Till Freihaut
PhD student, University of Zurich
freihaut [AT] ifi.uzh.ch
Bio
Hi! I am a PhD student interested in the mathematical aspects of Reinforcement Learning, particularly in multi-agent systems with a focus on imitation learning. I am fortunate to be advised by Giorgia Ramponi at the University of Zurich. Additionally, I am an affiliated doctoral student at the ETH AI Center.
Previously, I completed my master's degree in mathematics at the University of Mannheim (with honors), where I was co-advised by Claire Vernade , Leif Döring and Simon Weissmann. In my thesis I worked on (contextual) bandits and importance sampling.
News
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Publications
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Rate optimal learning equilibria from data
Till Freihaut‡, Luca Viano‡, Emanuele Nevali,Volkan Cevher, Matthieu Geist, Giorgia Ramponi
Arxiv'25: arXiv preprint. 2025.
Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning
Till Freihaut‡, Luca Viano‡, Volkan Cevher, Matthieu Geist, Giorgia Ramponi
NeurIPS 2025.
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
Till Freihaut, Giorgia Ramponi
NeurIPS 2025.
Barycenter Policy Design for Multiple Policy Evaluation
Simon Weissmann‡, Till Freihaut‡, Claire Vernade, Giorgia Ramponi, Leif Döring
EWRL 2025.
Rate optimal learning equilibria from data
Till Freihaut‡, Luca Viano‡, Emanuele Nevali,Volkan Cevher, Matthieu Geist, Giorgia Ramponi
Arxiv'25: arXiv preprint. 2025.
Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning
Till Freihaut‡, Luca Viano‡, Volkan Cevher, Matthieu Geist, Giorgia Ramponi
NeurIPS 2025.
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
Till Freihaut, Giorgia Ramponi
NeurIPS 2025.
Barycenter Policy Design for Multiple Policy Evaluation
Simon Weissmann‡, Till Freihaut‡, Claire Vernade, Giorgia Ramponi, Leif Döring
EWRL 2025.
Vitæ
Full Resume in PDF.