Dr. Hao Chen  

Assistant Professor

IEEE Senior Member

Room 3524 (via lifts 25-26)
Department of Computer Science and Engineering (Home)
Department of Chemical and Biological Engineering
Division of Life Science
Director of Collaboration Center for Medical and Engineering Innovation, HKUST
Associate Director in Center of Medical Imaging and Analysis, HKUST
The Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong
Email: jhc[at]ust.hk


[SmartX Lab, Google Scholar, HKUST Profile].

*NEW* Positions (including PhDs/RAs/Postdocs/Interns) are available on Large AI Model for Healthcare/Science (particually in Computational Pathology and Multi-omics). Strong self-motivation is preferred (details).
If you are in HKUST and interested in doing research with me, please send me an email.

04/2026 Two papers were accepted in MIA, Congrats to Jin Cheng, Zhengrui and Xuefeng!
03/2026 Two papers were accepted in ICLR 2026, Congrats to Linshan and Conghao!
02/2026 One paper was accepted by Nature Biomedical Engineering, Congrats to Zelin, Xi and Zhuoyao!
02/2026 One paper was accepted by CVPR 2026, Congrats to Shaochen and Yuting!
02/2026 Invited to join the MICCAI SiG Computational Pathology Board!
02/2026 One paper was accepted by npj Digital Medicine, Congrats to Yang Shu!
01/2026 One paper was accepted by Nature Communications, Congrats to Jiabo and Wenqiang!
01/2026 One paper was accepted by Nature Biomedical Engineering, Congrats to Yuxiang, Sunan and Yequan!
01/2026 Congrats to Dr Lin Yi (Alumni of SmartX Lab) winning 2025 AMIA Edward H. Shortliffe Doctoral Dissertation Award (First Prize) and 2024-2025 HKUST CSE Best PhD Dissertation Award (Honorable Mention)!

Biography

Prof. Hao Chen is an Assistant Professor at Department of Computer Science and Engineering, Department of Chemical and Biological Engineering and Division of Life Science, Hong Kong University of Science and Technology (HKUST). He leads the SmartX Lab focusing on large and trustworthy AI for healthcare. He serves as Director of Collaboration Center for Medical and Engineering Innovation, HKUST. He received the Ph.D. degree from The Chinese University of Hong Kong (CUHK) in 2017. He has 200+ publications in top-tier journals and conferences including Nature Biomedical Engineering, Nature Machine Intelligence, Lancet Digital Health, IEEE-TPAMI, CVPR, etc. He also has rich industrial research experience and holds a dozen of patents in AI and medical image analysis. He received several premium awards such as Asian Young Scientist Fellowship, MICCAI Young Scientist Impact Award, and several best paper awards. He serves as the Associate Editor of multiple journals including IEEE RBME, TMI, TNNLS, JBHI, etc. He also led the team winning 15 medical grand challenges.

Research Interests

Large and Trustworthy AI (e.g., Generalizability, Multimodal, Explainability, Privacy) for Biomedcine, Computational Pathology, Deep Learning, Computer-Assisted Intervention/XR, Bioinformatics, etc.

Selected Awards

06/2025 HKUST Engineering Young Investigator Research Award 2024-25
2022-2025 UROP Faculty Research Award
2024-2025 Highly Cited Researcher by Clarivate
2022-2024 Top 2% of the World's Top Scientists" in both "Long-term Career Impact" and "Annual Impact" lists
08/2024 Best Paper Award of TAI4H Workshop, IJCAI 2024
10/2023 The First Prize of Beijing Science and Technology Award
10/2023 OMIA-X Prestigious Achievement Award
06/2023 Ministry of Education Higher Education Outstanding Scientific Research Output Awards (Second Author)
05/2023 The Asian Young Scientist Fellowship (AYSF) 2023
10/2019 MICCAI Young Scientist Impact Award
10/2019 Forbes China 30 under 30
08/2018 CUHK Faculty Outstanding Thesis Award
09/2017 Best Paper Award of Medical Image Analysis-MICCAI 2017
09/2016 MIAR Best Paper Award, Switzerland
03/2013 Hong Kong PhD Fellowship
10/2012 Gold Medal, Beihang University

Selected Publications [Full publication list is available in Google Scholar]

  • An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision-Language Pre-training.
    Yuxiang Nie*, Sunan He*, Yequan Bie*, Yihui Wang, Zhixuan Chen, Shu Yang, Zhiyuan Cai, Hongmei Wang, Xi Wang, Luyang Luo, Mingxiang Wu, Xian Wu, Ronald Cheong Kin Chan, Yuk Ming Lau, Yefeng Zheng, Pranav Rajpurkar, Hao Chen#.
    Nature Biomedical Engineering 2026

  • GSCo: Towards Generalizable AI in Medicine via Generalist-specialist Collaboration.
    Sunan He*, Yuxiang Nie*, Hongmei Wang, Shu Yang, Yihui Wang, Zhiyuan Cai, Zhixuan Chen, Yingxue Xu, Luyang Luo, Huiling Xiang, Xi Lin, Mingxiang Wu, Yifan Peng, George Shih, Ziyang Xu, Xian Wu, Qiong Wang, Ronald Cheong Kin Chan, Varut Vardhanabhuti, Winnie Chiu Wing Chu, Yefeng Zheng, Pranav Rajpurkar, Kang Zhang, Hao Chen#.
    Nature Biomedical Engineering 2025

  • A Generalizable Pathology Foundation Model using A Unified Knowledge Distillation Pretraining Framework.
    Jiabo Ma*, Zhengrui Guo*, Fengtao Zhou, Yihui Wang, Yingxue Xu, Jinbang Li, Fang Yan, Yu Cai, Zhengjie Zhu, Cheng Jin, Yi Lin, Xinrui Jiang, Chenglong Zhao, Danyi Li, Anjia Han, Zhenhui Li, Ronald Cheong Kin Chan, Jiguang Wang, Peng Fei, Kwang-Ting Cheng, Shaoting Zhang#, Li Liang#, Hao Chen#.
    Nature Biomedical Engineering 2025

  • A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model.
    Yingxue Xu*, Yihui Wang*, Fengtao Zhou, Jiabo Ma, Shu Yang, Huangjing Lin, Xin Wang, Jiguang Wang, Li Liang, Anjia Han, Ronald Cheong Kin Chan, Hao Chen#.
    Nature Communications 2025

  • A Large Model for Non-invasive and Personalized Management of Breast Cancer from Multiparametric MRI.
    Luyang Luo, Mingxiang Wu, Mei Li, Yi Xin, Qiong Wang, Varut Vardhanabhuti, Winnie CW Chu, Zhenhui Li#, Juan Zhou#, Pranav Rajpurkar, Hao Chen#.
    Nature Communications 2025

  • Large-Scale 3D Medical Image Pre-training with Geometric Context Priors.
    Linshan Wu, Jiaxin Zhuang, Hao Chen#.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2025

  • Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction. Spotlight
    Yilan Zhang*, Yingxue Xu*,Jianqi Chen, Fengying Xie, Hao Chen#.
    ICLR 2024

  • Multimodal Optimal Transport-based Co-Attention Transformer with Global Structure Consistency for Survival Prediction.
    Yingxue Xu, Hao Chen.
    ICCV 2023

  • DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation. Winner of MICCAI GlaS Challenge
    Hao Chen, Xiaojuan Qi, Lequan Yu, Pheng-Ann Heng.
    IEEE Computer Vision and Pattern Recognition (CVPR 2016)

  • Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks.
    MICCAI Young Scientist Publication Impact Award
    Hao Chen, Qi Dou, Dong Ni, Jie-Zhi Cheng, Jing Qin, Shengli Li, Pheng-Ann Heng.
    MICCAI 2015

    • Professional Service

    Editorial Board Member
    Associate Editor of IEEE Reviews in Biomedical Engineering (RBME)
    Associate Editor of IEEE Transactions on Medical Imaging (TMI)
    Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
    Associate Editor of IEEE Journal of Biomedical and Health Informatics (JBHI)
    Program Committee
    MICCAI SiG Computational Pathology Board Member
    Area Chair of ICLR 2025-2026, CVPR 2024-2026, ACM Multimedia 2024, IPCAI 2024, MIDL 2022-2025, MICCAI 2021-2023 and 2025-2026, IEEE ISBI 2022
    Program Chair, Workshop on Trustworthy Artificial Intelligence for Healthcare (TAI4H), IJCAI 2024
    Program Chair, Workshop on Trustworthy Machine Learning for Healthcare (TML4H), ICLR 2023

    Teaching

    COMP5423 Deep Learning for Medical Image Analysis, Spring 2024-2026
    COMP4421 Image Processing, Fall 2021-2025
    COMP6211H Deep Learning in Medical Image Analysis, Spring 2022, Spring 2023