Bingjie YAN
Portrait
Logo Hong Kong Polytechnic University
Logo School of Optometry, Hong Kong Polytechnic University

I am a second-year Ph.D. student in the School of Optometry at The Hong Kong Polytechnic University, supervised by Prof. Danli SHI and co-supervised by Prof. Mingguang HE. Before that, I received an M.Eng. degree in Electronic Information from the Institute of Computing Technology, Chinese Academy of Sciences, where I was supervised by Prof. Yiqiang CHEN and Prof. Xinlong JIANG. I also received a B.Eng. degree in Software Engineering from Hainan University.

Research Interests:

  • Medical Agents and Agentic AI: Clinical decision support and autonomous ophthalmic workflows, including EyeAgent, EyeFlow, and SELSM.
  • Multimodal Ophthalmic AI: Vision-language benchmarks, report generation, and ocular world models, including OphthalWeChat, EyeGraphGPT, Buffalo, and EyeWorld.
  • Privacy-Preserving Federated Learning: Cross-silo training and model fusion, including FedEYE, FairFHTL, PrivFusion, and Model Trip.
  • Online Optimization and Learning Systems: Constrained optimization and asynchronous training, including COLDQ and AFL-CS.

My work has received over 800 citations on Google Scholar. Please feel free to contact me via email if you are interested in my research!

Google Scholar GitHub @yyyanbj LinkedIn Curriculum Vitae
Education
  • Hong Kong Polytechnic University
    Hong Kong Polytechnic University
    Ph.D. Student in the School of Optometry
    Sep. 2025 - present
  • Institute of Computing Technology, Chinese Academy of Sciences
    Institute of Computing Technology, Chinese Academy of Sciences
    M.Eng. in Electronic Information
    Sep. 2022 - Jun. 2025
  • Hainan University
    Hainan University
    B.Eng. in Software Engineering
    Sep. 2018 - Jun. 2022
Honors & Awards
  • Institute of Computing Technology Ziqiang International Exchange Scholarship
    2025
  • National Scholarship (3%)
    2024
  • First-Class Scholarship of ICT, CAS
    2024
  • Outstanding Graduate of Hainan University
    2022
  • Awards in various innovation and entrepreneurship competitions
    2019-2022
  • First-Class Scholarship of Hainan University
    2019
Experience
  • Institute of AI Industry Research, Tsinghua University
    Research Intern
    Jul. 2024 - Oct. 2024
  • Hong Kong Baptist University
    Research Assistant
    Jun. 2024 - Jul. 2024
  • FedML Inc.
    Remote Research Intern
    Jun. 2022 - Sep. 2022
Professional Activities
  • Conference Reviewer
    MICCAI (2026), AAAI (2025–2027), ICME (2025)
  • Teaching Assistant
    SO1D02: AI in Healthcare, The Hong Kong Polytechnic University
    1st Sem. 2026/27
Extracurricular Leadership & Service
  • IEEE Hainan University Branch
    President
    Mar. 2021 - Jun. 2022
  • Association of Robotics and Artificial Intelligence
    Co-Founder & Vice President
    Jul. 2020 - Jun. 2022
  • Cyberspace Security Association @Hainan University
    Vice President
    Sep. 2020 - Jun. 2021
News (view all )
2026
The revised version of our preprint "Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks" is available on arXiv!
Jun 27
Jun 05
I attended the Chinese Congress on Image and Graphics (CCIG 2026) in Guangzhou, China!
May 30
May 28
Our free paper "EyeFlow: A Self-Evolving Multi-Agent Framework for Knowledge-Grounded Ophthalmic Diagnosis" is accepted for presentation at the 11th APTOS Symposium!
Mar 30
Selected Publications (view all )
FedEYE: A Scalable and Flexible End-to-end Federated Learning Platform for Ophthalmology
FedEYE: A Scalable and Flexible End-to-end Federated Learning Platform for Ophthalmology

Bingjie YAN*, Danmin CAO*, Xinlong JIANG, Yiqiang CHEN†, Weiwei DAI†, Fan DONG, Wuliang HUANG, Teng ZHANG, Chenlong GAO, Qian CHEN, Zhen YAN, Zhirui WANG (* equal contribution, † corresponding author )

Patterns, Cell Press, JCR-Q1, IF=6.7 (2024)

FedEYE is an end-to-end federated-learning platform that lets ophthalmologists create and deploy collaborative machine-learning projects without programming. It supports flexible deployment while keeping clinical data decentralized.

[Paper] [Bib] [Code] [Page] [Site]

FedEYE: A Scalable and Flexible End-to-end Federated Learning Platform for Ophthalmology

Bingjie YAN*, Danmin CAO*, Xinlong JIANG, Yiqiang CHEN†, Weiwei DAI†, Fan DONG, Wuliang HUANG, Teng ZHANG, Chenlong GAO, Qian CHEN, Zhen YAN, Zhirui WANG (* equal contribution, † corresponding author )

Patterns, Cell Press, JCR-Q1, IF=6.7 (2024)

FedEYE is an end-to-end federated-learning platform that lets ophthalmologists create and deploy collaborative machine-learning projects without programming. It supports flexible deployment while keeping clinical data decentralized.

[Paper] [Bib] [Code] [Page] [Site]

EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmology
EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmology

Danli SHI*, Xiaolan CHEN*, Bingjie YAN*, Weiyi ZHANG, Jiancheng YANG, Ruoyu CHEN, Xinyuan WU, Siyu HUANG, Bowen LIU, Ziyu GAO, Yue WU, Pusheng XU, Senlin LIN, Kai JIN, Xia GONG, Yih Chung THAM, Xiujuan ZHANG, Li DONG, Yuzhou ZHANG, Jason YAM, Guangming JIN, Xiaohu DING, Haidong ZOU, Yalin ZHENG, Zongyuan GE, Mingguang HE† (* equal contribution, † corresponding author )

NEJM AI, accepted; arXiv:2511.09394 (2025) Co-first author

EyeAgent combines an LLM reasoning core with 32 clinical skills and 54 ophthalmic tools for multimodal clinical decision support. Its evaluation includes component studies, expert assessment, and an exploratory human–AI reader study.

[arXiv:2511.09394] [PDF]

EyeAgent: An Agentic AI System for Multimodal Clinical Decision Support in Ophthalmology

Danli SHI*, Xiaolan CHEN*, Bingjie YAN*, Weiyi ZHANG, Jiancheng YANG, Ruoyu CHEN, Xinyuan WU, Siyu HUANG, Bowen LIU, Ziyu GAO, Yue WU, Pusheng XU, Senlin LIN, Kai JIN, Xia GONG, Yih Chung THAM, Xiujuan ZHANG, Li DONG, Yuzhou ZHANG, Jason YAM, Guangming JIN, Xiaohu DING, Haidong ZOU, Yalin ZHENG, Zongyuan GE, Mingguang HE† (* equal contribution, † corresponding author )

NEJM AI, accepted; arXiv:2511.09394 (2025) Co-first author

EyeAgent combines an LLM reasoning core with 32 clinical skills and 54 ophthalmic tools for multimodal clinical decision support. Its evaluation includes component studies, expert assessment, and an exploratory human–AI reader study.

[arXiv:2511.09394] [PDF]

Model Trip: Enhancing Privacy and Fairness in Model Fusion across Multi-Federations for Trustworthy Global Healthcare
Model Trip: Enhancing Privacy and Fairness in Model Fusion across Multi-Federations for Trustworthy Global Healthcare

Qian CHEN, Yiqiang CHEN†, Bingjie YAN, Xinlong JIANG, Xiaojin ZHANG, Yan KANG, Teng ZHANG, Wuliang HUANG, Chenlong GAO, Lixin FAN, Qiang YANG († corresponding author )

ICDE'24, CCF-A (2024) Oral

This work introduces FairFusion, a cross-federation model-fusion method that optimizes utility, privacy, and fairness without additional training. Experiments on three healthcare datasets evaluate its performance across model structures and subgroups.

[Paper] [Bib] [Code]

Model Trip: Enhancing Privacy and Fairness in Model Fusion across Multi-Federations for Trustworthy Global Healthcare

Qian CHEN, Yiqiang CHEN†, Bingjie YAN, Xinlong JIANG, Xiaojin ZHANG, Yan KANG, Teng ZHANG, Wuliang HUANG, Chenlong GAO, Lixin FAN, Qiang YANG († corresponding author )

ICDE'24, CCF-A (2024) Oral

This work introduces FairFusion, a cross-federation model-fusion method that optimizes utility, privacy, and fairness without additional training. Experiments on three healthcare datasets evaluate its performance across model structures and subgroups.

[Paper] [Bib] [Code]

All publications