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AN21 Prize Spotlight

Congratulations to the following 18 members of the SIAM community who will receive awards at the virtual SIAM Annual Meeting (AN21). Additional information about each recipient, including Q&As, can be found below.



Vivette Girault

Vivette Girault has been selected to present the 2021 AWM-SIAM Sonia Kovalevsky Lecture .The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. Girault will give a lecture titled “From Linear Poroelasticity to Nonlinear Implicit Elastic and Related Models” on July 19, 2021 at 3:15 p.m. Eastern time.

Vivette Girault

The AWM-SIAM Sonia Kovalevsky Lecture is awarded annually by the Association for Women in Mathematics (AWM) and SIAM to highlight significant contributions of women to applied or computational mathematics. The lecture is normally given at the SIAM Annual Meeting.

Girault was born in France and went to primary school there until her family moved to Caracas, Venezuela and she attended Colegio Americano, an American high school in Caracas. After graduation, she did her undergraduate studies at McGill University in Montreal, Canada. After graduating from McGill University, Girault returned to France, where she started studying numerical analysis. At that time, numerical analysis was a new topic at the University of Paris, and she was very fortunate to be in the class of Professor Jacques-Louis Lions, a splendid mentor. Thanks to him, she was offered an assistant professorship in applied mathematics at the University of Paris, afterward named University Pierre et Marie Curie (UPMC) and now Sorbonne University. Girault worked her whole career there, except for two years when she worked at the University of Houston (Texas) with the groups of Dr. R. Glowinski and Dr. L.R. Scott.

At UPMC, Girault worked mostly with Dr. P.-A. Raviart, Dr. C. Bernardi, and Dr. F. Hecht. She also collaborated with the group of Dr. T. Chacon at the University of Sevilla (Spain) and the group of Dr. H. Lopez at UCV (Universidad Central de Venezuela). She retired from UPMC in 2008, became emeritus professor there, and was visiting professor and scholar first at the University of Pittsburgh (group of Dr. I. Yotov), and next in Texas: U of H (group of Dr. Y. Kuznetsov), UT Austin (group of Dr. M.F. Wheeler), Texas A&M  (groups of Dr. A. Bonito, Dr. J.-L. Guermond,  Dr. K.R. Rajagopal) and Rice University (group of Dr. B. Riviere). Because of her close connection to Texas, her research that was originally on the theory and discretization of Navier-Stokes equations, veered mostly to the theory and numerics of problems of complex fluids, problems of poroelasticity, and now fascinating problems of nonlinear implicit models introduced by Professor K.R. Rajagopal.

Q: Why are you excited to receive the award of the AWM-SIAM Sonia Kovalevsky Lecture?

A: I am very excited and grateful because it is a great honor to receive this award and it recognizes the importance of applied mathematics.

Q: Could you tell us a bit about the research that won you the prize?

A:  I like to solve equations of mechanical models arising from real life applications. And when it comes to numerical methods, I prefer those that are most likely to be adopted in practical computations. Of course, one cannot do everything, but whenever possible, I like to solve new problems and learn new methods.

Q: What does your work mean to the public?

A: In addition to the above choice of problems and numerical methods, it is important to convey the idea that rigorous mathematics can be applied to the theoretical analysis of a problem as well as to the convergence of numerical schemes and numerical algorithms. 

Q: What does being a member of SIAM mean to you?

A: Although I only joined SIAM recently, I have participated to SIAM for a long time. I am mostly interested in SIAM Journal on Numerical Analysis and in SIAM’s books. 


Hedy Attouch

Hedy Attouch is one of the 2021 recipients of the George B. Dantzig Prize. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The prize is awarded to Hedy Attouch for his fundamental contributions to modern variational analysis and nonsmooth optimization, including new notions of variational convergence, the introduction of novel topologies for the study of quantitative stability of variational systems, and their application in algorithm design and analysis, dynamical systems and partial differential equations.

Hedy Attouch

The George B. Dantzig Prize is awarded ever three years to one or more individuals for original research which by its originality, breadth, and depth is having a major impact on the field of mathematical optimization. The Mathematical Optimization Society (MOS) administers the prize and it is awarded jointly by MOS and SIAM.

After finishing his studies at the École Normale Supérieure (Cachan) and accomplishing the aggregation of Mathematics in 1970, Hedy Attouch was Assistant Professor at the University Paris-Sud, Orsay, from 1971 to 1982. In 1976 he accomplished his Ph.D. (Thése de doctorat d'état en Mathématiques) at the University Paris VI under the supervision of H. Brezis with the dissertation entitled “PDE's associated to subdifferential operators".

Beginning with 1983, he was Professor of Mathematics at the University of Perpignan, from where he moved to the University Montpellier in 1988, where he was director of the Convex Analysis Laboratory and ACSIOM, and received the distinction of Professor, exceptional class. During his studies, he obtained a six-month grant for a CNRS-NSF post-doctoral position, which marked the departure of his collaboration with R. Wets. At the same period the post-doctoral visiting positions that he obtained at the University of Roma (with U. Mosco) and at the Scuola Normale Superiore di Pisa (with E. De Giorgi) marked the departure of his collaboration with the Italian school of variational analysis.

Attouch has published more than 140 articles in international journals of pure and applied mathematics, as well as 7 books and monographs. As reported by Google Scholar, his work has been cited over 11,000 times, and his h-index is 49. He supervised 26 Ph.D. thesis or Habilitation thesis. All have become full professors or associate professors in French or international universities. Attouch serves as editor in several international journal of mathematics, including SIAM Journal on Optimization. Attouch was responsible for several international research programs including ANR (French), AFORS (US Air Force), and ECOS-Sud (Chile).

Q: Why are you excited to receive the award of the George B. Dantzig Prize?

A: The power of mathematics to model, simulate and act on the real world has always been a subject of fascination for me. In this regard, George B. Dantzig is a model for me. Indirectly, I have always been impressed by the immense respect he enjoys with colleagues and friends who have known him closely, such as R. Wets, of whom he was the thesis director, or M. Balinski, who was the founding editor-in-chief of the journal Mathematical Programming. I am very honored to see my name in the company of the prestigious mathematicians who have already obtained the George B. Dantzig Prize.

Q. Could you tell us a bit about the research that won you the prize?

A: As a mathematician working at the interface between theoretical and applied mathematics, throughout my career I have been aimed at emphasizing the universality of mathematical concepts used in my research and how the different areas of mathematics interact with each other and with the real world through rich exchanges. The selection committee stated that they wish to recognize “the fundamental contributions of H. Attouch to modern variational analysis and nonsmooth optimization, including new notions of variational convergence, the introduction of novel topologies for the study of quantitative stability of variational systems, and their application in algorithm design and analysis, dynamical systems and partial differential equations". With R. Wets we have developed epigraphical analysis as a new branch of mathematical analysis. The epi-convergence of sequences of functions and the corresponding notion of graph convergence for operators is at the core of this theory, with many applications to approximation, perturbation (qualitative and quantitative) of optimization problems, and to partial differential equations. Regarding numerical algorithms in optimization, the main originality of my work consists in using the close link between continuous dynamic systems and algorithms (obtained by explicit/implicit temporal discretization), which provides valuable mechanical intuition, and which makes it possible to use powerful results of various mathematical theories. For example, the Kurdyka-Lojasiewicz inequality for semi-algebraic functions and more generally tame functions (which comes under real algebraic geometry) allowed to provide the first general results of global convergence (convergence of the sequence of iterates, and rate of convergence) for first-order methods in a non-convex and non-smooth framework. The damped inertial dynamics from mechanics and control provide a natural framework for understanding and extend the Nesterov accelerated gradient method. Time rescaling and Hessian-driven damping are key tools to speed up these methods and dampen oscillations, respectively.

Q: What does your work mean to the public?

A: During my career, I have been confronted with fascinating problems coming from various fields, and where the mathematical approach provides a powerful tool. It was often necessary to develop new theories to grasp the complexity of the problem studied. For example, the theory of variational convergences (epi-convergence, Gamma convergence) made it possible to understand the mechanical behavior of heterogenous composite materials: the challenge then being to go to the limit in the variational formulation of the equations of physics, when the size of the microstructure, or of the heterogeneities tends towards zero, to obtain at the limit a homogeneous medium which accounts for the macroscopic behavior. In decision sciences, economics, sociology, the notions of cost to change and routine correspond to proximal algorithms whose crucial importance has been put forward to ensure the convergence of many optimization algorithms. In this case, the human sciences and algorithmics respond to and enrich each other. Big Data processing requires the development of algorithms using the most elementary possible operations, such as first order methods (gradient, or sub-differential evaluation). This apparent paradox between the complexity of the problems and the simplicity of the algorithmic tools to solve them, requires understanding the basic mechanisms of the convergence of algorithms, where real algebraic geometry and differential geometry play an essential role. The other pillar is the method of spitting, decomposition, of which George G. Dantzig was the precursor. 

Q: What does being a member of SIAM mean to you?

A: SIAM plays a central role in my research activity. I have published several of my favorite papers in SIAM Journal on Optimization (9 papers), SIAM Journal on Control and Optimization (2 papers), and SIAM Journal on Mathematical Analysis (1 paper). I have been associate editor at SIAM Journal on Optimization since 2015. I published the following book with SIAM: H. Attouch, G. Buttazzo, G. Michaille, Variational analysis in Sobolev and BV spaces, Applications to PDE's and Optimization, MPS-SIAM Series on Optimization, 2006, 634 pages. Second edition published in 2015, 793 pages, which has met with remarkable success, already with 760 citations. Another book is in preparation in the same series: H. Attouch, J. Peypouquet, Dynamics and algorithms for continuous optimization. Convergence and Complexity Analysis, MPS-SIAM Series on Optimization, 700 pages. SIAM meetings are also essential for meeting colleagues from around the world and promoting the best of mathematical sciences.


Michel Goemans

Michel Goemans is one of the 2021 recipients of the George B. Dantzig Prize. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The prize is awarded to Goemans for his outstanding contributions to the field of combinatorial optimization; most notably, the initiation of new research directions, introduction of novel and deep techniques, and ingenious use of sampling, rounding, and geometric ideas to significantly advance several fields, including the pioneering use of semi-definite programming for the design of approximation algorithms.

The George B. Dantzig Prize is awarded ever three years to one or more individuals for original research which by its originality, breadth, and depth is having a major impact on the field of mathematical optimization. The Mathematical Optimization Society (MOS) administers the prize and it is awarded jointly by MOS and SIAM.

Michel Goemans

A native of Belgium, Dr. Goemans is a Professor of Mathematics and the Head of the Department of Mathematics at MIT. He has held the Leighton Family Professorship at MIT, an Adjunct Professorship at the Universiy of Waterloo, a Professorship at the UC Louvain, and a Visiting Professorship at Kyoto University. He received his undergraduate degree from UC Louvain in 1987 and his Ph.D. from MIT in 1990. He also holds a Doctor Honoris Causa from UC Louvain. In addition to being a SIAM Fellow, he is also an AMS, ACM, Guggenheim, and Sloan Foundation Fellow. His research in the area of combinatorial optimization has been rewarded twice by the SIAG/Optimization Prize, the 2012 Farkas prize, the 2000 Fulkerson prize and an invited lecture at the International Congress of Mathematicians (1998).

Q: Why are you excited to receive the award of the George B. Dantzig Prize? 

A: This is a tremendous honor to receive the 2021 George B. Dantzig prize, and join a distinguished group of mathematical optimizers. George Dantzig not only is most well-known for the development of the simplex algorithm, but his work with Fulkerson and Johnson in the 50's on the traveling salesman problem was deeply influential in combinatorial optimization, and also in my own research. I am proud to be the recipient of a prize named after him. 

Q: Could you tell us a bit about the research that won you the prize?

A: Following on the footsteps of Dantzig, Fulkerson, and Johnson, I have been interested in how tightly one can approximate hard combinatorial optimization problems using efficiently computable optimization problems. Much of my work has shown how to derive provably good solutions from the solution of polynomially solvable relaxation of the problem being considered, and this has lead to the best approximation algorithms for a variety of combinatorial optimization problems, for problems such as the unsplittable flow. For example, one of my signature results together with a former Ph.D. student David Willaimson (now a Professor at Cornell U.) was on the MAXCUT problem, the problem of partitioning the vertices of a graph into two parts so as to maximize the number of edges cut. For this problem, we showed that a cut of value at least 0.87856 times the optimum can be obtained by relaxing the problem into a semidefinite program (where one optimizes over the cone of positive semidefinite matrices intersected with affine constraints) and a simple random hyperplane technique.

Q: What does your work mean to the public?

A: Optimization problems arise everywhere in transportation, logistics, manufacturing, chip design, scheduling, you name it, and some of the techniques I have developed are used in practice or have influenced the way a variety of problems are solved. For example, a load balancing algorithm I have designed for delivering content over the internet has been executed hundreds of millions of times in the last 20 years.

Q: What does being a member of SIAM mean to you?

A: I am proud to be a SIAM fellow, and also that my work has also been recognized by two SIAG/Optimization prizes. I enjoy the fact that SIAM covers the whole spectrum from fundamental (applied) mathematics to industrial applications, and this is fertile for new developments. I have been on the editorial board of both the SIAM Journal on Discrete Math, and the SIAM Journal on Optimization, and in addition to these two, I have often published in SIAM Journal on Computing, and also at the ACM-SIAM Symposium on Algorithms (SODA), one of my favorite conferences.


Assefaw H. Gebremedhin, Fredrik Manne, and Alex Pothen

Assefaw H. Gebremedhin, Fredrik Manne, and Alex Pothen are the 2021 recipients of the George Pólya Prize in Applied Combinatorics. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The prize is awarded to Gebremedhin, Manne, and Pothen for efficient graph coloring algorithms and codes with applications to Jacobian and Hessian matrix computations. 

Assefaw H. Gebremedhin

The George Pólya Prize in Combinatorics, originally established in 1969, is awarded every four years for a notable application of combinatorial theory. The prize is broadly intended to recognize specific work. The award may occasionally be made for cumulative work, but such awards should be rare.

Assefaw H. Gebremedhin is an associate professor in the School of Electrical Engineering and Computer Science at Washington State University (WSU). He received his undergraduate degree in electrical engineering from Addis Ababa University, Ethiopia, and his M.S. and Ph.D. degrees in computer science from the University of Bergen, Norway. He has been a member of SIAM since 2001. He grew up both as a researcher and a person within the combinatorial scientific computing community and contributed to its formation and evolution. He currently leads the Scalable Algorithms for Data Science Lab at WSU. He is a recipient of the NSF CAREER Award.    

Fredrik Manne is a professor of informatics at The University of Bergen, Norway. He received his Ph.D. from the same institution in 1993. His main line of work has been centered around developing parallel algorithms for problems motivated from combinatorial scientific computing. He is currently head of education at the Department of Informatics and has won several awards for teaching and pedagogic work.

Alex Pothen is a professor of computer science at Purdue University. He received his undergraduate degree from the Indian Institute of Technology, Delhi, where he was a National Science Talent Scholar, and his Ph.D. in Applied Mathematics from Cornell. He has been a SIAM member since 1984 and was designated as a SIAM Fellow in 2018. He helped found the combinatorial scientific computing community in the early 2000’s and served as the founding Chair of the SIAM Activity Group on Applied and Computational Discrete Algorithms (ACDA) during 2018-2020.

Fredrik Manne

Q: Why are you excited to receive the award of the George Pólya Prize in Applied Combinatorics?

A: The prize is in remembrance of George Pólya, one of the greatest mathematicians of the 20th century. To have our work recognized through this Prize and associated with his name is special indeed. Since this is the first time that the Prize is given for work in Applied Combinatorics, we are happy that this Prize communicates to the mathematics community that the design of graph algorithms for problems in scientific computing is beautiful, significant, and worthy of recognition.

Q: Could you tell us a bit about the research that won you the prize?

A: Graph coloring is a mathematical technique to divide a collection of objects into few groups, each group consisting of elements that do not depend on each other, so that a scarce resource can be used optimally. An example might be to group courses to be taught in a semester into time periods so that classrooms can be used effectively while making sure that any two courses scheduled for the same period do not have students enrolled in both of them. Our article describes efficient algorithms to solve several variant graph coloring problems, and then applies them to compute Jacobian and Hessian matrices. These derivative matrices enable scientists to solve nonlinear problems that could be modeled as optimization problems or differential equations. Our work provided a unifying framework for developing graph models for ten variant derivative matrix estimation problems. We identified graph data structures that enable the design of space- and time-efficient algorithms for these problems. We have provided a historical overview of the work in this area, and cited work on graph coloring done by several subcommunities in mathematics and computer science. We applied our work to solve the optimal power flow problem in electrical grids, and to model a simulated moving bed process in chromatographic separations in chemical engineering. We have developed a software library, ColPack, that implements the algorithms for graph coloring and matrix computation, and it is freely available on Github.

Q: What does your work mean to the public?

A: One of the most satisfying aspects of this work for us is seeing the hundreds of papers that have cited our work. We count more than fifty application areas in science, engineering, business, and industry that have cited our work, ranging from design of robots that assist individuals with impaired mobility to hydrodynamics of stars. A number of the leading software libraries for solving optimization problems, partial differential equations, control problems, process engineering, etc. have either incorporated our software or have implemented our algorithms to compute Jacobians and Hessians. 

Alex Pothen

Q: What does being a member of SIAM mean to you?

A: Assefaw H. Gebrmedhin: I have been a member of SIAM since 2001 when I first joined as a student. SIAM has been a wonderful community to me and has directly contributed to my professional development. I am a member of several of its Activity Groups, including the newly formed ACDA and the SIAGs on Supercomputing and Data Science. The SIAM Conferences and the unique “mini-symposia” they feature have been an excellent way for staying in touch with old friends and colleagues and connecting with new ones, and for exchanging ideas and recent work. I have had the privilege of publishing my work in several of its outstanding Journals that reach a broad scientific community internationally through its various platforms. I am looking forward to continuing being involved with SIAM and contributing to its high impact in research and education, especially in areas that intersect with computer science and applied mathematics.

Fredrik Manne: Throughout my academic career the SIAM meetings have always been the place to interact with friends and colleagues, to catch up on the latest research, and to present my own work. Together with the SIAM publications this has been an excellent way of staying involved in the academic community. With the recent addition of the SIAG on Applied and Computational Discrete Algorithms it is clear that SIAM will continue to strengthen and grow the connections between computer science and more applied fields.

Alex Pothen: I have been a member of SIAM since 1984, and for the past 37 years SIAM has been my professional home: I have enjoyed the community provided by several Activity Groups (SIAGs), participated in several SIAM conferences each year, and published in SIAM journals and proceedings. I have (or had) the privilege of serving on five SIAM journal and book editorial boards including SIAM Review and SIAM Books, and on several SIAM committees, including the one on Science Policy. With several colleagues, I had the privilege of birthing the SIAG on Applied and Computational Discrete Algorithms (ACDA) that will have its first conference in July 2021. I am looking forward to continuing involvement with SIAM and its members in the years ahead!

The authors collaborated on their answers to our questions.


Nicholas J. Higham

Nicholas J. Higham is the 2021 recipient of the George Pólya Prize for Mathematical Exposition. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The prize is awarded to Higham for the crisp clarity, elegance, and accessibility of his mathematical and popular exposition on a broad range of topics in applied mathematics.

The George Pólya Prize for Mathematical Exposition, established in 2013, is awarded every two years to an outstanding expositor of the mathematical sciences. The prize may be awarded for a specific work or for the cumulative impact of multiple expository works that communicate mathematics effectively. Following Pólya’s example, the nature of the work may range from popular accounts of mathematics and mathematical discovery to pedagogy to systematic organization of mathematical knowledge.

Nicholas J. Higham

Nick Higham is Royal Society Research Professor and Richardson Professor of Applied Mathematics in the Department of Mathematics at the University of Manchester. He received his Ph.D. in 1985 from the University of Manchester. He is a Fellow of the Royal Society, an ACM Fellow, a SIAM Fellow, and a Member of Academia Europaea. He was SIAM President from 2018-2019.

Much of his research is concerned with the accuracy and stability of numerical algorithms, and the second edition of his monograph on this topic was published by SIAM in 2002. His other books are Handbook of Writing for the Mathematical Sciences (SIAM, third edition, 2020), Functions of Matrices: Theory and Computation (SIAM, 2008), MATLAB Guide (with Des Higham, third edition, SIAM, 2017), and the 1000-page The Princeton Companion to Applied Mathematics (2015), of which he was editor. His current research interests include mixed precision numerical linear algebra algorithms.

Q: Why are you excited to receive the award of the George Pólya Prize for Mathematical Exposition?

A: The prize, which is awarded for expository work that communicates mathematics effectively, is named after George Pólya, the Hungarian mathematician who wrote the million-selling book How to Solve It, first published in 1945. Pólya was a brilliant researcher, teacher, and expositor of mathematics. It is an honor to receive this SIAM prize named after him, especially as most of my research and expository writing has been published with SIAM.

Q: Could you tell us a bit about the work that won you the prize?

A: My expository work includes my books; numerous articles for SIAM News, including twenty From The SIAM President columns; review articles; and my blog about applied mathematics at https://nhigham.com/blog/. Just over a year ago I started a "What Is" series of articles on the blog, in which I give brief descriptions of important concepts in numerical analysis and related areas, with a focus on topics that arise in my research. These seem to have struck a chord and have attracted a readership outside the usual applied mathematics community.

Q:  What does your work mean to the public?

A: One of the problems I work on that is easy to explain to a general audience concerns empirically constructed covariance matrices or correlation matrices that either have missing elements or turn out not to be positive definite for various reasons. If these deficiencies in the matrix are not corrected then the practical consequences can range from incorrectly computed insurance premiums to portfolio investments based on apparently negative risks. I recently co-authored an article for the magazine of The Institute and Faculty of Actuaries describing research I've been involved in on correlation matrix completion.

Q:  What does being a member of SIAM mean to you?

A: I've been a SIAM member for 37 years, having joined as a student, and I am now a lifetime member. SIAM has always been my most important professional affiliation. I've been to numerous SIAM conferences, published papers and books with SIAM, and served on the Council and Board and in the SIAM leadership. It's hard to imagine life without SIAM!


Léon Bottou, Frank E. Curtis, and Jorge Nocedal

Léon Bottou, Frank E. Curtis, and Jorge Nocedal are the 2021 recipients of the Lagrange Prize in Continuous Optimization. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The Lagrange Prize in Continuous Optimization is awarded jointly to Léon Bottou, Frank Curtis, and Jorge Nocedal for their paper, "Optimization Methods for Large-Scale Machine Learning", SIAM Review 60(2), 2018, which provides a foundational and insightful review of optimization methods for large-scale machine learning, including a new perspective for the simultaneous consideration of noise reduction and ill-conditioning and the foundations and analysis of second-order stochastic optimization methods for machine-learning.

Léon Bottou

The Lagrange Prize in Continuous Optimization is awarded every three years for an outstanding contribution in the area of continuous optimization published in the six calendar years prior to the award year. The Mathematical Optimization Society (MOS) administers the prize and it is awarded jointly by MOS and SIAM.

The award is based primarily on the work's mathematical quality, significance, and originality. Clarity and excellence of the exposition and the value of the work in practical applications may be considered as secondary attributes. The extended period of six years reflects the fact that the value of fundamental work cannot always be immediately assessed.

Léon Bottou received the Diplôme d’Ingénieur de l’École Polytechnique (X84) in 1987, the Magistère de Mathématiques Fondamentales et Appliquées et d’Informatique from École Normale Superieure in 1988, and a Ph.D. in Computer Science from Université de Paris-Sud in 1991. His research career took him to AT&T Bell Laboratories, AT&T Labs Research, NEC Labs America, and Microsoft. He joined Facebook AI Research in 2015. The long term goal of Léon’s research is to understand how to build human-level intelligence. Although reaching this goal requires conceptual advances that cannot be anticipated at this point, it certainly entails clarifying how to learn and how to reason. Leon Bottou best known contributions are his work on deep neural networks in the 90s, his work on large scale learning and optimization, and possibly his more recent work on causal inference in learning systems. Léon is also known for the DjVu document compression technology.

Frank E. Curtis is an Associate Professor in the Department of Industrial and Systems Engineering at Lehigh University. He received his Ph.D. from Northwestern University in 2007, then spent two years as a postdoctoral researcher at the Courant Institute of Mathematical Sciences at New York University prior to joining Lehigh in 2009. His research focuses on the design, analysis, and implementation of algorithms for (nonconvex and nonsmooth) continuous optimization. He is a recipient of a DOE Early Career Award and the ICS Prize from the INFORMS Computing Society. 

Frank E. Curtis

Jorge Nocedal is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University. He obtained his B.S. degree from UNAM, Mexico, and a Ph.D. from Rice University. His research is in optimization, both deterministic and stochastic, and with emphasis on large-scale problems. He served as editor-in-chief of the SIAM Journal on Optimization, is a SIAM Fellow, was awarded the 2012 George B. Dantzig Prize as well as the 2017 Von Neumann Theory Prize, for contributions to theory and algorithms of nonlinear optimization. He is a member of the U.S. National Academy of Engineering.

Q: Why are you excited to receive the award of the Lagrange Prize in Continuous Optimization?

A: We are honored to receive this prize and extremely grateful to SIAM, the prize committee, and our colleagues who inspire and support our work. Optimization for machine learning remains an important and influential field, and we hope that our work can be used as a valuable resource for researchers in the field and as a launching point for young scholars who are interested in the area.

Q: Could you tell us a bit about the research that won you the prize?


A: We are being awarded the prize for our paper entitled "Optimization Methods for Large-Scale Machine Learning," published in SIAM Review. Mathematical optimization is a pillar of machine learning. In particular, our paper focuses on the optimization problems arising in large-scale supervised learning, which involves the numerical computation of parameters for a system designed to make decisions about yet unseen data. We discuss the context of what makes such problems challenging, reflect on what algorithms have been the most successful to date, and summarize opportunities that exist for improving upon these algorithms.

Jorge Nocedal

Q: What does your work mean to the public?

A: Machine learning and the automated systems that have been created with it have become ubiquitous in modern society. It is critical for the creators and users of machine learning tools to understand the algorithms that underlie the training of automated systems to understand both their effectiveness and their potential shortcomings.

Q: What does being a member of SIAM mean to you?

A: SIAM offers plentiful avenues for connecting with researchers and scholars throughout all areas of applied mathematics. It is a society that cares deeply about its members and their work, and helps to support and stimulate future research endeavors.

The authors collaborated on their answers to our questions.


Thomas J.R. Hughes

Thomas J.R. Hughes is the 2021 recipient of the Ralph E. Kleinman Prize. The award will be presented virtually at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. The prize is awarded to Dr. Hughes for his influential and profound contributions to computational science and engineering and their impact on engineering design and simulation, while creating entirely new fields of mathematical research.

The Ralph E. Kleinman Prize is awarded every two years to one individual for outstanding research or other contributions that bridge the gap between mathematics and applications. Work that uses high-level mathematics and/or invents new mathematical tools to solve applied problems from engineering, science, and technology is particularly appropriate.

Thomas J.R. Hughes

Dr. Hughes is the leading researcher in computer aided engineering and its integration with computer aided design. He has made numerous seminal contributions to the analysis of structural, solid, fluid, and biomedical systems, and the seamless integration of analysis methodologies with design model representations. The fruits of his work have been incorporated in industrial and commercial computer programs that are used worldwide every day to design and analyze airplanes, automobiles, high-speed trains, consumer products, industrial processes, and other applications, and to non-invasively diagnose disease and guide medical interventions.  He has originated new fields of computational engineering and mathematics research and continues to lead their development.  He has been repeatedly recognized as a Highly Cited Researcher by Web of Science, and his published works have garnered over 120,000 citations with h-index of 154 in Google Scholar.

Dr. Hughes holds B.E. and M.E. degrees in Mechanical Engineering from Pratt Institute and an M.S. in Mathematics and Ph.D. in Engineering Science from the University of California at Berkeley. He taught at Berkeley, Caltech, and Stanford before joining the University of Texas at Austin.  At Stanford he served as Chairman of the Division of Applied Mechanics, Chairman of the Department of Mechanical Engineering, Chairman of the Division of Mechanics and Computation, and held the Mary and Gordon Crary Family Chair of Engineering.

He is co-editor of the international journal Computer Methods in Applied Mechanics and Engineering, a founder and past President of USACM and IACM, past Chairman of the Applied Mechanics Division of ASME, and past Chairman of the U.S. National Committee on Theoretical and Applied Mechanics (USNC/TAM).

Q: Why are you excited to receive the Ralph E. Kleinman Prize?

A: I am very excited to receive the Ralph E. Kleinman Prize because a SIAM award is a great honor and this one, in particular, recognizes work that bridges the gap between mathematics and applications, and I think it is fair to say that is what my work is all about. When I read the intent of the Prize, it seems to fit the approach I have taken in my work. Early on in my career I was advised to become either an engineer or a mathematician, as if they are mutually exclusive endeavors, because not focusing on one would hamper my career development. I decided to not take that advice and do what I liked, which is a combination of both. I think the Ralph E. Kleinman Prize vindicates my decision.

Q: Could you tell us a bit about the research that won you the prize?

A: The selection committee recognized me for “influential and profound contributions to computational science and engineering and their impact on engineering design and simulation, while creating entirely new fields of mathematical research.” That is flattering and quite broad. It describes at a high level just about everything I have ever done. I am interested in making practical contributions that are utilized in the world of engineering. The approach I take to do this is based on mechanics, mathematics and computation. My roots and early experiences in engineering design and analysis have given me insights into what is useable in engineering and what is not. That provides boundary conditions for my work, but ensures, that when my research is successful, it will have impact. 

Q: What does your work mean to the public?

A: A lot of my work on finite element methods and related numerical methods has been implemented in industrial and commercial codes used around the world to design and analyze airplanes, automobiles, trains, consumer products, industrial processes, and to non-invasively diagnose disease and guide medical interventions. I think, unbeknownst to the public, I have influenced many things that people encounter every day of their lives.

Q: What does being a member of SIAM mean to you?

A: It means a great deal to me. SIAM is an organization that spans my interests in numerical analysis, applied mathematics, and scientific computing.  It is an important and powerful voice advocating, nationally and internationally, for the type of work I, and people like me, do. It also provides a spectrum of highly regarded archival research journals, publishes books, and organizes conferences. All these activities comprise a significant force in the world of mathematical sciences.


Deborah Frank Lockhart

Deborah Frank Lockhart is the 2021 recipient of the SIAM Prize for Distinguished Service to the Profession. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021.

The prize is awarded to Lockhart in recognition of her far-reaching contributions to supporting and advancing applied mathematics and computational science in numerous venues, especially their central role in all of science and engineering. Her dedication and tireless efforts will have a lasting impact on our profession.

Deborah Frank Lockhart

The SIAM Major Awards Committee awards the prize every year to an applied mathematician who has made distinguished contributions to the furtherance of applied mathematics on the national or international level.

Lockhart received her B.A. in Mathematics from New York University and her M.S. and Ph.D. in Mathematics from Rensselaer Polytechnic Institute. She was on the faculty of the State University of New York, College at Geneseo, and Michigan Technological University prior to joining the National Science Foundation in 1988. During her career at NSF, she served as a program director in the Division of Mathematical Sciences (DMS) Infrastructure Program (1988-1993) and Applied Mathematics Program (1993-2004), as DMS Deputy Division Director from 2004 to 2011, as Deputy Division Director in the Division of Information and Intelligent Systems (IIS) from 2011 to 2016, and as Deputy Assistant Director for Mathematical and Physical Sciences from 2016 to 2019.

In August 2019, she retired from full-time government service. At various times she served as acting Division Director for DMS, IIS, the Division of Computing and Communication Foundations, and the Division of Undergraduate Education. She has served on committees for SIAM and MAA, and more recently has served as the Chair of the Mathematics Section of AAAS, and the Section representative to the AAAS-wide Council. She is a Fellow of the AMS and AAAS and has received the Distinguished Service Award and Meritorious Service Award from NSF.

Q: Why are you excited to receive the SIAM Prize for Distinguished Service to the Profession?

A: It is a tremendous honor to be awarded the 2021 SIAM Prize for Distinguished Service to the Profession. As a proud member of SIAM for over 40 years, it is wonderful to have my contributions to the profession recognized by my peers.

Q: Could you tell us a bit about the accomplishments that won you the prize?

A: Most of my professional life has been spent in various roles at the National Science Foundation. For many years I was a program director for the Applied Mathematics Program in the Division of Mathematical Sciences (DMS), which supports the research efforts of many mathematical scientists. My coordination of the NSF Mathematical Sciences Priority Area in the early 2000’s eventually resulted in providing many new opportunities to mathematicians for their work, including collaborations with colleagues in other disciplines, and in the establishment of new mathematical sciences institutes. As a Deputy Division Director in both the Division of Mathematical Sciences and the Division of Information and Intelligent Systems, I provided guidance for new programs and efforts in mathematics and computer science, many of which had strong connections with applications. As Deputy Assistant Director for Mathematical and Physical Sciences, I supported the involvement of mathematical and physical sciences in broader NSF activities and programs. These efforts would not have succeeded without my dedicated and innovative supervisors and colleagues. A continuing theme in my NSF career has been my strong support for programs supporting the development of new generations of mathematical scientists, particularly members of groups under-represented in the discipline.

Q: What does your work and service mean to the public?

A: I believe that my efforts have contributed to the mathematical sciences and their connections to other sciences and applications and to raising the awareness of the importance of the mathematical sciences broadly to technology and society.

Q: What does being a SIAM member mean to you?

A: Over the years, I have attended many SIAM Annual Meetings and Conferences. These have reinforced my strong connection to the community and introduced me to new and exciting mathematical ideas and emerging applications, as well as to participants from all over the world. I have found the SIAM community to be welcoming to participants from a wide variety of scientific backgrounds, thus providing a rich and diverse environment for interactions and sharing of ideas. SIAM’s publications are of the highest quality and its educational programs are innovative.


Karl Kunisch

Karl Kunisch is the 2021 recipient of the W. T. and Idalia Reid Prize. The award will be presented virtually at the SIAM Annual Meeting (AN21), to be held in a virtual format July 19 – 23, 2021. Kunisch will present a lecture titled “Solution Concepts for Optimal Feedback Control of Nonlinear Partial Differential Equations” on Wednesday July 21 at 3:30 p.m. Eastern Time. The prize is awarded to Kunisch for his fundamental and lasting theoretical, numerical, and computational contributions to nearly all aspects of PDE control theory, infinite dimensional optimization, and applications to complex systems.

The W. T. and Idalia Reid Prize is awarded annually to one individual for research in, or other contributions to, the broadly defined areas of differential equations and control theory.

Karl Kunisch

Kunisch is a professor at the department of mathematics at the University of Graz, and Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. He received his Ph.D. and Habiliation at the Technical University of Graz in 1978 and 1980. His research interests include optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, currently focusing on topics in the life sciences.

Kunisch spent three years at the Lefschetz Center for Dynamical Systems at Brown University, USA, held visiting positions at INRIA Rocquencourt and the Universite Paris Dauphine, and was a consultant at ICASE, NASA Langley, USA. Before joining the faculty at the University in Graz he was professor of numerical mathematics at the Technical University of Berlin.

Kunisch is also the author of two monographs and more than 340 papers. He is editor of numerous journals, including SIAM Journal on Optimization and Optimal Control, and SIAM Journal on Numerical Analysis.

Q: Why are you excited to receive the award of the W. T. and Idalia Reid Prize?

A: It’s a prestigious award, and I feel proud and humbled when I look at the list of colleagues who I join as a recipient of the W. T. and Idalia Reid Prize. I cannot stress enough that over the years I had the enormous fortune of working with extraordinary colleagues, postdocs, and docs. I see this as a recognition of their work as well.

Q: Could you tell us a bit about the research that won you the prize?

A: Likely the prize committee would know better than myself. Over the years I had been engaged on a multitude of aspects advancing the theoretical understanding and the practical solution processes related to control, estimation, and optimization with partial differential equations as constraints. This includes the linear quadratic regulator problem, semi-smooth Newton methods, regularization techniques involving non-smooth filters, and more recently, the development of concepts to reduce the burden of the curse of dimensionality in solving Hamilton Jacobi Bellman equations for optimal feedback control.

Q: What does your work mean to the public?

A: My work on the foundations of mathematics allowed me to acquire techniques which were instrumental for contributing to problems on the interface between mathematics and selected topics in medicine, including the modelling of the human heart, and to magnetic resonance imaging techniques, a medical imaging modality, which we all get in contact with.  

Q: What does being a SIAM member mean to you?

A: SIAM in general, and SIAM News in particular, addresses immanent and pressing issues of the evolution of applied mathematics within science and society early along and in a frank spirit. In this respect SIAM is not paralleled by any other mathematical society worldwide. It provides a unique platform for ‘mathematics in practice’ and its theoretical foundations.


Yuanzhao Zhang 

Yuanzhao Zhang is one of the 2021 recipients of the SIAM Student Paper Prize. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. Zhang received the award for their SIAM Review article "Symmetry-Independent Stability Analysis of Synchronization Patterns" and will present the article on July 23, 2021 at 3:30 p.m. Eastern Time during AN21.

The SIAM Student Paper Prize is awarded annually to the student author(s) of the most outstanding paper(s) accepted by SIAM Journals within the three years preceding the nomination deadline. The award is based solely on the merit and content of the student's contribution to the submitted paper. Up to three awards are made every year.

Yuanzhao Zhang

Zhang’s research interest lies at the interface between networks and nonlinear dynamics, mostly inspired by a fascination of collective behaviors that emerge from decentralized interactions. He is currently a Schmidt Science Fellow working with Steven Strogatz at Cornell’s Center for Applied Mathematics. He got his Ph.D. in Physics in 2020 from Northwestern University, advised by Adilson Motter.

Q: Why are you excited to receive the SIAM Student Paper Prize?

A: I am deeply honored to receive the SIAM Student Paper Prize; it means a lot to me as an early-career researcher. The paper being award this prize holds a special place in my heart (I am really proud of it!), and it is very encouraging to know that the broad SIAM community appreciates it as well.

Q: Could you tell us a bit about the research that won you the prize?

A: Many biological and technological networks show intricate synchronization patterns, where several internally coherent but mutually independent clusters coexist. Maintaining the desired dynamical patterns is critical to the function of those networked systems. For instance, long-range synchronization in the theta frequency band between the prefrontal cortex and the temporal cortex has been shown to improve working memory in older adults. Which synchronization patterns we can ultimately observe are determined by their stabilities. It is widely believed that utilizing symmetries in the network structure is crucial to the characterization of a pattern’s stability. However, symmetry-based methods are limited in the types of synchronization patterns they can directly treat and can be computationally expensive. In our SIAM Review paper, we found that when symmetry information is discarded, the problem becomes easier, not harder. By forgoing symmetry, we not only can treat all synchronization patterns under a unified framework but also develop algorithms that are orders of magnitude faster than symmetry-based ones.

Q: What does your work mean to the public?

A: Synchronization is everywhere. Sometimes, it is extremely visual, such as the breathtaking view of fireflies flashing synchronously in a balmy summer night; other times, it can be invisible to most of us yet extremely important, such as the synchronization of power generators that underlies the operation of our electric grids. The stability of synchronization is a fundamental question with important ramifications for the function of many of those networked systems. I hope that the framework developed in my work will advance our understanding of this fundamental question.

Q: What does being a member of SIAM mean to you?

A: I am an applied mathematician at heart, and SIAM provides a diverse community of excellent mathematicians with whom I share a common language. I have had only positive experiences with SIAM journals and conferences, and I look forward to both contributing to and learning from the SIAM community in the coming years.


Yingjie Bi

Yingjie Bi is one of the 2021 recipients of the SIAM Student Paper Prize. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. Bi received the award for his SIAM Journal of Optimization paper “Duality gap estimation via a refined Shapley–Folkman lemma" and will present the paper on July 23, 2021 at 3:30 p.m. Eastern Time during AN21.

The SIAM Student Paper Prize is awarded annually to the student author(s) of the most outstanding paper(s) accepted by SIAM journals within the three years preceding the nomination deadline. The award is based solely on the merit and content of the student's contribution to the submitted paper. Up to three awards are made every year.

Yingjie Bi

Yingjie Bi is currently a postdoctoral scholar in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. He received the Ph.D. degree in Electrical and Computer Engineering from Cornell University advised by Professor Kevin Tang in 2020.

Q: Why are you excited to receive the SIAM Student Paper Prize?

A: It is a great honor for me to receive this prize. I feel very encouraged for my work to be recognized by the community.

Q: Could you tell us a bit about the research that won you the prize?

A: My work focuses on nonconvex optimization problems with separable objectives and constraints. It is of particular interest to estimate the duality gap for such problems, mainly because of its relation to the dual-based approximation algorithms. This problem has a long history with the first bound being proposed in the 1970s based on the Shapley--Folkman lemma. In my paper, by refining the original Shapley--Folkman lemma and introducing a finer characterization for the nonconvexity of a function, we present a new estimation for the duality gap, which is qualitatively tighter than the existing ones, and demonstrate how the new result can be applied in practical problems.

Q: What does your work mean to the public?

A: Nonconvexities are prevalent in many areas such as machine learning, power systems and computer networks. My research can potentially provide a deeper insight for nonconvex problems from these fields, which is valuable for the design and analysis of better algorithms for solving these important problems.

Q: What does being a member of SIAM mean to you?

A: It is a great pleasure for me to participate in SIAM conferences and publish in SIAM Journals. I appreciate the opportunities provided by the SIAM community to help me know more about frontier research and facilitate collaboration with different people.


Michelle Feng

Michelle Feng is one of the 2021 recipients of the SIAM Student Paper Prize. The award will be presented at the SIAM Annual Meeting (AN21) to be held in a virtual format July 19 – 23, 2021. Feng received the award for her SIAM Review article "Persistent Homology of Geospatial Data: A Case Study with Voting" and will present the paper on July 23, 2021 at 3:30 p.m. Eastern Time during AN21.

The SIAM Student Paper Prize is awarded annually to the student author(s) of the most outstanding paper(s) accepted by SIAM journals within the three years preceding the nomination deadline. The award is based solely on the merit and content of the student's contribution to the submitted paper. Up to three awards are made every year. 

Michelle Feng

Michelle Feng is a postdoctoral researcher at Caltech in the Computing and Mathematical Sciences department. Feng’s research lies at the intersection of applied algebraic topology and computational social science. More specifically, she focuses on questions about the "shape" of human society - how do humans organize themselves in space, and how does that organization affect the way that our societies look? Outside of her research, she is passionate about social justice, modern literature, and food.

Q: Why are you excited to receive the SIAM Student Paper Prize?

A: I'm so thrilled that people are reading and appreciating our work! There are so many fascinating social questions which touch on our conceptions of what space is and how it functions, and I am personally very excited about exploring how to apply our mathematical notions of space to these questions. I'm honored that others are finding the work we're doing in this area worthwhile, and hope to continue seeing more and more researchers working in this area.


Q: Could you tell us a bit about the research that won you the prize?

A: The paper that won me this prize was focused on applying techniques from persistent homology (PH) to voting data. PH is a computational tool that allows us to study the topological structure of data at a variety of scales. Our research focused on studying how different conceptions of "scale" and different ways of organizing the data could answer slightly different questions about the existence of "voting islands" (that is, regions whose voting preferences differ from their neighbors). By putting the data together in different ways (using different topological constructions), we can compute different persistent homologies that are more or less effective at finding these voting islands, and that can detect different attributes of the voting islands (for example, geographic size vs. strength of voting preference).


Q: What does your work mean to the public?

A: One of our primary responsibilities as researchers is making our work accessible to the public so that they can both understand and buy into our work. As a researcher who works on questions that are intimately connected to the functions (and often failures) of our society, it is vital not to lose sight of the people whose lives underpin my research. People should have agency over how they are being studied, and we can only provide them with that agency by building bridges to the public.

Q: What does being a member of SIAM mean to you?

A: Math is a social pursuit - as mathematicians, we are constantly striving for common understanding, whether it be of new mathematical concepts, techniques, or applications. Community is tremendously important to this pursuit, and being connected to other mathematicians helps us learn from each other and helps us set community values. I'm very appreciative of the work SIAM does to provide community for applied mathematicians.

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