Peter Schüffler

Prof. Peter Schüffler is a Professor of Computational Pathology at the Technical University of Munich (TUM), holding joint appointments in the TUM School of Medicine and Health and the TUM School of Computation, Information and Technology. His research focuses on applying machine learning to digital pathology, including cancer detection, prognostic marker identification, and AI-driven diagnostic tools. He earned an MSc in Bioinformatics from Saarland University and a PhD in Machine Learning for Medical Image Analysis from ETH Zurich. As a postdoc and senior ML scientist at Memorial Sloan Kettering Cancer Center, he co-founded Paige, a digital pathology company. He joined TUM in 2021.

Education:

• MSc in Bioinformatics and Computational Biology, Saarland University and Max Planck Institute (MPI Saarbrücken)
• PhD in Machine Learning for Medical Image Analysis, ETH Zurich (2015)

Research Interests:

His work spans machine learning applications in pathology, including AI-driven diagnosis, automated quality assurance, and ergonomic systems for pathologists. Key areas include:

• Cancer detection and segmentation in pathology images
• Prognostic marker discovery for treatment success
• Efficient visualization of digital histopathology slides
• Integration of AI into clinical and educational workflows

Awards:

• Best Paper Award (2014): Computer Aided Crohn's Disease Severity Assessment in MRI
• Outstanding Paper Award (2013): Crohn's Disease Severity Assessment Model

Advising & Grants:

No specific student advisees or grants are listed in the provided text.

Labs/Teams:

Co-founder of Paige, a leader in AI-driven digital pathology systems. Active in TUM's computational pathology research groups.