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 (2023-present)
Ying (Dani) Dan (2026-present)
HK | Boston | NYC
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