Changjian Shui Headshot

Changjian Shui

Postdoctoral Fellow

Changjian is a Postdoc Fellow at Vector Institute. He got his PhD at Laval University in 2022. His primary research interest is in machine learning under distribution and its applications in health. Particularly he is interested in the issue of reliability (e.g., robustness, fairness, uncertainty, and transparency) and data-efficient machine learning (e.g., transfer, meta and active learning). His long research objectives are to establish transparent AI models. His research has appeared in major AI venues such as NeurIPS, ICML, ICLR, JMLR, IJCAI, AAAI, AISTATS.

Research Interests

  • Machine Learning Under Distribution Shift
  • Data-efficient Machine Learning
  • Algorithmic Fairness
  • Explainable AI


  • Expert Reviewer, TMLR
  • Outstanding reviewer in ICML/NeurIPS/ICLR
  • On Learning Fairness and Accuracy on Multiple Subgroups NeurIPS 2022
  • Deep Active Learning: Unified and Principled Method for Query and Training AISTATS 2020