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Lei Li is an Assistant Professor in the Department of Biomedical Engineering at the National University of Singapore (NUS), where she serves as Principal Investigator of the Digital Heart Lab. She joined NUS in October 2024. Previously, she held positions as Lecturer in the School of Electronics and Computer Science at the University of Southampton from January to October 2024 and as Postdoctoral Research Assistant at the Institute of Biomedical Engineering, University of Oxford, from August 2021 to December 2023. She earned her PhD from the School of Biomedical Engineering at Shanghai Jiao Tong University in 2021, receiving the SJTU 2021 Outstanding Doctoral Graduate Development Scholarship, and her Bachelor degree from the Department of Medical Information Engineering at Sichuan University in 2016.
Her research focuses on AI for healthcare, with specific emphasis on cardiac digital twins, medical imaging, and multimodal AI. She has contributed to the field through numerous publications, including papers in Medical Image Analysis and IEEE Transactions on Medical Imaging on topics such as cardiac image computing, myocardial pathology segmentation, and inverse problems in electrocardiography. Lei Li serves on editorial boards and as guest editor for journals including IEEE Transactions on Medical Imaging and Journal of Medical Artificial Intelligence. She is a board member of SIG-Cardiac and Women in MICCAI, has acted as Area Chair for MICCAI conferences, and has organized workshops and challenges in medical image analysis. Her honors include the Rising Star of Women in Engineering award from the Asian Deans’ Forum in 2023, Featured Woman in Science recognition by RSIP Vision, multiple IEEE TMI Distinguished Reviewer awards, and the 2nd Prize of the Shanghai Science and Technology Award in 2024. She has delivered invited talks at institutions and events worldwide on AI-powered cardiac digital twins and related topics.
Explore Asst Prof Lei Li's groundbreaking NUS research using π in MRI for cardiac digital twins, advancing personalized healthcare on Pi Day.
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