About me
I am leading the independent research group for Machine Learning in Medical Image Analysis at the University of Tübingen as part of the Cluster of Excellence - Machine Learning for Science.
Please check out our group website for the most up-to-date information!
My main research focus is on developing and applying ML technology for the analysis of medical images. My main research goals are to identify which criteria ML needs to fulfill to be clinically useful and solve the ML problems that prevent us from getting there. Specifically, my group is working on problems like learning from small datasets, robustness and uncertainty quantification, interpretable ML, and generative modelling of large medical datasets.
Short Bio
Before joining the University of Tübingen, I was working in a senior research engineering role at PTC Vuforia, where I focused on research and development of machine learning technology for augmented reality applications. Prior to this, I was a Post-doc at the Biomedical Image Computing Group at ETH Zürich working with Prof. Ender Konukoglu, and before in the Biomedical Image Analysis Lab with Prof. Daniel Rueckert. I completed my PhD in 2016 under the joint supervision of Prof. Andy King and Prof. Daniel Rueckert at King’s College London in the School of Biomedical Engineering & Imaging Sciences (link to PhD thesis). I obtained my Master’s degree in Biomedical Engineering and my Bachelor’s degree in Information Technology and Electrical Engineering from ETH Zürich.
News
- April 2023: PhD student Susu Sun wins the best poster jury award at the Bern Interpretable AI Symposium (BIAS)!
- September 2022: MLMIA team wins MICCAI K2S MR reconstruction and segmentation challenge!
- July 2022: After MIDL 2022 in Zürich, I will be again serving as Program Committee Member for MIDL 2023