Sebastian Pokutta
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| Sebastian Pokutta | |
|---|---|
| Born | June 1980 (age 46) Essen, Germany |
| 🏫 Education | University of Duisburg-Essen |
| 💼 Occupation | |
| 🏅 Awards | Gödel Prize (2023) STOC Test of Time Award (2022) STOC Best Paper Award (2012) NSF CAREER Award (2015) |
| 🌐 Website | www |
Sebastian Pokutta (born 1980) is a German mathematician and computer scientist. He is a professor of mathematical optimization at TU Berlin and Vice President of the Zuse Institute Berlin (ZIB).[1] He has been Executive Chair of the Cluster of Excellence MATH+ Berlin Mathematics Research Center since October 2024.[2]
Pokutta received the Gödel Prize in 2023, together with Samuel Fiorini, Serge Massar, Hans Raj Tiwary, Ronald de Wolf, and Thomas Rothvoss, for their work on the extension complexity of polytopes in combinatorial optimization.[3][4]
Education and career
Pokutta received his diploma in 2003 and PhD (Dr. rer. nat.) in 2005 in mathematics from the University of Duisburg-Essen, where he was advised by Rüdiger Göbel.[5] His doctoral dissertation was titled "Products over countable domains".[5]
After postdoctoral work at the Operations Research Center of the Massachusetts Institute of Technology (MIT),[6] Pokutta worked at IBM ILOG and in consulting.
In 2012, Pokutta joined the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology as an assistant professor. He was named Coca-Cola Early Career Professor in 2014[7] and David M. McKenney Family Early Career Professor in 2016.[8] He served as Associate Director of Georgia Tech's Center for Machine Learning (ML@GT).
In 2019, Pokutta became a professor for mathematical optimization and machine learning at TU Berlin, Germany, together with the position of Vice President at the Zuse Institute Berlin.[1] He leads the Interactive Optimization and Learning (IOL) research group, which conducts research on the intersection of mathematical optimization, machine learning, and artificial intelligence. Since 2020, he has co-chaired the Research Campus MODAL (Mathematical Optimization and Data Analysis Laboratories), a BMFTR-funded research initiative.[1]
In October 2024, Pokutta was elected Executive Chair of MATH+, the Berlin Cluster of Excellence in mathematics, alongside Claudia Schillings (FU Berlin) and Andrea Walther (HU Berlin).[2] In 2025, MATH+ secured continued funding under the German Excellence Strategy for another seven years.[9]
Research
Pokutta's research focuses on mathematical optimization and machine learning, particularly extended formulations and Frank–Wolfe algorithms. He and his research group also work on integer programming, explainable artificial intelligence, neural-network compression, and convex optimization. His recent research also applies methods from optimization and artificial intelligence across disciplines, including mathematical discovery, quantum computing, human–AI interaction, education, and the social sciences.
Extended formulations
In 2012, Pokutta and co-authors Samuel Fiorini, Serge Massar, Hans Raj Tiwary, and Ronald de Wolf proved that any linear programming formulation for the Travelling Salesman Problem (TSP) polytope requires exponentially many variables and constraints, resolving a conjecture that had been open since the work of Yannakakis in 1988.[3][10] Among other things, the proof established a connection between one-way quantum communication protocols and semidefinite programming formulations.[4] The paper received the Best Paper Award at STOC 2012[11] and the STOC Test of Time Award in 2022.[12][13]
Frank-Wolfe methods
Pokutta has also published research on the theory and applications of Frank-Wolfe algorithms (also known as conditional gradients) for convex optimization. In 2025, he co-authored a monograph on the subject published in the MOS-SIAM Series on Optimization.[14]
AI for mathematics
Pokutta studies the use of artificial intelligence for mathematical and scientific discovery (AI4MATH / AI4Science). This includes questions around the design of AI systems that can be used in mathematical discovery,[15] as well as questions around formalization and verification of AI generated mathematical output.
Interdisciplinary research
Pokutta's interdisciplinary research examines applications of large language models and multi-agent systems, including human–AI co-creativity,[16] AI-supported education,[17] AI-assisted research[15] and quantum physics,[18] and applications in social science research[19] and climate monitoring.[20]
Awards and honors
- Gödel Prize (2023), with Samuel Fiorini, Serge Massar, Hans Raj Tiwary, Ronald de Wolf, and Thomas Rothvoss[3]
- STOC Test of Time Award (2022)[12]
- STOC Best Paper Award (2012)[11]
- David M. McKenney Family Early Career Professor, Georgia Tech (2016)[8]
- NSF CAREER Award (2015)[21]
- Coca-Cola Early Career Professor, Georgia Tech (2014)[7]
Selected publications
- Fiorini, S.; Massar, S.; Pokutta, S.; Tiwary, H.R.; de Wolf, R. (2015). "Exponential Lower Bounds for Polytopes in Combinatorial Optimization". Journal of the ACM. 62 (2): 1–23. doi:10.1145/2716307.
- Braun, G.; Carderera, A.; Combettes, C.W.; Hassani, H.; Karbasi, A.; Mokhtari, A.; Pokutta, S. (2025). Conditional Gradient Methods. MOS-SIAM Series on Optimization. SIAM. ISBN 978-1-61197-855-1. Search this book on
References
- ↑ 1.0 1.1 1.2 "Prof. Dr. Sebastian Pokutta". Zuse Institute Berlin. Retrieved 2026-04-10.
- ↑ 2.0 2.1 "New Chairs for Berlin Excellence Cluster MATH+". MATH+. 18 October 2024. Retrieved 2026-04-10.
- ↑ 3.0 3.1 3.2 "2023 Gödel Prize Citation". ACM SIGACT. Retrieved 2026-04-10.
- ↑ 4.0 4.1 "Prof. Dr. Sebastian Pokutta receives Gödel Prize". Technische Universität Berlin. Retrieved 2026-04-10.
- ↑ 5.0 5.1 "Sebastian Pokutta". Mathematics Genealogy Project. Retrieved 2026-04-10.
- ↑ "Gödel Prize 2023 for Sebastian Pokutta". MATH+. 1 June 2023. Retrieved 2026-04-10.
- ↑ 7.0 7.1 "Sebastian Pokutta Appointed Coca-Cola Assistant Professor". Georgia Institute of Technology. 15 July 2014. Retrieved 2026-04-10.
- ↑ 8.0 8.1 "Faculty Spotlight: Sebastian Pokutta Announced as David M. McKenney Family Assistant Professor". Georgia Institute of Technology. 2016. Retrieved 2026-04-10.
- ↑ "Success in Excellence Strategy: MATH+ Receives Funding for Another Seven Years". MATH+. 2025. Retrieved 2026-04-10.
- ↑ Fiorini, Samuel; Massar, Serge; Pokutta, Sebastian; Tiwary, Hans Raj; de Wolf, Ronald (2015). "Exponential Lower Bounds for Polytopes in Combinatorial Optimization". Journal of the ACM. 62 (2): 1–23. arXiv:1111.0837. doi:10.1145/2716307.
- ↑ 11.0 11.1 "Best Papers". ACM SIGACT. Retrieved 2026-04-10.
- ↑ 12.0 12.1 "2022 Test of Time Award". ACM SIGACT. Retrieved 2026-04-10.
- ↑ "Prestigious ACM STOC 10-Year Test of Time Award for Ronald de Wolf and Colleagues". CWI. June 2022. Retrieved 2026-04-10.
- ↑ Braun, Gábor; Carderera, Alejandro; Combettes, Cyrille W.; Hassani, Hamed; Karbasi, Amin; Mokhtari, Aryan; Pokutta, Sebastian (2025). Conditional Gradient Methods. MOS-SIAM Series on Optimization. SIAM. doi:10.1137/1.9781611978568. ISBN 978-1-61197-855-1. Search this book on
- ↑ 15.0 15.1 Zimmer, Max; Pelleriti, Nico; Roux, Christophe; Pokutta, Sebastian (2026). The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learning. ICML 2026 Workshop on AI as a Tool for Mathematics, Computer Science, and Machine Learning (AI4Research). arXiv:2603.15914.
- ↑ Haase, Jennifer; Pokutta, Sebastian (2026). "Human–AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration". Generative Artificial Intelligence and Creativity. pp. 205–221. doi:10.1016/B978-0-443-34073-4.00009-5. ISBN 978-0-443-34073-4. Search this book on
- ↑ Gonnermann-Müller, Jana; Haase, Jennifer; Leins, Nicolas; Igel, Moritz; Fackeldey, Konstantin; Pokutta, Sebastian (2026). "FACET: Multi-Agent AI Supporting Teachers in Scaling Differentiated Learning for Diverse Students". Proceedings of the International Joint Conference on Artificial Intelligence. arXiv:2601.22788.
- ↑ Abbas, Amira; Ambainis, Andris; Augustino, Brandon; Bärtschi, Andreas; Buhrman, Harry; Coffrin, Carleton; Cortiana, Giorgio; Dunjko, Vedran; Egger, Daniel J.; Elmegreen, Bruce G.; Franco, Nicola; Fratini, Filippo; Fuller, Bryce; Gacon, Julien; Gonciulea, Constantin; Gribling, Sander; Gupta, Swati; Hadfield, Stuart; Heese, Raoul; Kircher, Gerhard; Kleinert, Thomas; Koch, Thorsten; Korpas, Georgios; Lenk, Steve; Marecek, Jakub; Markov, Vanio; Mazzola, Guglielmo; Mensa, Stefano; Mohseni, Naeimeh; Nannicini, Giacomo; O'Meara, Corey; Peña Tapia, Elena; Pokutta, Sebastian; Proissl, Manuel; Rebentrost, Patrick; Sahin, Emre; Symons, Benjamin C. B.; Tornow, Sabine; Valls, Victor; Woerner, Stefan; Wolf-Bauwens, Mira L.; Yard, Jon; Yarkoni, Sheir; Zechiel, Dirk; Zhuk, Sergiy; Zoufal, Christa (2024). "Challenges and opportunities in quantum optimization". Nature Reviews Physics. 6 (12): 718–735. arXiv:2312.02279. Bibcode:2024NatRP...6..718A. doi:10.1038/s42254-024-00770-9.
- ↑ Haase, Jennifer; Pokutta, Sebastian (2026). "Beyond static responses: Multi-agent LLM systems as a new paradigm for social science research". Humanities and Social Sciences Communications. 13 (1): 1490. doi:10.1057/s41599-026-08832-2.
- ↑ Pauls, Jan; Schrödter, Karsten; Ligensa, Sven; Schwartz, Martin; Turan, Berkant; Zimmer, Max; Saatchi, Sassan; Pokutta, Sebastian; Ciais, Philippe; Gieseke, Fabian (2026). "ECHOSAT: Estimating Canopy Height Over Space and Time". arXiv:2602.21421 [cs.CV].
- ↑ "CAREER: Semidefinite Programming (SDP) Extended Formulations". National Science Foundation. Retrieved 2026-04-10.
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