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Alfredo Noel Iusem graduated as Licenciado en Matemática at Universidad de Buenos Aires in 1971, as M.Sc. in Operations Research at Stanford University in 1979, and as PhD in Operations Research at Stanford University in 1981. He was a researcher at Instituto de Matemática Pura e Aplicada (IMPA) in Rio de Janeiro from 10/01/1981 to 09/05/2023. Currently, he is Full Professor at the School of Applied Mathematics (EMAp) of the Fundação Getulio Vargas (FGV) in Rio de Janeiro. During his 42 years at IMPA, he was Scientific Information Coordinator, Scientific Activities Coordinator coordinator of the MS Program on Mathematical Methods in Finance, member of the Scientific and Technical Council, member of the Administration Board, and director of the Optimization Seminar since its inception in 1992. Outside IMPA, he was member and later on coordinator of the Mathematics and Statistics Committee of the National Council of Scientific and Technological Development (CAMA/CNPq) and chair of the Steering Committee of the Working Group on Generalized Convexity and Monotonicity. He supervised 16 PhD students at IMPA and has published three books and 164 scientific papers in peer-reviewed journals. He has been associate editor of Journal of Optimization Theory and Applications, Set-Valued and Variational Analysis, Numerical Functional Analysis and Optimization and Journal of Nonlinear and Variational Analysis. He is Member of the Brazilian Order of Scientific Merit, member of the Brazilian Academy of Sciences (ABC), member of the Developing World Academy of Sciences (TWAS), and Fellow of the Society of Industrial and Applied Mathematics (SIAM).

Donald Goldfarb is the Avanessians Professor in the IEOR Department at Columbia University. He is internationally recognized for the development and analysis of efficient and practical algorithms for solving various classes of optimization problems, including the BFGS quasi-Newton method for unconstrained optimization, steepest-edge simplex algorithms for linear programming, and the Goldfarb-Idnani algorithm for convex quadratic programming. Don has also developed highly cited methods for image de-noising, compressed sensing, matrix rank minimization, and robust portfolio selection. In addition, he has developed simplex and combinatorial algorithms for network flow problems, interior-point methods for linear, quadratic and conic programming, and alternating linearization methods for sums of convex functions. He is a Member of the National Academy of Engineering, a recipient of the INFORMS John Von Neumann Theory Prize for Fundamental, Sustained Contributions to Theory in Operations Research and the Management Sciences, the Khachiyan Prize for Life-time Accomplishments in Optimization, and 1995 Prize for Research Excellence in the Interface between Operations Research and Computer Science. He is a SIAM Fellow, and was cited in 2014 by Thomson Reuters as one of World’s Most Influential Scientific Minds (specifically, among the top 1% most cited researchers in Mathematics between 2002 and 2012). Don has served as an editor-in-chief of Mathematical Programming, an editor of the SIAM Journal on Numerical Analysis and the SIAM Journal on Optimization, an associate editor of Mathematics of Computation, Operations Research and Mathematical Programming Computation, and is an editorial board member of Foundation and Trends in Optimization.

Philippe Toint is an emeritus professor of mathematics at the University of Namur, Belgium, specializing in numerical analysis, OR, and continuous optimization. His academic career has centered on the theory, computation, and software design of large-scale nonlinear optimization, including the co-development of the LANCELOT software package and contributions to trust-region and filter methods. Philippe has co-authored several books and about 200 papers, the vast majority of which were published in highly regarded journals. He was elected a SIAM Fellow in 2009, received the Beale-Orchard-Hays Prize in 1994, and the Lagrange Prize in Continuous Optimization in 2006. He also served as Chair of the Mathematical Optimization Society from 2010 to 2012.

Robert Vanderbei is a Professor in the Department of Operations Research and Financial Engineering at Princeton University. From 2005 to 2012, he was chair of the department. In addition, he holds courtesy appointments in the Departments of Mathematics, Astrophysics, Computer Science, and Mechanical and Aerospace Engineering. He is also a member of the Program in Applied and Computational Mathematics, is a founding member of the Bendheim Center for Finance, and a former Director of the Engineering and Management Systems Program. Beyond Princeton, he is a Fellow of the American Mathematical Society (AMS), the Society for Applied and Industrial Mathematics (SIAM) and the Institute for Operations Research and the Management Sciences (INFORMS). Within INFORMS, he has served as President of the Optimization Society and the Computing Society and is the 2017 winner of the Khachiyan Prize for his work in optimization. He also serves on the Advisory Board for the journal Mathematical Programming Computation. He has degrees in Chemistry (BS), Operations Research and Statistics (MS), and Applied Mathematics (MS, PhD). After receiving his PhD from Cornell (1981), he was an NSF postdoc at the Courant Institute for Mathematical Sciences (NYU) for one year, then a lecturer in the Mathematics Department at the University of Illinois-Urbana/Champaign for two years before joining Bell Labs in 1984. At Bell Labs he made fundamental contributions to the field of optimization and holds three patents for his inventions. In 1990, he left Bell Labs to join Princeton University where he has been since. In addition to hundreds of research papers, he has written four books: (i) a textbook entitled Linear Programming: Foundations and Extensions now in its fifth edition and published by Springer, (ii) Welcome To The Universe in 3D, an astronomy book written jointly with Neil deGrasse Tyson, J. Richard Gott and Michael Strauss and published by Princeton University Press, (iii) Sizing Up The Universe, an introductory astronomy book written jointly with J. Richard Gott and published by National Geographic, and (iv) Real and Convex Analysis, a textbook written jointly with Erhan Cinlar and published by Springer.

Katya Scheinberg is a Coca-Cola Foundation Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology. Prior to joining Georgia Tech, she held positions at Cornell and Lehigh Universities and at IBM T.J. Watson Research Center. She attended Moscow University for her undergraduate studies and received her PhD degree from Columbia University. Katya’s main research areas are related to developing practical algorithms (and their theoretical analysis) for various problems in continuous optimization, such as convex optimization, derivative-free optimization, machine learning, quadratic programming, etc. She is an INFORMS Fellow, a SIAM Fellow, and a recipient of the Lagrange Prize from SIAM and MOS, the Farkas Prize from the INFORMS Optimization Society, and the Outstanding Simulation Publication Award from the INFORMS Simulation Society. Katya currently serves as the Chair of the Mathematical Optimization Society and a co-editor of the Mathematical Programming journal. Her past service includes editor-in-chief of Mathematics of Operations Research and Chair of the SIAM Activity Group on Optimization.