Changjian Shui
Ph.D.
Université Laval, Mila
E-mail: changjian DOT shui AT mail DOT mcgill DOT ca
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About me
I completed my Postdoc in McGill University/Mila, under the supervision of Prof. Tal Arbel. I obtained Ph.D. degree from Université Laval, under the supervision of Prof. Christian Gagné and Prof. Boyu Wang.
Research Interests Learning limited labeled data (transfer learning, meta-learning, multitask learning, active learning); Trustworthy machine learning (algorithmic fairness, robustness, out-of-distribution generalization); Applied machine learning (data-mining, healthcare).
Recent news
[Sep 2023] Our paper “On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm” has been accepted in NeurIPS 2023.
[Jul 2023] I am selected as an Expert Reviewer in TMLR (Transactions on Machine Learning Research)!
[May 2023] Our paper “Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis” has been accepted in MICCAI (Early acceptance, 14% of submissions).
[Mar 2023] Our paper “Towards More General Loss and Setting in Unsupervised Domain Adaptation” has been accepted in IEEE Transactions on Knowledge and Data Engineering (TKDE).
[Oct 2022] Our paper “On Learning Fairness and Accuracy on Multiple Subgroups” has been accepted in NeurIPS 2022 (Spotlight presentation).
[May 2022] Our paper “Fair Representation Learning through Implicit Path Alignment” has been accepted in ICML 2022. See our blog for details!