OUR FELLOWS
Get to know the Fellows of the Max Planck School of Biomedical AI
The Max Planck School of Biomedical AI (BMAI) brings together leading experts in biomedical research and artificial intelligence from across Germany. Our Fellows represent a broad range of disciplines, combining expertise in AI, computer science, and the life sciences to advance Biomedical AI. Through their diverse expertise and collaboration, they provide the scientific foundation and mentorship for BMAI doctoral students.
Peter Benner
Research Focus: Scientific Machine Learning, Operator
Learning, Numerical Analysis, Scientific
Computing
Philipp Berens
Research Focus: Computational Neuroscience, Medical Image Computing, Machine Learning
Picture © Elia Schmid
Elisabeth Binder
Karsten Borgwardt
Research Focus: Scientific Machine Learning, Operator Learning, Numerical Analysis, Scientific Computing; Picture © Susanne Vondenbusch-Teetz, MPI for Biochemistry
Meeyoung Cha
Research Focus: Data Science, Information System, Machine Learning
Daniel Cremers
Peter Dayan
Research Focus: Computational Psychiatry, Neural Reinforcement Learning
Frauke Gräter
Research Focus: Machine Learning, Protein Design, Molecular Simulations, Biomaterials
Stephan Grill
Research Focus: Active Matter Physics, Biological Physics, Spatiotemporal Cell Biology
Krishna Gummadi
Research Focus: AI Safety, Fair ML, Computational Social Science, Social Computing
Iryna Gurevych
Research Focus: Natural Language Processing, AI for Science, AI Safety;
Picture © Rüdiger Dunker
Heather Harrington
Research Focus: Algebraic Systems Biology, Higher Order Network Structures and Topological Data Analysis
Moritz Helmstaedter
Research Focus: Neuroscience, Neural Networks, Connectomics, Cerebral Cortex, Mammalian Brains, Human Cortex, 3D-Electron Microscopy, Machine Learning, AI for Large-Scale Image Processing;
Picture © MPI for Brain Research/S. Kraus-Fernando
Veit Hornung
Research Focus: Immunology, Functional Genomics, Image-Based Phenotyping
Stefanie Jegelka
Research Focus: Machine Learning (ML for Structured Data, Foundation Models, Reasoning, Multimodality)
Ralf Jungmann
Research Focus: Single-Molecule Biophysics, Super-Resolution Microscopy, Spatial Proteomics, DNA Nanotechnology
Zorah Lähner
Research Focus: Machine Learning, Geometric Deep Learning, Representation Learning
Matthias Mann
Research Focus: Mass Spectrometry-Based Proteomics, Clinical Proteomics, Spatial Proteomics, Bioinformatics, Systems Biology
Alexander Meissner
Klaus-Robert Müller
Research Focus: Machine Learning, AI for the Sciences (Neuroscience, Digital Pathology, Quantum Chemistry)
Björn Ommer
Research Focus: Computer Vision, Machine Learning, Generative AI;
Picture © Deutscher Zukunftspreis/Ansgar Pudenz
Daniel Rückert
Research Focus: Machine Learning, Medical Imaging, AI for Healthcare and Medicine; Picture © Andreas Heddergott / TUM
Anne Schaefer
Bernt Schiele
Research Focus: Machine Learning, Computer Vision, Interpretability of Machine Learning
Julia Schnabel
Research Focus: Machine Learning, Medical Imaging, Computational Imaging and AI in Medicine
Oliver Stegle
Research Focus: Machine Learning, Bioinformatics, Genomics, Systems Genetics
Fabian Theis
Research Focus: Computational Biology, Machine Learning;
Picture © Matthias Tunger Photodesign
Christian Theobalt
Maya Topf
Research Focus: Bioinformatics, Computational Structural Biology, Image Processing, cryoEM, Structure-based Drug Design, Molecular Virology
Volker Tresp
Research Focus: Machine Learning, Multimodal AI, Agentic AI, Explainable AI, Medical Informatics
Arno Villringer
Research Focus: Neuroscience, Neuroimaging, Neurology