Aharon Ben-Tal Wins 2026 INFORMS Theory Prize for Robust Optimization

The Institute for Operations Research and the Management Sciences (INFORMS) has awarded Aharon Ben-Tal, a professor at Technion – Israel Institute of Technology, the 2026 John von Neumann Theory Prize for his sustained contributions to theory in operations research and the management sciences. Announced on October 20, 2026, the award recognizes Ben-Tal’s work over five decades, with INFORMS identifying his pioneering research on robust optimization as his most influential achievement. The prize is among the association’s highest honors.

INFORMS said the award recognizes fundamental, sustained contributions that have stood the test of time, using significance, innovation, depth and scientific excellence as its criteria. Ben-Tal is an internationally recognized expert in continuous optimization whose technical work has extended across robust optimization, convexity theory, duality, optimal decision-making under uncertainty, structural design, semidefinite optimization and conic optimization. Ben-Tal helped create robust optimization through a long series of papers and a monograph written with Arkadi Nemirovski and Laurent El Ghaoui.

According to the announcement, his contributions span the field’s core theory, including tractability, and extended the area from static linear problems to multistage decision-making. He has also worked on applications of robust optimization in machine learning. INFORMS Chief Executive Officer and Executive Director Elena Gerstmann said Ben-Tal’s work on robust optimization was among the field’s most consequential contributions because it gave operations research a rigorous framework for making sound decisions when data are uncertain. “He didn’t just advance an area of research.

He helped create one, and the field has been building on it ever since,” Gerstmann said. Beyond robust optimization, Ben-Tal has conducted foundational work in convexity theory, duality and optimal decision-making under uncertainty. He also contributed to structural design by helping develop the theory and computational toolbox for semidefinite and conic optimization.

The announcement describes these achievements as influential, long-running contributions to operations research and the management sciences rather than as results of a single study. This is an award announcement based on the published body of research and the association’s assessment of its significance; it does not report a new experiment, clinical trial or fresh quantitative evaluation. Ben-Tal’s connection to the field has included teaching, student supervision, editorial work and professional service in addition to research.

The prize will be presented at the 2026 INFORMS Annual Meeting in San Francisco, scheduled for November 1–4, 2026. It includes a $5,000 cash prize, a medal and a formal citation. INFORMS, which describes itself as the world’s largest association for professionals and students in operations research, AI, analytics, data science and related disciplines, has more than 12,000 members across academia, industry and government.

Subject of Research: Recognition of Aharon Ben-Tal’s sustained contributions to robust optimization and operations research theory

Article Title: Aharon Ben-Tal awarded 2026 INFORMS John von Neumann Theory Prize

Article References: Aharon Ben-Tal awarded 2026 INFORMS John von Neumann Theory Prize. Original publication (Bibliographic details unavailable.)

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Keywords: Aharon Ben-Tal, INFORMS, John von Neumann Theory Prize, robust optimization, operations research, continuous optimization, convexity theory, duality, multistage optimization, machine learning, semidefinite optimization, Aharon