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 main research interest is reinforcement learning, particularly the problem of generalization and lifelong learning in RL. I am also interested in exploring connections between machine learning and other fields, such as dynamical systems, physics, and theoretical computer science.

Before 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.


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