Hello!

I am a PhD student at the Max Planck Institute for Intelligent Systems and the University of Tübingen, advised by Claire Vernade and Michael Mühlebach.

My research centers on reinforcement learning, with a focus on the problems of generalization and lifelong learning. In my PhD, I aim to develop theoretical foundations for reinforcement learning under partial observability. I am also interested in the intersections of machine learning with other disciplines, such as dynamical systems, physics, and theoretical computer science.

Before starting my PhD, I interned at Google Research in Paris, where I worked on applying RL and graph neural networks to solve logistics problems. I did my master’s degree in machine learning at the University of Tübingen, where I worked with Georg Martius (at MPI-IS) on colored noise exploration in RL. Before that, I studied electrical engineering and computer science at the University of Duisburg-Essen, where I worked with Torsten Zesch on low-resource automatic speech recognition. Additionally, I have worked as a data scientist at Siemens on operational forecasting for power plants.