Timo is a postdoc at the Machine Learning in Science Cluster at the University of Tübingen. His research centers around interpretable ML and XAI, the philosophy of science, ML and causality, as well as the ethics of AI, and algorithmic fairness. In his recent work, Timo raises awareness of the issues around model-agnostic tools to explain ML models, works on formalizing existing concepts in the XAI literature, or introduces a new framework for understanding robustness. He is also coauthor of the book Supervised Machine Learning for Science.

Before Tübingen, Timo was a PhD student at the Munich Center for Mathematical Philosophy (LMU Munich) working on the question of what it is that explainable AI explains.