Research Lab
My group is interested in Artificial Intelligence, Optimization, and Machine Learning and its applications. We develop new methodologies (e.g., new optimization and learning algorithms), work on combining learning and decision-making, as well as design AI Systems for real-world deployment in various application contexts. Recent examples include the estimation of biomass from satellite data, entanglement and non-locality thresholds via optimization, new constructions in extremal combinatorics via AI, as well as questions around AI and creativity. [group homepage] [more about research and projects]
TL;DR. We use computers to learn from data and make better decisions.
Prospective Students. If you are interested in working in our group or writing your MS/BS thesis please check our openings.
Select Recent Papers
(see publications for a complete list)
- Martínez-Rubio, D., and Pokutta, S. (2025). Beyond Short Steps in Frank-Wolfe Algorithms. Preprint. [arXiv] mlopt
- Troppens, H., Besançon, M., Wilken, S. E., and Pokutta, S. (2025). Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks. Preprint. [arXiv] ai4sciencebiochemistryopt
- Hendrych, D., Besançon, M., Martínez-Rubio, D., and Pokutta, S. (2025). Secant Line Search for Frank-Wolfe Algorithms. Preprint. [arXiv] opt
- Sadiku, S., Wagner, M., Nagarajan, S. G., and Pokutta, S. (2025). S-CFE: Simple Counterfactual Explanations. To Appear in Proceedings of AISTATS. [arXiv] mlxai
- Wirth, E., Besançon, M., and Pokutta, S. (2025). The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control. To Appear in Proceedings of AISTATS. [arXiv] mlopt (Oral Presentation + Conference Proceedings)
- Martinez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2025). Accelerated Methods for Riemannian Min-Max Problems. To Appear in Proceedings of AISTATS. [arXiv] mlopt
- Mexi, G., Kamp, D., Shinano, Y., Pu, S., Hoen, A., Bestuzheva, K., Hojny, C., Walter, M., Pfetsch, M. E., Pokutta, S., and Koch, T. (2025). State-of-the-art Methods for Pseudo-Boolean Solving with SCIP. Preprint. [arXiv] ipoptsoftware
- Roux, C., Martínez-Rubio, D., and Pokutta, S. (2025). Implicit Riemannian Optimism with Applications to Min-Max Problems. Preprint. [arXiv] mlopt
- Mundinger, K., Zimmer, M., Kiem, A., Spiegel, C., and Pokutta, S. (2025). Neural Discovery in Mathematics: Do Machines Dream of Colored Planes? Preprint. [arXiv] ai4sciencedggraphs
- Besançon, M., Designolle, S., Halbey, J., Hendrych, D., Kuzinowicz, D., Pokutta, S., Troppens, H., Viladrich Herrmannsdoerfer, D., and Wirth, E. (2025). Improved algorithms and novel applications of the FrankWolfe.jl library. Preprint. [arXiv] optsoftware
- Haase, J., and Pokutta, S. (2024). Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration. Preprint. [arXiv] mlsocial
- Designolle, S., Vértesi, T., and Pokutta, S. (2024). Better bounds on Grothendieck constants of finite orders. Preprint. [arXiv] optphysicsquantum
- Abbas, A., Ambainis, A., Augustino, B., Bärtschi, A., Buhrman, H., Coffrin, C., Cortiana, G., Dunjko, V., Egger, D. J., Elmegreen, B. G., Franco, N., Fratini, F., Fuller, B., Gacon, J., Gonciulea, C., Gribling, S., Gupta, S., Hadfield, S., Heese, R., … Zoufal, C. (2024). Quantum Optimization: Potential, Challenges, and the Path Forward. Nature Reviews Physics. [PDF] [arXiv] optphysicsquantumsurvey
- Wirth, E., Peña, J., and Pokutta, S. (2024). Fast Convergence of Frank-Wolfe algorithms on polytopes. Preprint. [arXiv] mlopt
- Braun, G., Carderera, A., Combettes, C. W., Hassani, H., Karbasi, A., Mokthari, A., and Pokutta, S. (2022). Conditional Gradient Methods. Preprint. [arXiv] mloptsurvey
Select Recent Talks and Teaching
- 12/2024: (technical) “Exploring Mixed-Integer Convex Optimization with Conditional Gradients: Foundations and Applications”. Talk at MIP International Workshop (Mumbai, India). [slides]
- 12/2024: (technical) “AI x Algorithms x Applications”. Talk at NUS School of Computing Seminar (Singapore).
- 11/2024: (technical) “Extending the Continuum of Six-Colorings”. Talk at MFO Program: Combinatorial Optimization (Oberwolfach, Germany). [slides]
- 07/2024: (technical) “German <-> Japanese Supercomputing - a success story”. Keynote at 16th JHPCN symposium (Tokyo, Japan). [slides]
- 07/2024: (technical) “Extending the Continuum of Six-Colorings”. Talk at Conference on Discrete Optimization and Machine Learning (Tokyo, Japan). [slides]
- WS/2024: Discrete Optimization and Machine Learning (seminar)
Recent Blog Posts
- 02/2025: FrankWolfe.jl: An Update on the Julia Package
- 02/2025: Estimating Rare Probabilities
- 11/2024: On the Byzantine-Resilience of Distillation-Based Federated Learning
- 11/2024: The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses
- 10/2024: A short intro to Special Relativity
Select Outreach
- 11/2024: El aprendizaje automático ayuda a atacar problemas matemáticos clásicos (Machine learning helps attack classical mathematical problems). El Pais: Café y teoremas. (Newspaper (Spanish))
- 11/2024: Zukunftsforum KI. IHK Berlin. (Panel Discussion (German))
- 10/2021: Improve the World with Maths?. Humboldt Forum: Discourse, Science and Humanities. (Talk + Discussion (German))
- 05/2021: Durch KI verhandene Ressourcen effizienter nutzen. Aufbruch Ausgabe 28. (Interview (German))
- 12/2020: Folge 7: „Trendsetter Internet? Angstmacher KI? Folgen der Digitalisierung“. Brain City Berlin. (Podcast (German))
News
- 10/2024: Elected Chair of the Cluster of Excellence MATH+ together with Claudia Schillings and Andrea Walther.
- Fall 2024: David Martínez-Rubio started a faculty position at Carlos III University of Madrid. Congratulations!
- Fall 2024: Zev Woodstock started a faculty position at James Madison University. Congratulations!
- 01/2024: The Zuse Institute Berlin (ZIB) is celebrating its 40th anniversary in 2024.
- Fall 2023: Mathieu Besançon started a faculty position at INRIA Grenoble. Congratulations!