Xiaoxiao Li headshot

Xiaoxiao Li

Faculty Member

Assistant Professor, Department of Electrical and Computer Engineering, University of British Columbia

Canada CIFAR Artificial Intelligence Chair

Dr. Xiaoxiao Li is an Assistant Professor in the Electrical and Computer Engineering Department at the University of British Columbia (UBC), leading the Trusted and Efficient AI (TEA) Group, and an Adjunct Assistant Professor at the School of Medicine at Yale University. Dr. Li specializes in the interdisciplinary field of deep learning and healthcare. Their primary mission is to make AI more reliable, especially when it comes to sensitive areas like healthcare. At the TEA Group, they explore wide-range of topics from fundamental machine learning to more focused healthcare-driven AI solutions. The group delves into topics like learning from multimodal and heterogeneous data, efficient AI models, federated learning, vision-language models, and creating AI models that not only perform tasks but can also be trustworthy. Some of their groundbreaking work includes AI-driven analysis of neuroimages, pathology slides, molecular and clinical notes. In essence, Dr. Li’s work is all about bridging the world of advanced machine learning with the practical needs of the healthcare industry.

Research Interests

  • Safe and Trustworthy AI
  • Multi-model Learning
  • Optimization
  • Healthcare

Highlights

  • Outstanding Reviewer, ICLR (2023)
  • Meta Research Award (2022)
  • NVIDIA Hardware Award (2021/22)
  • Student Travel Award, MICCAI (2020)
  • Yale Advanced Graduate Leadership Fellowship (2018-2020)
  • Merit Abstract Award, OHBM (2018)