Biography
Shoham Sabach joined the School of Operations Research and Information Engineering at Cornell in 2025 as an Associate Professor. His research focuses on mathematical optimization, spanning both theoretical foundations and applications in areas such as machine learning, data science, and artificial intelligence. Prior to Cornell, he was an associate professor on the faculty of Data and Decision Sciences at the Technion – Israel Institute of Technology and served as an Amazon Scholar at Amazon Research, where he worked on optimization for large-scale AI systems, including large language models. He received his Ph.D. in Mathematics from the Technion in 2012.
Research Interests
Dr. Sabach is an applied mathematician whose research focuses on the development and theoretical analysis of computationally efficient optimization algorithms. His work has advanced both the theoretical foundations and practical applications of modern optimization. He has introduced innovative algorithmic frameworks for large-scale nonconvex optimization with rigorous convergence guarantees, as well as efficient methods for convex bilevel optimization with established complexity bounds. On the applications side, his contributions span image processing, data science, machine learning, reinforcement learning, and, more recently, optimization techniques for large language models.
Service Interests:
Shoham Sabach is currently an associate editor for the following journals: Mathematics of Operations Research, Journal of Optimization Theory and Applications, Journal of Applied Mathematics and Optimization, Open Access Journal of Mathematical Optimization, and ESAIM: Control, Optimization and Calculus of Variations.
Select Publications
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Bolte, J., Sabach, S. and Teboulle, M.: Proximal alternating linearized minimization for nonconvex and nonsmooth problems, Mathematical Programming (Ser. A) 146 (2014), 459 – 494.
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Pock, T. and Sabach, S.: Inertial proximal alternating linearized minimization (iPALM) for nonconvex and nonsmooth problems, SIAM Journal on Imaging Sciences 9 (2016), 1756 – 1787.
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Sabach, S. and Shtern, S.: A first order method for solving convex bi-level optimization problems, SIAM Journal on Optimization 27 (2017), 640–660.
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Bolte, J., Sabach, S., Teboulle, M. and Vaisbourd, Y. First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems, SIAM Journal on Optimization 28 (2018), 2131 – 2151.
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Gur, E., Sabach, S. and Shtern, S.: Convergent nested alternating minimization algorithms for non-convex optimization problems, Mathematics of Operations Research 48 (2022), 53 – 77.
Select Awards and Honors
- Rothblum Award - ORSIS Prize for excellence in research in OR 2019
- Cooper prize for research excellence at the Technion 2018
- SIAM Activity Group on Optimization (SIAG/OPT) prize for the most outstanding paper in optimization 2017
- Humboldt postdoctoral fellowship 2013
Education
- B.Sc. in mathematics, University of Haifa 2004
- M.Sc. in mathematics, University of Haifa 2008
- Ph.D. in mathematics, Technion - Israel Institute of Technology 2012