Subject to: Alfredo Iusem

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.

Aharon “Ronny” Ben-Tal is a Professor of OR and former head of the MINERVA Optimization Center at the Faculty of Industrial Engineering and Management at the Israel Institute of Technology (Technion). His interests lie in Continuous Optimization, particularly nonsmooth and large-scale problems, conic and robust optimization, as well as convex and nonsmooth analysis. He has published more than 130 papers in professional journals and co-authored three books. Ronny was Dean of the Faculty of Industrial Engineering and Management at the Technion and he also served as a council member of the Mathematical Programming Society. He was Area Editor Operations Research and Math. of OR, and member of the Editorial Board of SIAM J. Optimization, J. Convex Analysis, OR Letters, Mathematical Programming, Management Science, Math. Modeling and Numerical Analysis, EJOR, and Computational Management Science. He also served as Associate Editor for SIAM J. Optimization. He in an EURO Gold Medalist, an INFORMS and SIAM fellow, and a Distinguished Scientist by CWI in The Netherlands. Ronny is a recipient of the IBM Faculty Award, and was also awarded the Khachiyan Prize by the INFORMS Optimization Society for lifetime achievements in the area of Optimization. In addition, the OR Society of Israel awarded him the lifetime achievement Prize. As of April 2026, he has over 41,000 citations on Google Scholar.

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 PhD 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, and was awarded the 2012 George B. Dantzig Prize (MOS-SIAM), the 2017 Von Neumann Theory Prize (INFORMS), and the 2024 John Von Neumann Prize (SIAM) for contributions to theory and algorithms of nonlinear optimization. He is a member of the US National Academy of Engineering.

Alain Hertz graduated in mathematical engineering and obtained a Ph.D in operations research at the École Polytechnqiue Fédérale de Lausanne. Since 2001, he is professor at the department of mathematics and industrial engineering at Polytechnique Montréal, Canada. He is also member of the multi disciplinary GERAD research group that includes nearly sixty researchers and experts in operations research and discrete mathematics. He is the author of around 200 scientific publications and 4 detective novels. His main research domains are combinatorial optimization, graph theory, algorithmics, and the development of decision aid systems for scheduling and distribution problems. Alain serves on the editorial board of several scientific journals and he is also a member of the executive committee of the European Chapter on Combinatorial Optimization working group. He has organized several international conferences on graphs and optimization. He was president of the Swiss OR Society from 1996 to 2001, during which he dedicated himself to promoting the discipline worldwide.

Professor Terlaky is the director of the Quantum Computing and Optimization Laboratory (QCOL). He served as the Chair of the Department of Industrial and Systems Engineering, Lehigh University, 2008 – 2017. Prior to his appointment at Lehigh U., Prof. Terlaky has taught at Eötvös U., Budapest, Hungary; Delft University of Technology, Delft, Netherlands; McMaster U., ON, Canada. At McMaster he also served as the founding Director of the School of Computational Engineering and Science. Prof. Terlaky has published four books, edited over ten books and journal special issues and published over 220 research papers. Topics include theoretical and algorithmic foundations of operations research (e.g., invention of the criss-cross method), design and analysis of large classes of interior point methods, computational optimization, worst case examples of the central path, nuclear reactor core reloading optimization, oil refinery and VLSI design optimization and robust radiation therapy treatment optimization. Further, his research interest includes high performance optimization methods, optimization modeling, optimization problems in engineering sciences, and Quantum Computing Optimization. Prof. Terlaky is Founding Editor-in-Chief of the journal, Optimization and Engineering, and Editor-in-Chief of the Journal of Optimization Theory and Applications . He has served as associate editor of ten journals and has served as conference chair, conference organizer, and distinguished invited speaker at conferences all over the world. He was general Chair of the INFORMS 2015 Annual Meeting, a former Chair of INFORMS’ Optimization Society, Chair of the ICCOPT Steering Committee of the Mathematical Optimization Society, Chair of the SIAM Activity Groupon Optimization. He received: the MITACS Mentorship Award for his distinguished Ph.D. student supervisory record; the Egerváry Award of the Hungarian Operations Research Society; the Award of Merit of the Canadian Operations Research Society; The Wagner Prize of INFORMS; The Outstanding Innovation in Service Science Engineering Award of IISE. Prof. Terlaky is Fellow of the Fields Institute, Fellow of INFORMS, Fellow of SIAM, Fellow of IFORS, and Fellow of the Canadian Academy of Engineering.

Susanne Heipcke is Director of Software Engineering at FICO, where she has led the Modelling Team of FICO Xpress development for more than 12 years. Her team is responsible for the development and design of the modelling tools (Xpress Mosel) and the APIs of the Xpress Optimization software suite, with past tasks including the design of application development toolkits, solution templates, and productized optimization solutions such as FICO Decision Optimizer. More recently, her team’s responsibilities have expanded to include CI/CD, performance testing, and delivery infrastructure for the entire Xpress suite. Before joining Dash Optimization (acquired by FICO in 2008) in 1998, she worked for BASF-AG in Germany. Her Ph.D. research at the University of Buckingham—conducted partly at the MIT OR Center (USA) and the University Aix-Marseille II (France)—focused on solving large-scale industrial problems using a combination of constraint programming and mixed integer programming. Her work centers on all aspects of modelling, particularly through her contributions to the development of the algebraic modelling and programming language Xpress Mosel. She is the author of the book Applications of Optimization with Xpress-MP and numerous papers on different aspects of mathematical modelling. Susanne enjoys teaching mathematical optimization, having participated in teaching the mathematical modelling course in the OR master’s program at the University Aix-Marseille II (2001–2004) and the Computational Mixed-Integer Programming course at the Technical University of Munich in 2020. She regularly organizes specialist training events and conference sessions, such as the “Software for Optimization Modeling and Deployment” sessions at recent INFORMS Annual Meetings (jointly with Bob Fourer), and she is actively engaged in mentoring younger colleagues. Since 2019 she has been a member of the EURO Practitioners' Forum committee (formerly the EURO Working Group Practice of OR), leading the organization of the Forum’s annual meetings in 2020, 2023, and 2026. With more than 30 years of experience in applied OR, she has also contributed to numerous consulting projects worldwide, involving scheduling and planning in manufacturing, personnel staffing, aircraft routing with maintenance planning, portfolio optimization, trading, energy production planning and unit commitment, and retail logistics.Contents of this video:0:00 - Intro1:27 - Family background and early years4:15 - Attending a girls' high school4:58 - Polyglot9:11 - Learning to program during high school11:13 - Moving to Bavaria to study mathematics13:19 - Practical data processing projects14:52 - Learning about OR16:31 - Master's thesis on constraint programming (CP) applied to a problem arising at BASF20:31 - Getting inspiration from a female leader at BASF22:14 - Spending half a year at the MIT OR Center + moving to the University of Buckingham for a PhD25:02 - Adapting to the UK26:06 - Combining MIP and CP to solve production planning and scheduling problems29:19 - Joining Dash Optimization in 199830:32 - Moving to France in 199931:20 - Working form home in an era before Zoom, Git, and similar tools existed32:28 - Maternity and work33:55 - The modelling language Xpress Mosel36:38 - Launching Mosel in 200139:45 - Evolution of Mosel over the years45:16 - Mosel’s long-standing team47:35 - High compatibility across different versions of Mosel 48:16 - Xpress Mosel is a free software since 201849:21 - Favorite contributions to Mosel53:21 - Software engineering and optimization58:20 - AI and optimization software1:01:12 - Organizing conferences, workshops and special sessions regarding optimization software1:03:25 - EURO Practitioners' Forum1:04:52 - Regrets?1:05:18 - Plans for the future1:06:15 - Inspiring takeaway message1:07:22 - Concluding remarks