RL theory
Melanie Zeilinger
safe reinforcement learning
learning-based control
model predictive control
control theory
Zeilinger leads ETH Zurich’s Intelligent Control Systems group, developing theory and algorithms for safe learning-based control, model-based decision making, and reinforcement-learning-adjacent control systems with guarantees.
Pros
- Strong safe learning-based control with rigorous guarantees and ERC-level funding
- Excellent ETH ecosystem, resources and visibility
- Clear control-plus-RL-adjacent fit with real-world relevance
ETH Intelligent Control Systems profile
A quick heads-up: This list is a work in progress! The focus tags and pros are AI-generated, so they might occasionally miss the mark. If you spot any missing labs, notice an error, or have ideas for improvements, please feel free to open a pull request. We’d love your help making this better!