BASc (Zhejiang University), MASc (Yale University) , PhD (Yale University)
Office: KAIS 3110
Dr. Li is an Assistant Professor (tenure-track) at the Department of Electrical and Computer Engineering (ECE) at the University of British Columbia (UBC) starting August 2021. Before joining UBC，Dr. Li was a Postdoc Research Fellow in the Computer Science Department at Princeton University. Dr. Li obtained her PhD degree from Yale University in 2020. During her PhD studies, she was awarded the Advanced Graduate Leadership Scholarship.
Dr. Li is leading the Trusted and Efficient AI (TEA) Lab. Her groups’ research interests range across the interdisciplinary files of deep learning and biomedical data analysis, aiming to improve the trustworthiness of AI systems for healthcare. In the recent few years, Dr. Li has over 30 papers published in leading machine learning conferences and journals, including NeurIPS, ICML, ICLR, MICCAI, IPMI, BMVC, and Medical Image Analysis. Her work has been recognized with the OHBM Merit Abstract Award, the MLMI Best Paper Award, and the DART Best Paper Award. In addition, she has received travel awards from NeurIPS/ICML/MICCAI/IPMI. Dr. Li has also organized a number of workshops on the topic of machine learning and healthcare. She is the Associate Editor of Frontiers in NeuroImaging and a reviewer for a number of international conferences and journals. Dr. Li and her group have close connections with industries. Dr. Li interned at research group at Sony (Japan), Siemens Healthineers (US), and JP Morgan AI Research (US). Her group has received funding/computing resource support from NVIDIA, Microsoft, and Google. TEA lab members will have access to advanced and sufficient GPU computational recourses.
Dr. Li always looks for self-motivated M.Sc. and Ph.D. candidates, who are interested in artificial intelligence and healthcare applications. Having a solid background in mathematics and/or excellent coding skills is a plus. UBC students, who are interested in doing research with Dr. Li, are also welcome. For more information about the application, internship and collaboration opportunities (e.g., visiting students or scholars), please check Dr. Li’s webpage and drop your email with the indicated format, required documents, and state why you are interested in working with Dr. Li.
Machine Learning, Deep Learning, Explainable AI, Trustworthy AI, Privacy and Security, Medical Image Analysis, Bioinformatics