Dr. Hao Chen  

Assistant Professor

IEEE Senior Member

Room 3517 (via lifts 25-26)
Department of Computer Science and Engineering (Home)
Department of Chemical and Biological Engineering
The Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong
Email: jhc[at]ust.hk


[Smart Lab,Google Scholar].

*NEW* Positions (including PhDs/RAs/Postdocs/Interns) are available on Machine Learning in Medical Imaging and Analysis. Strong self-motivation is preferred (details).
If you are HKUST students and interested in doing research with me, please send me an email.


11/22 Three papers were accepted in Medical Image Analysis.
10/22 Ranked Top 2% of Scientists on Stanford List.
08/22 Honored to serve as Associate Editor of IEEE JBHI.
08/22 Elevation to IEEE Senior Member.
07/22 Two papers were accepted in Radiology AI.
05/22 Six papers were accepted in MICCAI 2022 (five are early accept).

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. He also led the team winning 15+ grand challenges, such as RSNA Challenge on Pneumonia Screening, etc.

Research Interests

Trustworthy AI, Medical Image Analysis, Deep Learning, Computer Vision, Multimodal Learning, Computational Pathology, Bioinformatics, etc.

Selected Awards

10/22 Ranked 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

Selected

◎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]

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

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

  • ORF-Net: Deep Omnisupervised Rib Fracture Detection from Chest CT Scans.
    Chai Zhizhong, Lin Huangjing, Luo Luyang, 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
    Program Committee
    Area Chair of MICCAI 2022, MICCAI 2021, MIDL 2022, IEEE ISBI 2022
    Senior PC of AAAI 2022, PC of AAAI 2021, IJCAI-ECAI 2022
    Organizing Committee of Diabetic Retinopathy Analysis Challenge, 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 Methods
    IEEE Transactions on Pattern Recognition and Machine Intelligence (TPAMI)
    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, NeuIPS, CVPR, IROS, IPCAI, ISBI, MIDL, MICCAI-COMPAY, MICCAI-AE-CAI

    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

    COMP4421 Image Processing, Fall 2022
    COMP6211H Deep Learning in Medical Image Analysis, Spring 2022
    COMP4421 Image Processing, Fall 2021