Prof. Dr. Björn Menze is a Full Professor for Biomedical Image Analysis and Machine Learning at the University of Zurich (UZH), Department of Quantitative Biomedicine, since September 2020. His work focuses on developing computational methods for transforming qualitative visual inspection of biomedical images into quantitative analyses and functional disease process modeling. Key research areas include clinical neuroimaging, tumor growth modeling, and integrating biophysical models with machine learning. Research interests span machine learning applications in medical imaging, such as magnetic resonance spectroscopy (MRS), deep learning for image analysis, and federated learning for privacy-protected AI. His team includes 17 PhD candidates and postdoctoral researchers, addressing challenges in neurovascular disease imaging, tumor characterization, and imaging biomarker development. Labs and teams include the Menze group at UZH, supported by the Helmut Horten Foundation. Current projects involve MRS simulation frameworks (e.g., MRS-Sim), deep learning for spectral modeling, and federated learning initiatives (e.g., FETS.Ai). Collaborations focus on advancing AI-driven diagnostics and personalized medicine.
