Xiaoxiao Li

Xiaoxiao Li is an Associate Professor in the Department of Electrical and Computer Engineering at The University of British Columbia. Her research interests include Deep Learning, Trustworthy AI, Federated Learning, Graph Learning, and Medical Image Analysis. Dr. Li is also an Associate Member in the Department of Computer Science and the Department of Pathology and Laboratory Medicine at UBC. She is a faculty member at the Vector Institute and holds a Canada Research Chair (Tier II) in responsible AI and a Cifar AI Chair. Her work focuses on AI and healthcare, artificial general intelligence, and AI trustworthiness. Dr. Li's research has been published in top-tier conferences and journals, and she is actively seeking motivated graduate students and postdocs for collaboration.

Xiaoxiao Li is an Associate Professor at the University of British Columbia (UBC), affiliated with the Vector Institute, Google, and CIFAR AI Chair. Her research focuses on deep learning, particularly in the areas of federated learning, graph neural networks, and medical image analysis. She has developed frameworks for privacy-preserving federated learning and interpretable models for brain disorder analysis using fMRI data. Her work also includes explainable AI for clinical applications and medical image segmentation. Li's research emphasizes the integration of deep learning with domain adaptation and network inpainting for robust and interpretable models.