Bernhard Reuter

Bernhard Reuter is a researcher at the University of Tübingen in the Department of Computer Science, focusing on machine learning methods for biomedical data. He develops tools for drug-resistance prediction in tuberculosis and HIV, and created the Generalized Perron Cluster Cluster Analysis (G-PCCA) for modeling non-equilibrium systems.

Education

• Dr. rer. nat. in Theoretical Physics (2018), University of Kassel
• Dipl.-Phys. in Physics (2013), University of Kassel

Research Highlights: His work bridges machine learning with biomolecular dynamics, particularly in drug resistance prediction and non-equilibrium system modeling. Publications in Nature Methods and Journal of Chemical Physics demonstrate his technical contributions.

Awards

• GDCH travel scholarships (2014, 2016)
• CINSAT poster award (2013)
• Doctoral scholarship (2013)
• Studienstiftung scholarship (2006)

He has contributed to open-source software projects like pyGPCCA and COmic, and collaborated with institutions including the Max Planck Institute for Biological Cybernetics.