Wolfseher

Lymphoma diagnosis depends on the visual interpretation of stained tissue biopsies — a process that is complex, experience-driven, and difficult to standardize. AI can support pathologists in this task, but only if its reasoning is transparent enough to be trusted clinically. My research focuses on developing interpretable AI methods for lymphoma diagnostics, combining self-supervised representation learning with similarity-based case retrieval to make AI-driven diagnoses traceable back to validated reference cases.

I studied Mathematics at the University of Regensburg and joined the Spang Lab in June 2023.