Ruisheng Su

Ruisheng Su is an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), part of the Medical Image Analysis group (IMAG/e). He leads the SWITCH stroke workshop at MICCAI and collaborates with institutions like Erasmus MC, University of Bern, and Philips. His research focuses on deep learning for neurovascular image/video analysis, including applications in stroke, aneurysms, and image-guided interventions. He aims to develop trustworthy AI methodologies for medical professionals.

Academic Background: Joined TU/e's IMAG/e group in 2024. Previously, he was a post-doctoral researcher at Erasmus MC’s Biomedical Imaging Group Rotterdam, specializing in AI for endovascular stroke interventions. Before 2020, he worked as a software engineer at ASML and a research scientist at Philips Research. Holds a Master’s in Electrical Engineering from Technical University of Munich (TUM), with thesis work at Philips on patient activity monitoring.

Research Highlights: Active in developing AI-based techniques for image registration, segmentation, and quantification in neurovascular diseases. Key projects include CAVE (artery/vein segmentation), AngioMoCo (motion correction), and autoTICI (automatic reperfusion scoring). His work contributes to UN Sustainable Development Goals in health and well-being.

Awards: Van Leersum Grant (2022) for visiting Harvard Medical School and DAAD AiNet Fellowship (2023) for collaborations in Berlin/Munich.

Teaching: Courses include 'Medical Image Analysis' spanning from 2013 to present and ongoing courses starting 2024.