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
The Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong
Email: jhc[at]ust.hk


[Smart Lab,Google Scholar,HKUST Profile].

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

02/2024 One paper was accepted in CVPR 2024.
01/2024 One paper was accepted in IEEE Reviews on Biomedical Engineering and one was in Patterns (Cell Press).
01/2024 Invited to serve as Area Chair for MIDL 2024.
01/2024 Invited to serve as Area Chair for the 32nd ACM International Conference on Multimedia.
01/2024 One paper was accepted in ICLR (spotlight) and One in IEEE TMI.
01/2024 One paper was accepted in Nature Communications and One in IEEE TMI.
12/2023 Two papers were accepted in AAAI 2024.
11/2023 Two papers were accepted in IEEE-TMI and one paper was accepted in Nature Medicine.
10/2023 Ranked 2023 Top 2% of the World's Top Scientists" in both "Long-term Career Impact" and "Annual Impact" lists.
10/23 I received the OMIA-X Prestigious Achievement Award.
08/23 One paper was accepted in Medical Image Analysis.
07/23 Two papers were accepted in ICCV 2023.
07/23 Six papers were accepted in MICCAI 2023.
06/23 We are organizing a Special Issue on Foundation Models for Healthcare in Connected Health And Telemedicine. Welcome to submit your manuscripts.
06/23 Invited to serve as Area Chair in CVPR 2024.
06/23 We are organizing a Special Issue on Trustworthy Machine Learning for Health Informatics in IEEE-JBHI and welcome to submit your manuscripts.
05/23 I am honored to receive The Asian Young Scientist Fellowship (AYSF) 2023.
05/23 Two UG students won the UROP Awards (one is First Runner-up and One is Second Runner-up). Congrats to Siyu and Weiwen!
04/23 One paper was accepted in IJCAI 2023 and one was accepted in Medical Image Analysis.
04/23 We are organizing the 2023 MICCAI challenge on Myopic Maculopathy Analysis Challenge.
04/23 We are organizing the 2023 MICCAI Workshops on Ophthalmic Medical Image Analysis (OMIA-X) and Multiscale Multimodal Medical Imaging (MMMI).
04/23 We are organizing the 2023 ICCV Workshop on Computer Vision for Automated Medical Diagnosis.
03/23 Three papers were accepted in CVPR 2023.
02/23 One paper was accepted in IPMI 2023.
01/23 Invited to serve as Area Chair in MICCAI 2023 and MIDL 2023.
12/22 We are organizing 2023 ICLR Workshop on Trustworthy Machine Learning in Healthcare.
11/22 Three papers were accepted in Medical Image Analysis.

Biography

Dr Chen is an Assistant Professor at Department of Computer Science and Engineering and Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology (HKUST). He leads the Smart Lab focusing on AI in healthcare and serves as Associate Director in Center of Medical Imaging and Analysis, HKUST. He obtained Hong Kong PhD Fellowship in 2013 and received PhD degree from The Chinese University of Hong Kong (CUHK). He was a postdoctoral research fellow in CUHK and a visiting scholar in Utrecht University Medical Center previously. He also has rich industrial research experience including Siemens and co-founded a startup. He holds a dozen of patents in AI and medical image analysis. He received several premium awards including Best Paper Award in MIAR 2016, CUHK Faculty Outstanding Thesis Award in 2017, MICCAI Young Scientist Publication Impact Award in 2019, Forbes China 30 under 30 and Asian Young Scientist Fellowship. He also led the team winning 15+ grand challenges, such as RSNA Challenge on Pneumonia Screening, etc.

Research Interests

Trustworthy AI (e.g., Generalizability, Multimodal, Explainability, Privacy) for Healthcare, Medical Image Analysis, Deep Learning, Computer-Assisted Intervention, Bioinformatics, etc.

Selected Awards

10/2023 The First Prize of Beijing Science and Technology Award
10/2023 2023 Top 2% of the World's Top Scientists" in both "Long-term Career Impact" and "Annual Impact" lists
10/2023 OMIA-X Prestigious Achievement Award
10/2023 IEEE TMI Distinguished Reviewer Award (Platinum Level)
06/2023 Ministry of Education Higher Education Outstanding Scientific Research Output Awards (Second Author)
05/2023 The Asian Young Scientist Fellowship (AYSF) 2023
05/2023 UROP Faculty Research Award
01/2023 Distinguished Reviewers Award of CMIG in recognition of distinguished service to the journal and its authors
10/2022 Top 2% of Scientists on Stanford List
08/2022 IEEE TMI Distinguished Reviewer Award (Gold Level)
06/2022 UROP Faculty Research Award
02/2022 Computerized Medical Imaging and Graphics (CMIG) Outstanding Reviewer Award
07/2021 World Artificial Intelligence Conference (WAIC) SAIL Award
02/2021 IEEE TMI Distinguished Reviewer Award (Gold Level)
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 Invited Talks

◎2023-08 Advance Medical Imaging with Vision and Language Models, IJCAI-2023 Session on Medical Large Models, Symposium on Large Language Models (LLM 2023), Macao.
◎2023-08 Explainable Artificial Intelligence for Healthcare: Where Are We Now? International Conference on AI in Medicine. Singapore.
◎2023-05 Artificial Intelligence for COVID-19 Lesion Quantification from Radiology Images. APEC Workshop. Indonesia.
◎2022-11 Towards Trustworthy AI for Medical Imaging and Analysis. Keynote, AICI Forum, Australia.
◎2022-10 Label-Efficient Deep Learning for Medical Image Analysis. International School on Deep Learning, Sweden.
◎2022-08 Towards Trustworthy AI for Medical Imaging and Analysis. SenseTime/CUHK Medicine Joint Seminar.
◎2022-02 Not-so-supervised Deep Learning for Medical Image Analysis. MICS China
◎2021-12 Artificial Intelligence in Medical Imaging and Analysis: Progress, Promises and Pitfalls. HKSTP X HKMA CME Lecture
◎2021-02 Deep Learning for Large-scale Computational Pathology. Hong Kong Pathology Forum
◎2020-01 PathLAKE Masterclass: Data Science for Computational Pathology, UK
◎2019-10 How Deep Learning Can Help in the Radiology Diagnosis? Keynote in 2019 Macao Radiology Association Annual Scientific Meeting, China
◎2019-9 How Deep Learning Can Help in the Clinical Diagnosis? Create, Manage, and Deploy in the Clinical Workflow. Keynote in MICCAI CLIP Workshop, China
◎2019-3 AI in OCT: What is 3D Deep Learning? Asia-Pacific Academy of Ophthalmology Congress. Bangkok, Thailand
◎2016-07 Deep Learning for Histopathology Image Analysis, Medical Vision Workshop in CVPR 2016 (Las Vegas)
◎2016-01 Deep Learning in Medical Imaging (National Institute of Health, Washington)

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

  • OvcaFinder: Development and Validation of an Interpretable Model Integrating Multimodal Information for Improving Ovarian Cancer Diagnosis: A Retrospective Study.
    Huiling Xiang*, Yongjie Xiao*, Fang Li*, Chunyan Li, Lixian Liu, Tingting Deng, Cuiju Yan, Fengtao Zhou, Xi Wang, Jinjing Ou, Qingguang Lin, Ruixia Hong, Lishu Huang, Luyang Luo, Huangjing Lin, Xi Lin#, Hao Chen#.
    Nature Communications 2024

  • 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

  • Cross-Modal Translation and Alignment for Survival Analysis.
    Fengtao Zhou, Hao Chen.
    ICCV 2023

  • DoNet: Deep De-overlapping Network for Microscopy Instance Segmentation.
    Hao Jiang, Rushan Zhang, Yanning Zhou, Yumeng Wang, Hao Chen.
    CVPR 2023

  • Image Quality-aware Diagnosis via Meta-Knowledge Co-Embedding.
    Haoxuan Che, Siyu Chen, Hao Chen.
    CVPR 2023

  • Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentation.
    Yi Lin, Dong Zhang, Xiao Fang, Yufan Chen, KT Cheng, Hao Chen.
    IPMI 2023

  • InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance Segmentation.
    Yi Lin, Zeyu Wang, KT Cheng, Hao Chen.
    MICCAI 2022

  • Learning Robust Representation for Joint Grading of Ophthalmic Diseases via Adaptive Curriculum and Disentanglement. MICCAI Travel Award
    Haoxuan Che, Haibo Jin, Hao Chen.
    MICCAI 2022

  • ORF-Net: Deep Omnisupervised Rib Fracture Detection from Chest CT Scans.
    Zhizhong Chai, Huangjing Lin, Luyang Luo, Pheng-Ann Heng, Hao Chen.
    MICCAI 2022

  • OXnet: Omni-supervised Thoracic Disease Detection from Chest X-rays.
    Luyang Luo*, Hao Chen*,Yanning Zhou, Huangjing Lin, Pheng-Ann Heng.
    MICCAI 2021

  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images. Oral
    Yanwen Li*, Luyang Luo*,Huangjing Lin, Hao Chen, Pheng-Ann Heng.
    MICCAI 2021

  • Dual-path Network with Synergistic Grouping Loss and Evidence Driven Risk Stratification for Whole Slide Cervical Image Analysis. One of largest cervical screening WSI datasets
    Huangjing Lin*, Hao Chen*,, Xi Wang, Qiong Wang, Liansheng Wang, Pheng-Ann Heng.
    Medical Image Analysis (MIA), 2021

  • Potentials of AI in Medical Image Analysis in Gastroenterology and Hepatology.
    Hao Chen, Joseph JY Sung*.
    Journal of Gastroenterology and Hepatology, 2021

  • Towards a New Generation of Artificial Intelligence in China. WAIC SAIL Award
    Fei Wu, Cewu Lu, Mingjie Zhu, Hao Chen, Jun Zhu, Kai Yu, Lei Li, Ming Li, Qifeng Chen, Xi Li, Xudong Cao, Zhongyuan Wang, Zhengjun Zha, Yueting Zhuang, Yunhe Pan*
    Nature Machine Intelligence, 2021

  • H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes.
    Xiaomeng Li, Hao Chen*, Xiaojuan Qi, Qi Dou, Chi-Wing Fu, Pheng-Ann Heng.
    IEEE Transactions on Medical Imaging (TMI), 2018. ESI Highly Cited Paper and Winner of LiTS Challenge

  • Detection of Glaucomatous Optic Neuropathy with Spectral-domain Optical Coherence Tomography: a Retrospective Training and Validation Deep-learning Analysis. Journal Cover Page
    An Ran Ran, Carol Y Cheung, Xi Wang, Hao Chen, Lu-yang Luo, et al.
    Lancet Digital Health, 2019

  • VoxResNet: Deep Voxelwise Residual Networks for Brain Segmentation from 3D MR Images. Most Cited Articles
    Hao Chen, Qi Dou, Lequan Yu, Jing Qin, Pheng-Ann Heng
    NeuraoImage, 2018

  • Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women with Breast Cancer. First Large-scale WSI Study
    Bejnordi B E, Veta M, Van Diest P J, Hao Chen, Huangjing Lin, et al.
    JAMA, 2017

  • Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma.
    Editorial Comment: Will AI Improve Tumor Delineation Accuracy for Radiation Therapy?
    Li Lin*, Qi Dou*, Yue-Ming Jin, Guan-Qun Zhou,..., Hao Chen, Ying Sun.
    Radiology, 2019

  • 3D Deeply Supervised Network for Automated Segmentation of Volumetric Medical Images. MIA-Elsevier Best Paper Award
    Qi Dou, Lequan Yu, Hao Chen, Yueming Jin, Xin Yang, Jing Qin, Pheng-Ann Heng.
    Medical Image Analysis (MIA), 2017

  • 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)

  • 3D Fully Convolutional Networks for Intervertebral Disc Localization and Segmentation. Best Paper Award
    Hao Chen*, Qi Dou*, Xi Wang, Jing Qin, Jack CY Cheng, Pheng-Ann Heng
    International Conference on Medical Imaging and Augmented Reality (MIAR 2016)

  • Mitosis Detection in Breast Cancer Histology Images via Deep Cascaded Networks. Oral
    Hao Chen, Qi Dou, Xi Wang, Jing Qin, Pheng Ann Heng.
    The Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)

  • Deep Contextual Networks for Neuronal Structure Segmentation. Oral
    Hao Chen*, Xiaojuan Qi*, Jie-Zhi Cheng, Pheng-Ann Heng.
    The Thirtieth AAAI Conference on Artificial Intelligence (AAAI 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
  • Automatic Localization and Identification of Vertebrae in Spine CT via a Joint Learning Model with Deep Neural Networks. MICCAI Travel Award
    Hao Chen*, Chiyao Shen*, Jing Qin, Dong Ni, Lin Shi, Jack CY Cheng, Pheng-Ann Heng.
    MICCAI 2015

    • Professional Service

    Editorial Board Member
    Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
    Associate Editor of IEEE Journal of Biomedical and Health Informatics (JBHI)
    Associate Editor of Medical Physics
    Associate Editor of Computerized Medical Imaging and Graphics (CMIG)
    Associate Editor of Neurocomputing
    Associate Editor of Frontiers in Artificial Intelligence
    Associate Editor of Frontiers in Big Data
    Guest Editor on Trustworthy Machine Learning for Health Informatics in IEEE-JBHI.
    Program Committee
    Area Chair of CVPR 2024, ACM Multimedia 2024, IPCAI 2024, MIDL 2024， MICCAI 2023, MICCAI 2022, MICCAI 2021, MIDL 2023, MIDL 2022, IEEE ISBI 2022
    Senior PC of AAAI 2022, PC of AAAI 2021, IJCAI 2022, IJCAI 2023
    Program Chair, Workshop on Trustworthy Machine Learning for Healthcare (TML4H), ICLR 2023
    Workshop on Computer Vision for Automated Medical Diagnosis, ICCV 2023
    Workshop on Ophthalmic Medical Image Analysis (OMIA-X), MICCAI 2023
    Workshop on Multiscale Multimodal Medical Imaging (MMMI), MICCAI 2023
    Challenge on Myopic Maculopathy Analysis, MICCAI 2023
    Challenge on Diabetic Retinopathy Analysis, MICCAI 2022
    Technical Commitee Member of MIDL (2022-2024)
    Vice President of Steering Committee of the HKSTP Startups Alumni Association (2022-2024)
    Hong Kong BioMedical Technology Development Advisory Panel Member (2022-2024)
    Membership
    IEEE Senior Member, MICCAI Member, AAAI Member
    Regular Journal Reviewer
    Nature Medicine
    Nature Methods
    IEEE Transactions on Pattern Recognition and Machine Intelligence (TPAMI)
    Nature Machine Intelligence
    Nature Communications
    Medical Image Analysis (MIA)
    IEEE Transactions on Medical Imaging (TMI)
    npj Digital Medicine
    Journal of Clinical Investigation
    NeuroImage
    IEEE Transactions on Cybernetics
    IEEE Transactions on Image Processing (TIP)
    IEEE Transactions on Biomedical Engineering (TBME)
    IEEE Reviews in Biomedical Engineering
    EBioMedicine
    Engineering
    JAMA Network Open
    IEEE Computational Intelligence Magazine
    IEEE Journal of Biomedical and Health Informatics
    Artificial Intelligence In Medicine
    Knowledge-Based Systems
    Machine Learning for Biomedical Imaging
    Patter Recognition
    Expert Systems with Applications
    International Journal of Computer Assisted Radiology and Surgery (IJCARS)
    Regular Conference Reviewer
    AAAI, IJCAI, MICCAI, IPMI, NeuIPS, CVPR, IROS, IPCAI, ISBI, MIDL

    Selected Challenges

    ◎2021/12 Winner in 2021 Tencent AI Medical Innovation System (AIMIS) Challenge
    ◎2020/09 Top3 in MICCAI 2020 RibFrac Challenge: Rib Fracture Detection and Classification
    ◎2018/11 Top5 in Kaggle RSNA Pneumonia Detection Challenge
    ◎2018/09 Winner on the MICCAI 2018 Multi-organ Nuclei Segmentation Challenge
    ◎2016/10 Winner on the MICCAI 2016 M2CAI Challenge on Surgical Workflow Recognition
    ◎2016/10 Winner on the MICCAI 2016 IVD Localization and Segmentation from 3D Multi-modality Images
    ◎2016/10 State-of-the-art record was achieved from our team on Cancer Metastasis Detection in Lymph Node
    ◎2016/10 CU_DL with 3D Deep Learning method placed 1st on MICCAI 2013 Brain Segmentation from MR Images  
    ◎2016/05 CUMedVision won the 1st place in 2016 ISBI LUNA (lung nodule detection from CT images) Challenge.
    ◎2016/05 CUMedVision won the 1st place in 2016 ISBI Skin Lesion Classification Challenge out of 20+ teams.
    ◎2015/10 MICCAI Gland Segmentation Challenge. CUMedVision won the 1st place out of 13 teams. [NVIDIA news]
    ◎2015/10 2015 MICCAI Nuclei Segmentation Challenge. Our team (CUMedVision) won the 1st place.
    ◎2015/10 2015 MICCAI Endoscopic Vision Challenge. Our team (CUMedVision) won the 1st place on Polyp Detection from videos in terms of overall F1 score and detection latency.
    ◎2015/10 Our team won the 1st place in 2015 MICCAI IVD Localization Challenge.
    ◎2015/10 2012 ISBI Challenge: Segmentation of neuronal structures in Electron Microscopy (EM) stacks. Our team (CUMedVision) placed 1st on the neuronal structure segmentation out of 38 teams. [Leader board]
    ◎2014/10 MITOS-ATYPIA-14 challenge, 2014. Our team won the 1st place among the 17 teams on mitosis detection.

    Teaching

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