I’m a Machine Learning and AI researcher with a focus on scientific discovery—developing theory and algorithms to uncover novel and causal mechanisms behind complex phenomena in the life sciences. I earned my PhD at the Max Planck Institute for Informatics and Saarland University, where I worked on information retrieval, statistical learning theory, and the exact discovery of robust multivariate, non-linear interactions. Afterward, I joined Harvard University to study the molecular mechanisms of cancer by inferring and analyzing gene regulatory networks from data.
My work spans traditional statistics (e.g. hypothesis testing, decision trees) through to modern approaches like deep neural networks, LLMs, computer vision, graph methods, and interpretable AI. I’ve also had the privilege of mentoring students throughout their academic journeys, which has been one of the most rewarding aspects of my career.