equations in continuum mechanics.

Born in Yugoslavia in 1956, he was educated at the University of Belgrade and did his graduate work as a British Council Scholar at the University of Reading and at St Catherine’s College, Oxford. He received his doctorate in mathematics from the University of Belgrade in 1985, and in the same year he was appointed to a faculty position at the University of Oxford, where he is a Professor of Numerical Analysis and a Fellow of Worcester College.

He was elected a Foreign Member of the Serbian Academy of Sciences and Arts (2009), a Member of the European Academy of Sciences (2010), a Fellow of the Society of Industrial and Applied Mathematics (2016), a Member of the Academia Europaea (2020), and a Fellow of the Royal Society (2021).

His other honours include: Chair, Society for the Foundations of Computational Mathematics (SFoCM, 2002–2005), Invited Speaker at the International Congress of Mathematicians (ICM 2006, Madrid), Fellow of the Institute of Mathematics and its Applications (FIMA, 2007), Charlemagne Distinguished Lecture, Aachen (2011), IMA Service Award (2011), Professor Hospitus Universitatis Carolinae Pragensis, Charles University in Prague (2012–), Distinguished Visiting Chair Professor, Shanghai Jiao Tong University (2013), President, SIAM United Kingdom and Republic of Ireland Section (2013–2015), London Mathematical Society/New Zealand Mathematical Society Forder Lecturer (2015), Aziz Lecture, University of Maryland (2015), BIMOS Distinguished Lecture, Berlin (2016), John von Neumann Lecture, Münster (2016), Sibe Mardešić Lecture, Zagreb (2018), and London Mathematical Society Naylor Prize and Lectureship (2021).

### Prof. Michele Benzi

Michele Benzi was born and raised in Bologna, Italy, where he attended the local university, graduating in Mathematics with honors in 1987. He received a PhD degree in Applied Mathematics in 1993 from North Carolina State University. After holding positions at the University of Bologna, at CERFACS in Toulouse (France) and at Los Alamos National Laboratory, in 2000 he joined the faculty of Emory University in Atlanta. He was promoted to full professor in 2006, and in 2012 he was named the Samuel Candler Dobbs Professor of Mathematics and Computer Science. In 2018 he returned to Italy as Professor of Numerical Analysis at the Scuola Normale Superiore in Pisa. He is the author or co-author of over 130 publications and has supervised 15 PhD students and post-docs. Michele Benzi serves, or has served, on the editorial board of 20 scientific journals, and is currently the Editor-in-Chief of SIAM Journal on Matrix Analysis and Applications. He is the recipient of several awards, including the SIAM Outstanding Paper Prize (2001, joint with M. Tuma). His research has been supported by the US National Science Foundation, the US Department of Energy, and the Italian Ministry of University and Research.

Michele Benzi is a SIAM Fellow (2012), a Fellow of the American Mathematical Society (2018), and a member of Academia Europaea (2019).

### Prof. Antonin Chambolle

Antonin Chambolle is currently a CNRS senior research scientist working at CEREMADE, the applied mathematics department of Université Paris-Dauphine in Paris, France. Prior, he held a similar position in applied mathematics at CMAP, Ecole Polytechnique, Palaiseau, with also a teaching position. His interests is in mathematical methods for the studies of discontinuities, singularities and geometric variational problems, for applications ranging from image reconstruction, data analysis, to elasticity problems with fractures and materials science. His work addresses theoretical issues, such as the existence of a crystalline mean curvature flow or of minimizers of linearized elasticity energies with fracture terms, numerical issues such as the discretization of singular functionals (total variation, Mumford-Shah) and algorithmic and computational issues. He is the co-authors of several works in mathematical programming developing efficient algorithms for non-smooth convex optimization and was awarded the “Michel Monpetit-INRIA” prize by the French Academy of Science in 2021.

He studied at Ecole Normale Supérieure in Paris and then obtained a PhD from Université Paris-Dauphine in 1993, under the supervision of Prof. Jean-Michel Morel. He also spent some time in SISSA, Trieste, Italy, in the group of Prof. Gianni Dal Maso. Later, he was “French Government Fellow” at Churchill College, Cambridge (UK) in 2015-16, working with the Cambridge Image Analysis at DAMTP.

### Prof. Xiaoyun Wang

Xiaoyun Wang is a mathematician and cryptographer. She is a C. N. Yang Professor in Institute for Advanced Study, Tsinghua University, the Academician of Chinese Academy of Sciences and the International Association for Cryptologic Research (IACR) fellow. Xiaoyun Wang is well-known for her research on hash functions. Hash functions are the key technique of many cryptographic applications such as digital signatures, integrity verifications, password validations and blockchains. A hash function generates a short digest (digital fingerprint) of the input message. Collision-resistance is one of three security properties of cryptographic hash functions (the others are preimage resistance and second-preimage resistance). Xiaoyun Wang developed the bit-based cryptanalysis theory, and gave the collision attack on five dedicated hash functions including widely deployed MD5 and SHA-1. In response to SHA-1 attack, the US National Institute for Standards and Technology (NIST) recommended the replacement of SHA-1 by SHA-2 hash function family and announced a 5-year project to design the new hash function standard SHA-3. She was in charge of designing SM3 cryptographic hash function, as the Chinese standard, which has been deployed widely in financial, transportation, state grid and other important economic fields in China. In October 2018, SM3 officially became one of the ISO/IEC standards of new generation hash functions. She also analysed some cryptographic primitives with keys, including message authentication codes, symmetric ciphers and authenticated encryption schemes, and achieved very important results on HMAC-MD5, MD5-MAC, SIMON, Keccak-MAC, etc. Since 2006, she has been focusing on post-quantum public-key cryptography, and gave innovative results in lattice-based cryptography, including a two-level heuristic sieve algorithm for general lattices and the design of practical lattice-based algorithms with tight security.

### Prof. Lei Guo

Lei GUO received his B.S. degree in mathematics from Shandong University in 1982 and a Ph.D. degree in control theory from the Chinese Academy of Sciences (CAS) in 1987. He was a postdoctoral fellow at the Australian National University from 1987 to1989 and became a Professor of the Institute of Systems Science at CAS in 1992. From 2002 to 2012, he was the President of the Academy of Mathematics and Systems Science at CAS. He has been the Director of the National Center for Mathematics and Interdisciplinary Sciences at CAS since 2010.

Dr. Guo is a Fellow of IEEE, Member of CAS, Fellow of the Academy of Sciences for the Developing World (TWAS), Foreign Member of the Royal Swedish Academy of Engineering Sciences, and Fellow of the International Federation of Automatic Control (IFAC). He received the 1993 IFAC World Congress Young Author Prize, the IFAC Outstanding Service Award, and an honorary doctorate from the Royal Institute of Technology (KTH), Sweden. He delivered plenary lectures at the triennial IFAC World Congress twice, in 1999 and 2014, and an invited lecture at the International Congress of Mathematicians (ICM) in 2002. In 2019, he was awarded the Hendrik W. Bode Lecture Prize by the IEEE Control Systems Society “for fundamental and practical contributions to the field of adaptive control, system identification, adaptive signal processing, stochastic systems, and applied mathematics” in France, where he delivered the Bode Prize Lecture at the 58th IEEE Conference on Decision and Control.

He formerly served as Council Member of IFAC (2005-2011), General Co-Chair of the 48th IEEE Conference on Decision and Control (CDC’2009), Congress Director of the 8th International Congress on Industrial and Applied Mathematics (ICIAM’2015), and President of the China Society for Industrial and Applied Mathematics (CSIAM, 2008-2016). He has also served as a member of editorial boards of several professional journals including SIAM J. Control and Optimization.

His research interests include stochastic systems, adaptive control, system identification, adaptive filtering, machine learning, control of nonlinear and uncertain dynamical systems, maximum feedback capability, multi-agent systems, and game-based control systems.

### Prof. Ichiro Hagiwara

Ichiro HAGIWARA Distinguished Professor Emeritus, Dr. Eng. ASME Fellow, Research and Intellectual Property Strategic Organization, Meiji Institute for Advanced Study of Mathematical Sciences(MIMS),

Meiji University’s Institute of Autonomous Driving(MIAD), Emeritus Professor of Tokyo Institute of Technology, Member of Science Council of Japan(SCJ).

He received his BS and MS Degrees in applied mathematical engineering from Kyoto University in 1970 and 1972. Also he received his PhD in mechanical engineering from the University of Tokyo in 1990. He worked as a researcher at the research center of Nissan Motor Co., Ltd. from April of 1972 to March of 1996. He worked as a professor Department of Mechanical Sciences and Engineering, Graduate School of Science and Engineering, Tokyo Institute of Technology(TIT)from April 1st in 1996 to 31st of March in 2012. And since april 1st, he has worked in Meiji University, Second Director, Institute for Advanced Study of Mathematical Sciences(MIMS), Professor, Organization for the Strategic Coordination of Research and Intellectual Property (Emeritus Professor of Tokyo Institute of Technology). He is now engaged in MIMS and MIAD(Meiji university’s Institute of Autonomous Driving) as a Meiji University distinguished professor emeritus. He is an honorary member of JSIAM(Japan Society for Industrial and Applied Mathematics), JSME(Japan Society of Mechanical Engineers),JSST(Japan Society for Simulation Technology) and JACM(Japan Association for Computational Mechanics). He is a fellow member of ASME (American Society of Mechanical Engineers), JSAE(Society of Automotive Engineers of Japan) and ASIAIM(Asia Simulation Association). He served as a consulting professor at Harbin Institute of Technology, P.R.Ckina. He also served as a guest professor & a consulting professor of The State Key Laboratory of Vibration, shock & Noise of Shanghai Jiao Tong University, P.R.China. And he served as a Foreign communication member of the academic committee of the state key laboratory of automotive safety and energy of Tsinghua University, P.R.China, an honorary professor of School of Mechanical Engineering on Jianjin University, P.R.China and an additional professor of Huazhong University of Science and Technology and an additional professor of Nanjing university of information & technology, P.R.China. He is also a member of Science Council of Japan(SCJ) since March of 2006. He received numerous awards from several academic societies at home and abroad for his various types of researches for computational mechanics, sound and vibration, machine learning, control and origami engineering. He also received Minister of Education, Culture, Sports, Science and Technology Award for his computational mechanics aided origami engineering. He is now interested in both of origami engineering and intelligent self-driving car.

His title for the invited lecture in ICIAM 2023 is “Mathematical sciences for realization of origami engineering aided land / sea / air self-driving car with intelligence”. The lecture will consist of origami engineering, machine learning, optimal control and control of plural eigenfrequencies. In origami engineering, it will be shown the most splendid Japanese Kirigami honeycomb which receives very much attention because it is the best treasure trove to produce metamaterials. As far as machine learning, it will be shown his own technology FQHNN(Fuzzy Quantification method aided Holographic Neural Network) which has causal information unlike CNN(Convolutional Neural Network) which leads the third generation of machine learning. And in optimal control, it will be shown also his own method which is only one real-time optimal control method. The so-called optimal control is not used in the real car because Pontryagin’s maximum principle gives the nonlinear equation which cannot be solved in real time. He has noticed the analogy of the new optimal control theory and the nature of the solution of parabolic equations for the first time and this has contributed to pass this problem. As far as control of plural eigenfrequencies, it is very difficult to be applied the conventional topology optimization. He has developed a new high speed and high accuracy topology change method for ride quality improvement and elimination of anxiety due to the absence of the driver in the self-driving car from observations of strain and dynamic energy distributions of each eigen frequency mode. He is mobilizing with his lab members all of these technologies to successfully create an origami engineering aided land / sea / air self-driving car with intelligence. Here he will discuss the mathematical backbones for these techniques which successfully develop the dream land / sea / air self-driving car with intelligence.

### Prof. Yasuaki Hiraoka

TBA

### Prof. Satoru Iwata

TBA

### Prof. Gary Froyland

Gary Froyland is a professor of mathematics at the University of New South Wales in Sydney, Australia.

### Prof. Alicia Dickenstein

Alicia Dickenstein is a Professor at the University of Buenos Aires and a Senior Researcher at CONICET, the National Research Council of Argentina. She is a Member of the National Academy of Exact and Natural Sciences and of the National Academy of Sciences of Argentina. She was Vice-President of the International Mathematical Union. She is an AMS Fellow and a SIAM Fellow. She holds Honorary Doctorates from UNS, Argentina, and KTH, Sweden. She received the 2015 TWAS Prize in Mathematics and a 2021 L’Oréal-UNESCO Award “For Women in Science”.