Coordinates
Professor
Optimization and Machine Learning
Mathematics and EECS (courtesy), TU Berlin
Straße des 17. Juni 135, 10623 Berlin
Bio
Sebastian Pokutta is a mathematician and computer scientist, the Vice President of the Zuse Institute Berlin (ZIB) and a Professor of Mathematics at TU Berlin with a research focus on Artificial Intelligence and Optimization. He is also the Executive Chair of the Cluster of Excellence MATH+, a Chair of the Research Campus MODAL, and a member of ELLIS (European Laboratory for Learning and Intelligent Systems). Having received both his diploma and Ph.D. in mathematics from the University of Duisburg-Essen in Germany, Pokutta was a postdoctoral researcher and visiting lecturer at MIT, worked for IBM ILOG, and various consulting companies. Prior to joining ZIB and TU Berlin, he was the David M. McKenney Family Associate Professor in the School of Industrial and Systems Engineering and an Associate Director of the Machine Learning @ GT Center at the Georgia Institute of Technology as well as a Professor at the University of Erlangen-Nürnberg. Sebastian received the Gödel Prize in 2023, a STOC Test of Time award (10 years) in 2022, the David M. McKenney Family Early Career Professorship in 2016, an NSF CAREER Award in 2015, the Coca-Cola Early Career Professorship in 2014, the outstanding thesis award of the University of Duisburg-Essen in 2006, as well as various Best Paper awards.
Pokutta’s research is situated at the intersection of Artificial Intelligence and Optimization, combining Machine Learning with continuous and discrete optimization techniques, alongside the complexity theory of Extended Formulations. A particular focus is the development and analysis of Frank-Wolfe (conditional gradient) methods due to their versatility in constrained optimization, structured learning, and network compression. More recently, his research group has focused on AI4Science and AI4Math, working on agentic systems for scientific discovery and mathematical reasoning. This includes the development of evolutionary coding agents, automated constraint-handler generation for mixed-integer programming, and the integration of Large Language Models with formal proof verification. This is complemented by the use of deep learning and attention-based architectures to solve problems in computational algebra, such as transformer oracles for border basis algorithms and neural sum-of-squares certificates. Additional research directions include the interface of AI and human co-creativity, modeling multi-agent student simulations, temporal persona stability, and functional analogs of intrinsic motivation. Pokutta has also worked on diverse applied optimization problems across supply chain logistics, manufacturing, and quantitative finance.
Education
- Diploma in Mathematics (minor in Computer Science)
University of Duisburg-Essen, Germany, 2003 - Ph.D. in Mathematics
University of Duisburg-Essen, Germany, 2005 - Postdoctoral Researcher
Massachusetts Institute of Technology, USA, 2006
Honors & Awards
- Land-Doing MIP Computational Competition Winner, 2026
together with G. K. Tjusila, A. Hoen, N.-C. Kempke, G. Mexi, T. Berthold, A. Gleixner, and T. Koch - Land-Doing MIP Computational Competition Winner, 2025
together with G. Mexi, D. Hendrych, S. Designolle, and M. Besançon - Science Prize of the Association for Pediatric Orthopedics (VKO), 2025
for “Feature Engineering for the Prediction of Scoliosis in 5q-Spinal Muscular Atrophy”, T.-L. Vu-Han, V. Sunkara, R. Bermudez-Schettino, J. Schwechten, R. Runge, C. Perka, T. Winkler, S. Pokutta, C. Weiß, M. Pumberger - Gödel Prize, 2023
for “Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds”, S. Fiorini, S. Massar, S. Pokutta, H.R. Tiwary, R. de Wolf - Symposium on Theory of Computing (STOC) Test of Time award (10 years), 2022
for “Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds”, S. Fiorini, S. Massar, S. Pokutta, H.R. Tiwary, R. de Wolf - David M. McKenney Family Early Career Professorship, 2016
in the H. Milton School of Industrial and Systems Engineering at Georgia Tech - NSF CAREER Award, 2015
- EGRIE Annual Meeting Best paper award, 2014
for “Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments”, N. Gatzert, S. Pokutta, and N. Vogl - Coca Cola Early Career Professorship, 2014
in the H. Milton School of Industrial and Systems Engineering at Georgia Tech - Symposium on Theory of Computing (STOC) Best paper award, 2012
for “Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds”, S. Fiorini, S. Massar, S. Pokutta, H.R. Tiwary, R. de Wolf - Energy-Finance Best paper award, 2010
for “On clearing coupled day-ahead electricity markets”, A. Martin, J. Müller, S. Pokutta - DAAD Postdoctoral fellow, 2006-2007
- GIF Postdoctoral fellowship, 2006
Select Key Roles
- Cluster of Excellence MATH+
Executive Chair, Fall 2024 - link - Research Campus MODAL
Chair, 2020 - link - Zuse Institute Berlin
Vice President, 2019 - link - Technische Universität Berlin
Professor, 2019 - link - Georgia Institute of Technology
Associate Professor (with tenure), 2016 - 2019 link - Center for Machine Learning @ Georgia Tech
(Founding) Associate Director, 2016 - 2019 link
Select Service
- SCML: Symbolic Computation and Machine Learning
Founding Member of Scientific Committee, 2024 - link - Mathematical Programming
Associate Editor, Jan. 2021 - link - Open Journal of Mathematical Optimization
Section Editor: Discrete Optimization, Jan. 2020 - link - Discrete Optimization
Associate Editor, 2017 - link - DFG (2025 - 2026), ONR (2024, 2020), ERC (2024), ANITI (2023), Max-Planck (2023), Bavarian Government (2019), FNRS (2015), NSF (2013, 2014, 2015, 2017, 2018)
Panelist / Reviewer
Select Conference Service
- Neural Information Processing Systems (NeurIPS)
Area Chair (2026, 2025, 2024, 2023, 2022, 2021) - International Conference on Machine Learning (ICML)
Area Chair (2026, 2025, 2023) - International Conference on Learning Representations (ICLR)
Area Chair (2026) - 8th International Conference on Discrete Optimization and Machine Learning
Conference Organizer, Tokyo, Japan (2026) link - Workshop on AI-gestützte Forschungsprozesse in der Mathematik
Workshop Organizer, Speinshart, Germany (2026) link - International Conference on Optimization and Machine Learning (ICOML)
Organizing Committee Member, Taipei, Taiwan (2026) link - 7th International Conference on Discrete Optimization and Machine Learning
Conference Organizer, Kyoto, Japan (2025) link - 6th International Conference on Discrete Optimization and Machine Learning
Conference Organizer, Tokyo, Japan (2024) link - Thematic Einstein Semester on Mathematical Optimization for Machine Learning (MATH+)
Organizer, Berlin, Germany (2023) link - ICERM Special Semester on Discrete Optimization: Mathematics, Algorithms, and Computation
Workshop Organizer, Providence, RI (2023) link - ADA Lovelace Workshop on Discrete Optimization and Machine Learning
Workshop Organizer and Program Committee, Erlangen, Germany (2023) link - 5th International Conference on Discrete Optimization and Machine Learning
Conference Organizer, Tokyo, Japan (2023) link - International Symposium on Combinatorial Optimization (ISCO) (2026), OPT 2025 @ NeurIPS Workshop (2025), NHR Conference 2025 (2025), Symposium on Experimental Algorithms (SEA) (2025), Neural Information Processing Systems (NeurIPS) Competitions (2022), International Joint Conferences on Artificial Intelligence (IJCAI) (2021), Integer Programming and Combinatorial Optimization (IPCO) (2021)
Program Committee Member