Scholar
Lequan Yu
Google Scholar ID: llXf3wUAAAAJ
Assistant Professor, The University of Hong Kong
Citations & Impact
Citations
18,649
H-index
57
i10-index
114
Publications
20
Co-authors
16
list available
Publications
Resume (English only)
Academic Achievements
- Invited to serve as editor or area chair for several top-tier journals and conferences, including IEEE Transactions on Medical Imaging (TMI), ICLR 2026, CVPR 2026, AAAI 2026, etc. Published numerous high-impact papers in top venues such as Nature Communications, NeurIPS, TPAMI, TMI, ICML, ACL, MICCAI, and more. Some of his research has received best paper awards and honorable mentions.
Research Experience
- Before joining HKU, he was a postdoctoral research fellow at Stanford University.
Education
- Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong in 2019; B.Eng. in Computer Science from Zhejiang University in 2015.
Background
- Currently an assistant professor at The University of Hong Kong, leading the Medical AI Lab. His research lies at the intersection of artificial intelligence and healthcare, focusing on designing advanced computational and machine learning algorithms for biomedical data analysis, particularly medical images, to improve medical decision-making. Specific research directions include: 1) developing multimodal learning algorithms (e.g., multimodal foundation model) to integrate multi-scale biomedical data for disease prevention, diagnosis, prognosis, and treatment design; 2) building real-world learning systems to learn generalizable, trustworthy, and fair representations from imperfect biomedical data; 3) leveraging statistical learning tools (e.g., causal inference) to improve their interpretability, robustness, and safety for healthcare problems.
Miscellany
- Welcomes self-motivated Postdoc/PhD/RA/Interns interested in medical AI to apply to join his lab.
