Simon Ging is a PhD candidate at the University of Freiburg, working with Prof. Thomas Brox on vision–language models. His current focus is radiology: getting models to connect what a scan shows with what a radiologist writes about it. Two papers at MICCAI 2026 come out of this line of work: disease-aware pretraining for 3D CT, and a scalable recipe for spatially grounded 2D radiology models. Before medicine, he worked on general-purpose vision–language problems: COOT (NeurIPS 2020) introduced a hierarchical transformer for video-text representation learning; an ICLR 2024 spotlight repurposed classification datasets and their label hierarchies into an open-ended VQA benchmark; a GCPR 2025 oral used knowledge graphs to harvest better CLIP training data. He holds an M.Sc. from Freiburg and, before that, several years of experience as a software developer and SAP consultant.
