Marc Teboulle

Marc Teboulle is a distinguished Professor holding The Eric and Sheila Samson Chair of Optimization in the School of Mathematical Sciences at Tel Aviv University. With a career spanning over three decades, he has established himself as a leading figure in optimization theory and applications. His work bridges theoretical foundations with practical implementations across multiple scientific domains.

Professor Teboulle's research focuses on continuous optimization, with particular emphasis on convex optimization, complexity analysis of algorithms, Lagrangian and dual decomposition methods, variational inequalities, and nonconvex nonsmooth large-scale optimization. His work has significant applications in engineering science, machine learning, and finance, demonstrating the interdisciplinary impact of optimization techniques. He has developed novel frameworks for center-based clustering algorithms and contributed to the theoretical understanding of first-order methods beyond traditional Lipschitz gradient continuity assumptions.

His publication record shows a clear evolution toward increasingly sophisticated optimization frameworks, with recent work focusing on nonconvex composite optimization, Lagrangian-based methods, and complexity analysis of gradient-based algorithms. The trend indicates growing interest in non-Euclidean geometries for optimization and applications to high-dimensional data problems, reflecting the evolving challenges in modern optimization.

As an educator and mentor, Professor Teboulle has supervised numerous PhD and MSc students since 1990, including prominent researchers like Amir Beck, Ron Shefi, and Yoel Drori. His graduate courses include Convex Analysis and Optimization, Advanced Topics in Modern Optimization, Algorithms for Continuous Optimization, and Advanced Seminar in Continuous Optimization.

He has been exceptionally active in the academic community, delivering invited lectures at major international conferences from 2003 through 2024 across Asia, Europe, and North America. His book 'Asymptotic Cones and Functions in Optimization and Variational Inequalities' (co-authored with A. Auslender) has become a standard reference in the field, while his edited volume 'Grouping Multidimensional Data: Recent Advances in Clustering' has influenced data science applications.