My research interests lie broadly in the area of safe and trustworthy Machine Learning and its subdomains: Modern Machine Learning systems, despite being tremendously successful at a plethora of tasks, are known to make overly confident predictons. This is, they are unable to communicate low confidence when confronted with data that is different from the data seen during training. Designing safe systems capable of flagging inputs they do not know how to properly process, is therefore crucial for safety-critical areas. In particular, I currently focus on out-of-distribution detection and open-set recognition for computer vision, with applications to the medical domain. Before the start of my PhD in Tübingen, I received a M.Sc. in Physics from LMU Munich and a M.Sc. in Data Science from the Barcelona GSE.