I am a senior expert on reinforcement learning and activity lead at the Bosch Center for AI. My main goal is to bring advanced AI methods to applications in the real world. Currently, my main focus is on reinforcement learning, large-scale meta-learning, and generative AI methods.
Previously, I completed my PhD at ETH Zurich, for which I received the ELLIS PhD award. My PhD advisors were Andreas Krause and Angela Schoellig. I held a AI fellowship from the Open Philanthropy Project, was an Associated Fellow at the Max Planck ETH Center for Learning systems and a postgraduate affiliate at the Vector institute. I was also the workflow co-chair for ICML 2018 and completed research internships at Microsoft Research and Deepmind.
Recent News
- Jul. 2024: Publications Chair at ICML 2024
- Jul. 2024: Reinforcement Learning Workshop accepted at ICML 2024
- Jan. 2024: Invited talk at RL Workshop in Mannheim
- Feb. 2024: Invited talk at the RL4AA Workshop
- Sep. 2023: Represented Bosch at the ELLIS Phd Symposium
- Jul. 2023: Invited talk at the Reinforcement Learning Summer School
- Dec. 2022: Invited talk at the NeurIPS trustworthy AI Workshop
- Jul. 2022: Invited talk at IJCAI Workshop on Safe RL
- Feb. 2021: Two papers accepted at ICLR and AISTATS
- Oct. 2021: Invited talk at the Control Seminar, University of Oxford
- Oct. 2021: Outstanding reviewer award for NeurIPS 2021
- Sep. 2021: Invited talk at TU Darmstadt
- Sep. 2021: Panel speaker at IROS workshop on Safe Real-World Robot Autonomy
- Mar. 2021: Guest lecture on safe reinforcement learning as UCSD
Talks and Lectures
Guest lecture on Safe Bayesian Optimization for CS 159: Data-Driven Algorithm Design at Caltech.
ETH Day 2018 short presentation (in German)
Invited talk at the Workshop on Reliable AI 2017
NIPS/CoRL 2017: "Safe Model-based Reinforcement Learning with Stability Guarantees".