Dr. Markus Wenzel is a senior scientist in the Applied Machine Learning Group at the AI department of Fraunhofer HHI in Berlin.
He is interested in machine learning for the life sciences and medicine, and has published in: Bioinformatics, BMC Bioinform., BMC Genom., BMJ Health Care Inform., Front. Neurosci., J Neurosci., J Neural Eng., J Med. Syst., Medical Image Analysis, Nature Digital Medicine, IEEE CSM, PloS One, and The Lancet.
See these recent articles about explainable AI for protein language models, and about deep learning in histopathology:
- Wenzel, Grüner, Strodthoff. (2024). Insights into the inner workings of transformer models for protein function prediction. Bioinformatics, btae031. https://doi.org/10.1093/bioinformatics/btae031
- Springenberg, Frommholz, Wenzel, Weicken, Ma, & Strodthoff (2023). From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology. Medical Image Analysis, 102809. https://doi.org/10.1016/j.media.2023.102809
Currently, he is involved in the AI/AR Microscope project (with Fraunhofer USA Center Mid-Atlantic CMA) and the Testing and Experimentation Facility for Health AI and Robotics (TEF-Health).
Dr. Wenzel received his PhD (summa cum laude) from Technische Universität Berlin, for research on brain-computer interfacing, completed graduate studies (with distinction) in neurobiology, bioinformatics and biophysics at Albert-Ludwigs-Universität Freiburg, and has conducted research at École Normale Supérieure de Lyon, the Berlin Institute for Medical Systems Biology, the Bernstein Center for Computational Neuroscience, Technische Universität Berlin, and Fraunhofer HHI.