NEXZ AI Lab

We work on building affordable, robust, and scalable medical AI co-pilots that can trustworthily perceive, reason, reflect, and act in complex clinical environments, with recent focus on world models, multimodal foundation models, continual learning, self-evolving AI, label-efficient learning, and agentic AI systems for healthcare applications.

Note: I am an incoming tenured faculty member at a top university in Shanghai (2027 Fall) and multiple positions of Ph.D./master students (2027 Fall) and Postdocs/RA (anytime) are available. You will work with our international team from, e.g., Stanford, Harvard, MIT, Columbia, CUHK, HKU, NUS, Tsinghua, Alibaba DAMO, and Tencent. If you are interested in cutting-edge topics in Healthcare AI or general AI (e.g., AI Agents, World Models, foundation models, Continual Learning), feel free to reach out.

Ph.D. Students

Xinyao (Yoyo) Wu

Xinyao (Yoyo) Wu (2023-present)

B.Sc. and M.S.@Imperial College London, Ph.D.@CUHK
📚 MICCAI'24-25, MedIA'25, ICLR'26

Continual Learning Medical VLM Foundation Model
Ying (Dani) Dan

Ying (Dani) Dan (2026-present)

B.Sc.@STU, Ph.D.@CUHK
📚 MICCAI'26

Clinical World Model Stroke Foundation Model

Former Mentees

  • Wentao Pan (M.S. @ Tsinghua, 2021-2024): Now Ph.D. candidate @ CUHK EE (HKPFS) /📚: TMI'22, PR'25
  • Yinuo Wang (Ph.D. candidate @ BUAA, 2024-2025) /📚: CMIG'25
  • Ritvik Pulya (High School Intern @ Harvard, 2019-2020): JHU'25 -> Vandy Med MA /📚: MICCAI'20