Adrian Müller

Hi, I’m Adrian! I’m a first-year ELLIS PhD student in Computer Science at ETH Zürich, fortunate to be advised by Niao He and co-advised by Gergely Neu. My research interests are the foundations of sequential decision-making (including reinforcement learning), online learning, and theoretical machine learning more broadly.

I obtained my MSc in data science and my BSc in mathematics, both from ETH. Throughout my undergraduate studies, I had been very fortunate to be supported by the German Academic Scholarship Foundation („Studienstiftung“). I had also been an active long-term member of the ETH Student Sustainability Committee.

• 09/2024: I'm officially starting my PhD in the ODI lab!
• 07/2024: Together with Luca Viano, Pragnya Alatur and Anas Barakat, we organized the ETHZ-EPFL Summer School on Multi-Agent Reinforcement Learning.
• 07/2024: Presenting our paper Truly No-Regret Learning in Constrained MDPs as a Spotlight at ICML and at the Foundations of RL and Control Workshop.

Best of Both Worlds: Regret Minimization versus Minimax Play
Adrian Müller*, Jon Schneider*, Stratis Skoulakis*, Luca Viano*, Volkan Cevher
Preprint, under review.
> arXiv link

Truly No-Regret Learning in Constrained MDPs
Adrian Müller, Pragya Alatur, Volkan Cevher, Giorgia Ramponi, Niao He
ICML, 2024 (Spotlight)
> arXiv link

Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes
Adrian Müller, Pragya Alatur, Giorgia Ramponi, Niao He
European Workshop on Reinforcement Learning, 2023
> arXiv link

• Spring 2025: Teaching Assistant for Theoretical Foundations of Reinforcement Learning
• 2024: Co-organizer of the ETHZ-EPFL Summer School on Multi-Agent Reinforcement Learning
• Fall 2020 & 2021: Teaching Assistant for Algorithms and Complexity