*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.

News

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. Hao Chen is an Assistant Professor at the 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, Computational Pathology, Bioinformatics, etc.

Selected Awards

◎10/2022 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 Talks

◎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).

Publications

Full publication list is available in Google Scholar.

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