I'm a research scientist and team lead working on decision-making under uncertainty, mechanistic interpretability of large models, and generalization. I've published at machine learning venues including ICLR, ICML, TMLR, CoRL, with 900+ citations and an h-index of 13.
I'm currently serving as a research group leader at the FZI and KIT. For more details, please see this page.
I engineer and align representations in deep learning models. Key aspects of my work include leveraging representation quality metrics and invariance properties of features for learning. I apply these techniques to create more interpretable and controllable models.
My research covers model-based reinforcement learning, focusing on partially observable Markov decision processes and multi-armed bandits. My work includes novelty detection, information gathering, and curriculum learning to enhance learning efficacy.
Autonomous driving serves as a major application area of my research. I develop and evaluate algorithms that operate in real-time on autonomous car prototypes to study sequential decision-making, interpretability, and generalization.