Maximilian Seeliger

I am a direct doctorate student at ETH Zurich, currently working with the Learning & Adaptive Systems Group on reinforcement learning. In particular, my focus is on zero-shot methods that generalize to unseen tasks at test time and analyzing latent world models to understand their relationship to reinforcement learning.

Prior to ETH, I completed a Bachelor with Honors in computer science at the Technical University of Vienna, working with Prof. Thomas Gärtner on graph representations for machine learning. I was also a research intern at the Chatterjee Group at IST Austria, where I worked on formal verification and automated reasoning.