Rm 226, Run Run Shaw Building
Division of Statistics and Actuarial Science
School of Computing and Data Science
The University of Hong Kong
Email: lqyu [at] hku [dot] hk
Biography
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.
[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.
If you are an HKU student interested in doing research with me, please send me an email.
Adaptive Region-Specific Loss for Improved Medical Image Segmentation
Yizheng Chen, Lequan Yu, Jen-Yeu Wang, Neil Panjwani, Jean-Pierre Obeid, Wu Liu, Lianli Liu, Nataliya Kovalchuk, Michael Francis Gensheimer, Lucas Kas Vitzthum, Beth M Beadle, Daniel T Chang, Quynh-Thu Le, Bin Han, Lei Xing. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
3D FractalNet: Dense Volumetric Segmentation for Cardiovascular MRI Volumes Lequan Yu, Xin Yang, Jing Qin, Pheng-Ann Heng. MICCAI Workshop on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, 2016.
Ranked 1st place in Whole-Heart and Great Vessel Segmentation Challenge
Jiacheng Xu (BSc at HKU)(PhD Student, 2023-)(HKPF)
Liting Yu (BSc at XJTU)(PhD Student, 2023-)
Yushi Feng (BSc at HKU)(PhD Student, 2024-)
Tao Ma (MPhil at PKU)(PhD Student, 2024-)
Ziyan Xiao (BASc at HKU)(PhD Student, 2024-)(HKPF)
Ruiyang Zhang (MSc at NUS)(PhD Student, 2024-)
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:
Jiayi Xin (2024 Undergraduate Intern) (BASc at HKU --> PhD at UPenn)
Ziyan Xiao (2024 Undergraduate Intern) (BASc at HKU --> PhD at HKU)
Yushi Feng (2024 Undergraduate Intern) (BSc at HKU --> PhD at HKU)
Jiacheng Xu (2023 Undergraduate Intern) (BSc at HKU --> PhD at HKU)
Wing Kwan Pang (2023 Undergraduate Intern) (BSc at HKU --> MPhil at HKU)
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 --> PhD at NTU)
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
Leveraging Deep Learning in Computational Pathology: from Single-modal to Multi-modal Analysis
at The Third Affiliated Hospital of Sun Yat-sen University, April 2024.
at Zhejiang Lab, Hangzhou, July 2023.
at Shanghai AI Lab, Shanghai, July 2023.
at Computational Health seminar, Helmholtz AI, German, July 2023.
Learning generalized medical visual representation from accompanied medical reports
at MICS online seminar, April 2023.
at Department of Biomedical Engineering, SZU, April 2023.
Medical Image Analysis and Reconstruction with Data-efficient Learning
at VALSE 2022 workshop "医学数据分析中的深度学习方法", August 2022.
at Beihang University, May 2022.
at Zhejiang University, May 2022.
at 海峡两岸暨港澳精准医学青年博士论坛, November 2021.
at 中国医师协会第十五次放射医师年会, October 2021.
at Nanjing University of Information Science and Technology, October 2021.
at Department of Electrical and Electronic Engineering, HKU, September 2021.
at MICS 2021, July 2021.
at Data Science and Computational Statistics Seminar, University of Birmingham, February 2021.
AI for Medical Imaging: Applications and Beyond
at AI and Big Data Research for Health Improvement Symposium, Institute of Data Science, HKU, August 2022.
at Mini-Symposium on Interdisciplinary Research, Faculty of Science, HKU, January 2022.
at School of Biomedical Sciences, HKU, December 2021.
The Applications of Transformer in Volumetric Segmentation and Low Dose CT
at VALSE Webinar, October 2022.
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
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 Spring
STAT8021 Big Data Analytics
2023&2024 Spring
STAT8307 Natural Language Processing and Text Analysis
2022&2023 Fall
STAT3612 Statistical Machine Learning
2022 Fall
BIOF1001 Introduction to Biomedical Data Science (guest lecture)