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 will join Tongji University (Shanghai, China) as a CS faculty member, and will be recruiting PhD and master's students, as well as postdocs/RAs. You will work closely with our international team from, e.g., Stanford, Harvard, MIT, Columbia, CUHK, HKU, NUS, Tsinghua, Alibaba DAMO, Ant Group, and Tencent. If you are interested in cutting-edge topics in Healthcare AI, feel free to reach out with the email subject [PhD/Master/RA Application]. Applicants from top universities in mainland China are especially encouraged to apply. Before applying, please make sure to review our research directions and requirements on the Prospective Students page.

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 MLLMs Foundation Model
Ying (Dani) Dan

Ying (Dani) Dan (2026-present)

B.Sc.@STU, Ph.D.@CUHK
📚 MICCAI'26

Medical 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