Generative Machine Learning Models in Medical Image Computing
A comprehensive exploration of generative modeling techniques tailored to the unique demands of medical imaging.
Zeju Li (He/Him)
Associate Professor
College of Biomedical Engineering
Fudan University
Office Location
Room C2008, No. 2 Interdisciplinary Research Building
Jiangwan Campus, Fudan University
Shanghai, China
Email
📧 Work: zejuli(at)fudan.edu.cn
📧 Personal: lizeju79(at)sina.cn
About Me
Zeju Li’s research focuses on machine learning and its applications in medical image processing, with an emphasis on neuroimaging analysis and addressing clinical problems.
He has published over 30 peer-reviewed publications, many of which have been published in top-tier journals and conferences including TMI and MICCAI.
His work has garnered over 4,000 citations on Google Scholar. He has won championships in the Huawei AI Challenge and the MICCAI Challenge, and serves as an area chair for conferences such as MICCAI and MIDL.
Zeju was a Post-Doctoral Researcher in the FMRIB Analysis Group at the University of Oxford before joining Fudan in February 2025.
He obtained his PhD in Computing from the BioMedIA Group. He spent time at the Institute of Computing Technology and Huawei Noah’s Ark Lab (London).
- Ph.D. in Computing ∙ Imperial College London ∙ 2023
- M.S. in Biomedical Engineering ∙ Fudan University ∙ 2018
- B.S. in Electronic Engineering ∙ Fudan University ∙ 2015
To Prospective Student: I have multiple positions available (PhD, Master’s, interns, and Post-doc) at Fudan University. If you are interested, please read this). If you cannot read Chinese but are still interested, feel free to contact me directly.
李泽榉，现复旦大学生物医学工程与技术创新学院青年研究员，获国家高层次青年人才项目和上海市高层次青年人才项目资助。 他于2023年1月在帝国理工学院Computing系获得博士学位，此前是牛津大学FMRIB Centre的博士后研究员。李泽榉的研究方向集中在机器学习及其在医学图像处理中的应用，侧重神经影像分析和解决临床问题，其发表学术论文30余篇，其中多篇发表于TMI和MICCAI；Google Scholar引用超过4000次，曾获得华为AI挑战赛和MICCAI挑战赛冠军，并担任MICCAI/MIDL等领域会议的领域主席。
