SIAM Announces Class of 2020 Fellows

April 1, 2020

April 1, 2020 — Society for Industrial and Applied Mathematics (SIAM) is pleased to announce the 2020 Class of SIAM Fellows. These distinguished members were nominated for their exemplary research as well as outstanding service to the community. Through their contributions, SIAM Fellows help advance the fields of applied mathematics and computational science.

SIAM congratulates these 28 esteemed members of the community, listed below in alphabetical order:

Srinivas Aluru, Georgia Institute of Technology, is being recognized for contributions to sequential and parallel discrete algorithms in computational genomics, and leadership in data science and engineering.

Steven Ashby, Pacific Northwest National Laboratory, is being recognized for exemplary scientific leadership, outstanding service to SIAM, and important contributions to the field of computational science.

John P. Boyd, University of Michigan, is being recognized for contributions to geophysical fluid dynamics, Chebyshev polynomial and Fourier spectral methods, and nonlinear waves.

Richard Byrd, University of Colorado Boulder, is being recognized for fundamental contributions to the theory and algorithms for nonlinear optimization.

Ümit V. Çatalyürek, Georgia Institute of Technology, is being recognized for contributions to high-performance and parallel algorithms and to combinatorial scientific computing.

David Colton, University of Delaware, is being recognized for fundamental contributions to acoustic and electromagnetic scattering theory, and inverse problems in wave phenomena.

Jorge Cortes, University of California San Diego, is being recognized for contributions to the control and optimization of network systems.

George Cybenko, Dartmouth College, is being recognized for contributions to theory and algorithms in signal processing, artificial neural networks, and distributed computing systems.

Alicia Dickenstein, Universidad de Buenos Aires and CONICET, is being recognized for contributions to algebraic geometry and its applications within geometric modeling and in the study of biochemical reaction networks.

Yalchin Efendiev, Texas A&M University, is being recognized for fundamental contributions in developing innovative multiscale analysis and computations with applications to subsurface modeling and geosciences.

Martin J. Gander, Université de Genève, is being recognized for contributions to domain decomposition and time parallel methods.

David M. Gay, AMPL Optimization, Inc, is being recognized for fundamental contributions to optimization theory, modeling languages, and other software tools.

Laura Grigori, Inria, is being recognized for contributions to numerical linear algebra, including communication-avoiding algorithms.

George Haller, ETH Zürich, is being recognized for contributions to applied dynamical systems including the theory of Lagrangian coherent structures.

Alfred Hero, University of Michigan, is being recognized for contributions to the mathematical foundations of signal processing and data science.

Kristin E. Lauter, Microsoft Research, is being recognized for the development of practical cryptography and for leadership in the mathematical community.

Knut-Andreas Lie, SINTEF, is being recognized for contributions to the advancement of mathematics within the geosciences, multiscale and operator-splitting numerical methods, and open-source software tools.

Robert Lipton, Louisiana State University, is being recognized for contributions to the mathematics of materials and their translation to engineering applications.

Yi Ma, University of California Berkeley, is being recognized for contributions to the theory and algorithms for low-dimensional models and their applications in computer vision and image processing.

Kavita Ramanan, Brown University, is being recognized for contributions to constrained and reflected processes and stochastic networks.

Olaf Schenk, Università della Svizzera italiana, is being recognized for advances in the development of robust parallel sparse matrix algorithms and their effective use in large-scale science and engineering applications.

Jie Shen, Purdue University, is being recognized for fundamental contributions to spectral methods and applications, including pioneering algorithms in computational fluids dynamics and materials science.

Ronnie Sircar, Princeton University, is being recognized for contributions to financial mathematics and asymptotic methods for stochastic control and differential games.

Aravind Srinivasan, University of Mayland College Park, is being recognized for contributions to randomized algorithms and probablistic methods with applications to network and computational science.

Defeng Sun, Hong Kong Polytechnic University, is being recognized for contributions to algorithms and software for conic optimization, particularly matrix optimization.

Ruth J. Williams, University of California San Diego, is being recognized for contributions to the study of stochastic processes and their applications.

Barbara Wohlmuth, Technische Universität München, is being recognized for sustained seminal contributions to the field of numerical mathematics and for exemplary leadership and service to the computational science community.

Pingwen Zhang, Peking University, is being recognized for contributions in complex fluids modeling, multiscale analysis, and adaptive grid computation.

In addition to raising the visibility of applied mathematics and computational science, the SIAM Fellows Program helps makes SIAM members more competitive for awards and honors as well as leadership positions in the broader society.

Learn more about the SIAM Fellows Program.

About SIAM

Society for Industrial and Applied Mathematics (SIAM) is an international community of over 14,000 individual members. Almost 500 academic, manufacturing, research and development, service and consulting organizations, government, and military organizations worldwide are institutional members. SIAM was incorporated in 1952 as a nonprofit organization to convey useful mathematical knowledge to other professionals who could implement mathematical theory for practical, industrial, or scientific use. Since then, SIAM’s goals have remained the same.


Source: SIAM 

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