Dr. Xia Li is a tenure-track Associate Professor and PhD supervisor. He received his master’s degree from Peking University and obtained his PhD from ETH Zurich, where he subsequently continued his postdoctoral research. His research focuses on interdisciplinary medical AI, with the goal of enabling image-guided precision radiotherapy, particularly proton therapy, through advanced imaging algorithms. Specifically, his work investigates machine learning and computer vision theories, aiming to accelerate and advance fundamental medical image analysis algorithms and apply them to fast and precise cancer radiotherapy. Dr. Li has published more than 40 papers in leading journals and conferences across computer vision (NeurIPS, CVPR, ICCV, ECCV) medical image analysis (Medical Image Analysis, MICCAI) and radiation oncology (Rad. & Onc., phiRO). He has served as an Area Chair for ICML and NeurIPS. He has been listed among the world’s top 2% scientists, received the ICCR 2024 Rising Star Award, and has accumulated over 5,000 citations on Google Scholar. He won the third place and the Innovation Award in the COCO International Challenge. Group website: medapt.cn.

2017-2020 Master in Applied Computer Technology, Peking University

2020-2024 Ph.D. in Computer Science, ETH Zurich

2022-2024 Guest Scientist in Center for Proton Therapy, Paul Scherrer Institut
2025-2026 Postdoc in ETH Zurich

Machine learning theoray, computer vision algorithm, medical image analysis, image-guided proton therapy

Jihe L, Xiang L, Fabian Z, Xixin C, Ye Z, Joachim B, Xia L. Gaussian Representation for Deformable Image Registration. Physics and Imaging in Radiation Oncology (PhiRO), 2025

Xia L, Fabian Z, Muheng L, Damien W, Antony L, Joachim B, Ye Z. Neural Graphics Primitives-based Deformable Image Registration for On-the-fly Motion Extraction. International Conference on the use of Computers in Radiation therapy (ICCR), 2024. ICCR Rising Star Award

Xia L, Renato B, Gabriel M, Barbara B, Damien W, Antony L, Joachim B, Ye Z. Uncertainty-aware MR-based CT synthesis for robust proton therapy planning of brain tumour. Radiotherapy and Oncology (Green Journal), 2024

Xia L, Zhisheng Z, Jianlong W, Yibo Y, Zhouchen L, Hong L. Expectation Maximization Attention Networks for Semantic Segmentation. International Conference in Computer Vision (ICCV), 2019. Google Scholar cited by 1200+

Xia L, Jianlong W, Zhouchen L, Hong L, Hongbin Z. Recurrent Squeeze-and-Excitation Net for Single Image Deraining. European Conference on Computer Vision (ECCV), 2018. Google Scholar cited by 800+=