Claas Thesing

Claas is an interdisciplinary researcher with a background in computer science and a focus on machine learning for healthcare and computational biology. He holds degrees in Computer Science from RWTH Aachen University (B.Sc.) and the University of Oxford (M.Sc.). His research includes generalising kernel-based algorithms for robust atrial fibrillation detection and designing pipelines for the segmentation and 3D reconstruction of the atria from MRI scans.

Claas has also worked in industry, applying machine learning to accelerate drug discovery. Building on this experience, he is especially interested in generative models for designing novel proteins and small molecules.

Beyond academia, Claas contributes to international exchange and science outreach. He also enjoys doing sports, particularly long-distance running and half marathons.