Scholar
Xiaoxiao Li
Google Scholar ID: sdENOQ4AAAAJ
Assistant Professor, UBC; Vector Institute; CIFAR AI Chair; Canada Research Chair
Citations & Impact
Citations
6,662
H-index
34
i10-index
76
Publications
20
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- - Multiple papers accepted by top conferences including NeurIPS 2025, MICCAI 2025, ICML 2025, ICLR 2025, AAAI 2025
- - One paper on federated unlearning received Best Paper Award at FL@FM WWW 2024
Research Experience
- - Conducting research at the Trusted and Efficient AI (TEA) lab at UBC
- - Involved in multiple research projects including data valuation, federated learning, and fairness benchmarking for medical imaging foundation models
Background
- Research interests include improving the explainability, fairness, privacy, and efficiency of AI models. Focused on developing machine learning algorithms and systems based on these principles, with applications in real-world scenarios such as healthcare.
