I am a Ph.D. student at McGill–Mila working with Prof. Xue (Steve) Liu and Prof. Christopher Pal. I graduated (bachelor) from University of Science and Technology of China as an outstanding graduate (73/1824 ≈ 4%). Besides, I interned at Microsoft Research Asia, Tencent, and Baidu, among others, and served as a mentor at Amgen, Valence Labs, and AbCellera. I am currently interested in generative modeling, AI for Science and meta-learning.
* denotes co-first author and † denotes (co-)corresponding author.
Parallel-Mentoring for Offline Model-Based Optimization. Can Chen†, Chris Beckham, Zixuan Liu, Xue Liu, Chris Pal. In NeurIPS 2023.
Importance-Aware Co-Teaching for Offline Model-Based Optimization. Can Chen*†, Ye Yuan*, Zixuan Liu, Willie Neiswanger, Xue Liu. In NeurIPS 2023.
Structure-Aware Protein Self-Supervised Learning. Can Chen†, Jingbo Zhou†, Fan Wang, Xue Liu, Dejing Dou. In Bioinformatics 2023.
Bidirectional Learning for Offline Model-Based Biological Sequence Design. Can Chen†, Yingxue Zhang, Xue Liu, Mark Coates. In ICML 2023.
Bidirectional Learning for Offline Infinite-Width Model-Based Optimization. Can Chen†, Yingxue Zhang, Jie Fu, Xue Liu, Mark Coates. In NeurIPS 2022.
Generalized Data Weighting via Class-Level Gradient Manipulation. Can Chen*†, Shuhao Zheng*†, Xi Chen, Erqun Dong, Xue Liu, Hao Liu, Dejing Dou. In NeurIPS 2021.