Andreas Schlaginhaufen is a Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the SYCAMORE Lab under the Institute of Microengineering (IGM) within the School of Engineering (STI). His research focuses on reinforcement learning, safe AI systems, and convex analysis, with a particular emphasis on aligning AI models with human preferences and expert demonstrations. Education: He holds a Bachelor's and Master’s in Electrical Engineering and Information Technology from ETH Zurich, with an exchange semester at the University of Toronto, Canada. He has interned with EWZ Zurich's power grid team and ETH Zurich’s Learning & Adaptive Systems group. Bachelor's in Electrical Engineering (ETH Zurich) Master’s in Electrical Engineering and Information Technology (ETH Zurich) Exchange: University of Toronto, Canada Research Interests: His work spans reinforcement learning, safe reinforcement learning, convex analysis, and learning in games. He explores theoretical and practical aspects of reward shaping, transferability of learned models, and ensuring policy safety in dynamic environments. Awards: He has been awarded the Swiss Data Science Center PhD Fellowship, providing full funding and mentorship during his doctoral studies. Advising and Grants: While currently focused on his doctoral research, his fellowship supports his exploration of inverse reinforcement learning and its applications. He contributes to the SYCAMORE Lab, which investigates multi-agent optimization and systems control. Labs/Teams: He is part of the SYCAMORE Lab at EPFL, which focuses on systems control and multi-agent optimization, advancing theoretical and applied research in AI-driven systems.










