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)

Publications

Hypernetwork-based personalized federated learning for multi-institutional CT imaging

Ziyuan Yang and Wenjun Xia and Zexin Lu and Yingyu Chen and Xiaoxiao Li and Yi Zhang

2023

BUDDY: molecular formula discovery via bottom-up MS/MS interrogation

Shipei Xing and Sam Shen and Banghua Xu and Xiaoxiao Li and Tao Huan

2023

Federated Adversarial Learning: A Framework with Convergence Analysis

Xiaoxiao Li and Zhao Song and Jiaming Yang

2023

Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP

Ruinan Jin and Chun-Yin Huang and Chenyu You and Xiaoxiao Li

2024

Backdoor attack and defence in federated generative adversarial network-based medical image synthesis

Ruinan Jin and Xiaoxiao Li

2023

Community-Aware Transformer for Autism Prediction in fMRI Connectome

Anushree Bannadabhavi and Soojin Lee and Wenlong Deng and Xiaoxiao Li

2023

FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation

Minghui Chen and Meirui Jiang and Qi Dou and Zehua Wang and Xiaoxiao Li

2023

LESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image Screening

Beidi Zhao and Wenlong Deng and Zi Han and Chen Zhou and Zuhua Gao and Gang Wang and Xiaoxiao Li

2024

Forgettable federated linear learning with certified data removal

Ruinan Jin and Minghui Chen and Qiong Zhang and Xiaoxiao Li

2023

Local Superior Soups: A Catalyst for Reducing Communication Rounds in Federated Learning with Pre-trained Model

Minghui Chen and Meirui Jiang and Qi Dou and Zehua Wang and Xiaoxiao Li

2024

Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection

Xianjie Guo and Kui Yu and Hao Wang and Lizhen Cui and Han Yu and Xiaoxiao Li

2024

A Simple and Provable Approach for Learning on Noisy Labeled Multi-modal Medical Images

Nan Wang and Zonglin Di and Houlin He and Qingchao Jiang and Xiaoxiao Li

2024

Advances and open challenges in federated learning with foundation models

Chao Ren and Han Yu and Hongyi Peng and Xiaoli Tang and Anran Li and Yulan Gao and Alysa Ziying Tan and Bo Zhao and Xiaoxiao Li and Zengxiang Li and Qiang Yang

2025

DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models

Wenlong Deng and Yize Zhao and Vala Vakilian and Minghui Chen and Xiaoxiao Li and Christos Thrampoulidis

2025

Gmvaluator: Similarity-based data valuation for generative models

Jiaxi Yang and Wenglong Deng and Benlin Liu and Yangsibo Huang and James Zou and Xiaoxiao Li

2025

Can Textual Gradient Work in Federated Learning?

Minghui Chen and Ruinan Jin and Wenlong Deng and Yuanyuan Chen and Zhi Huang and Han Yu and Xiaoxiao Li

2025

S4M: S4 for multivariate time series forecasting with Missing values

Peng Jing and Meiqi Yang and Qiong Zhang and Xiaoxiao Li

2025