Lequan Yu

Assistant Professor

Rm 226, Run Run Shaw Building
Department of Statistics and Actuarial Science
The University of Hong Kong
Hong Kong

Email: lqyu [at] hku [dot] hk


I am an assistant professor at The University of Hong Kong, where I direct the Medical AI Lab. My research lies at the intersection of artificial intelligence and healthcare. We are dedicated to designing advanced computational and machine learning algorithms for biomedical data analysis, primarily focusing on medical images, to improve medical decision-making. Specifically, we focus on: 1) developing multimodal learning algorithms (e.g., multimodal foundation model) to integrate multi-scale biomedical data for disease prevention, diagnosis, prognosis, and treatment design; 2) building real-world learning systems to learn generalizable, trustworthy, and fair representations from imperfect medical data; and 3) developing causality-driven learning algorithms to improve their interpretability and safety for healthcare problems.

Before joining HKU, I was a postdoctoral research fellow at Stanford University, working with Prof. Lei Xing. I obtained my Ph.D. degree in CSE, The Chinese University of Hong Kong in 2019 and the B.Eng degree in CS, Zhejiang University in 2015.

[New in Dec 2023] We have Postdoc/RA openings in multimodal learning and computational pathology. Please contact me if you are interested in this opportunity (Details).

We are looking for self-motivated Postdoc/PhD/RA/Interns, who are interested in medical AI, multimodal learning, computational pathology, and biomedical informatics. Welcome to drop me an email with your CV and transcripts.



Selected Publications [Google Scholar]






Before 2020


Current Students:
Howard Tsai Hor Chan (BSc at HKU)(PhD Student, 2021-)
Fuying Wang (BEng at Tsinghua)(PhD Student, 2021-)
Weiqin Zhao (BEng at Beihang)(PhD Student, 2021-)
Lingting Zhu (BEng at ZJU)(PhD Student, 2021-) (HKU-PS)
Zhenchao Jin (MPhil at USTC)(PhD Student, 2022-)
Zhuo Liang (BSc at HKU)(PhD Student, 2022-)(HKU-PS)
Yihang Chen (BSc at RUC)(PhD Student, 2023-)
Yanyan Huang (MPhil at ZJU)(PhD Student, 2023-)
Feng Wu (MPhil at ZJU)(PhD Student, 2023-)
Jiacheng Xu (BSc at HKU)(PhD Student, 2023-)(HKPF)
Liting Yu (BSc at XJTU)(PhD Student, 2023-)

Co-supervised Students:
Xuanyu Liu (Mphil at SUSTech)(PhD Student, 2021-)(w/ K.C. Yuen)
Yan Miao (MPhil at McGill)(PhD Student, 2022-)(HKPF) (w/ Wai-Kay Seto)
Pei Cai (MPhil at NTU)(PhD Student, 2023-) (w/ Jianpan Huang)

Previous Mentorship:
Jiacheng Xu (Undergraduate Intern) (BSc at HKU --> PhD at HKU)
Wing Kwan Pang (Undergraduate Intern) (BSc at HKU --> MS Biostatistics at McGill)
Xi Zheng (2022 Summer Intern) (BSc at XJTU --> IS PhD at UW)
Tengfei Cui (2022 Summer Intern) (BSc at XJ-Liverpool --> MS Biostatistics at UW)
Yiqing Shen (2021 Summer Intern) (BSc at SJTU --> CS PhD at JHU)
Ruichen Luo (2021 Summer Intern) (BEng at ZJU --> ECE PhD at UMN)
Xiaoyu Zhang (2021 Summer Intern) (BEng at ZJU --> MCDS at CMU)
Zeqi Xiao (2021 Summer Intern) (BEng at ZJU --> Intern at Shanghai AI Lab)
Yijun Yang (2021 Summer Intern) (BEng at SDU --> PhD at HKUST-GZ)
Kang Li (Ph.D. at CUHK) (now, Postdoc at CUHK)
Shujun Wang (Ph.D. at CUHK) (now, Asst. Prof. at PolyU)
Xianzhi Li (Ph.D. at CUHK) (now, Assoc. Prof. at HUST)

Recent Talks & Presentations

Honors & Awards

The world’s top 1% scholars ranked by Clarivate Analytics, 2023
MICCAI 2023 Young Scientist Publication Impact Award Runner-up, 2023
国家教育部高等学校科学研究优秀成果奖(科学技术), 自然科学二等奖 (排名: 4/5), 2022
Ranked Top 2% of Scientists on Stanford List, 2022 and 2023
the World's First List of Top 150 Chinese Young Scholars in Artificial Intelligence, 2022
Rising Star of Science Award by Research.com, 2022
IEEE TMI Distinguished Reviewer Platinum Level, 2022 and 2023
IEEE TMI Distinguished Reviewer Silver Level, 2021
CUHK Young Scholars Thesis Award 2019
Young Scientist Award Short-listed, Hong Kong Institution of Science, 2019
Teaching Assistant of Merit, 2018
MedIA-MICCAI'17 Best Paper Award, 2017
AAAI Scholarship, San Fransisco, USA, 2017
Champion, Optic Disc&Cup Segmentation on Retinal Fundus Images (REFUGE 2018)
Champion, Whole-Heart and Great Vessel Segmentation (HVSMR 2016)
Champion, Skin Lesion Analysis Towards Melanoma Detection Challenge (ISIC 2016)
Champion, Prostate MR Image Segmentation 2012 (PROMISE12, until 2018 Jan.)
National Scholarship in China (1.8%), 2012-2014
He Zhijun Scholarship (1/300+, Highest Honor in College of Computer Science, Zhejiang University), 2014
Kwanjeong Educational Foundation Scholarship, 2012-2014
Meritorious Winner, Interdisciplinary Contest in Modeling (ICM), Consortium for Mathematics and Its Application, 2014
The Outstanding Undergraduate Award (Awarded by CCF, 100 undergraduates every year in China), 2014
Outstanding Graduates of Zhejiang University, 2015

Professional Activities

  • Program Committees:
    Area Chair of Medical Image Computing and Computer Assisted Intervention (MICCAI’22-24)
    Senior Program Committee of AAAI Conference on Artificial Intelligence (AAAI’22)
    Senior Program Committee of International Joint Conference on Artificial Intelligence (IJCAI’21)
    Co-organizer of ICCV workshop on Computer Vision for Automated Medical Diagnosis (ICCV'21 and ICCV'23)

  • Conference Reviews:
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19-22)
    PC of AAAI Conference on Artificial Intelligence (AAAI’20-21)
    IEEE International Conference on Computer Vision (ICCV’21, ICCV'19)
    Medical Image Computing and Computer Assisted Intervention (MICCAI’18-21)
    IEEE Winter Conference on Applications of Computer Vision (WACV’20-21)
    Medical Imaging with Deep Learning (MIDL’21)
    SIGGRAPH 2020
    European Conference on Computer Vision (ECCV’20)
    Asian Conference on Computer Vision (ACCV’20)

  • Journal Reviews:
    Nature Machine Intelligence
    Nature Computational Science
    Nature Communications
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    International Journal of Computer Vision (IJCV)
    Medical Image Analysis (MedIA)
    IEEE Transactions on Medical Imaging (TMI)
    IEEE Transactions on Image Processing (TIP)
    IEEE Transactions on Biomedical Engineering (TBME)
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
    IEEE Transactions on Automation Science and Engineering (TASE)
    IEEE Transactions on Artificial Intelligence (TAI)
    IEEE Transactions on Big Data (TBD)
    IEEE Transactions on Dependable and Secure Computing
    IEEE Journal of Biomedical and Health Informatics (JBHI)
    IEEE Robotics and Automation Letters (RA-L)

  • Teaching

    2023&2024 SpringSTAT8021 Big Data Analytics
    2023&2024 SpringSTAT8307 Natural Language Processing and Text Analysis
    2022&2023 FallSTAT3612 Statistical Machine Learning
    2022 FallBIOF1001 Introduction to Biomedical Data Science (guest lecture)
    2022 SpringAPAI4011/STAT4011 Natural Language Processing