Bio
I am a quantitative researcher now. I completed my Ph.D. in the Department of Automation at Tsinghua University in October 2025. Prior to this, I earned my Bachelor of Science degree in Mathematics and Physics from the Department of Physics at Tsinghua University in 2020.
My research primarily focuses on machine learning under mismatched distribution, including areas such as long-tailed learning and test-time adaptation.
Selected Publications
Journal Papers
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
Chaoqun Du, Yulin Wang, Shiji Song, Gao Huang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, IF=20.8), 2024
Conference Papers
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
Chaoqun Du*, Yizeng Han*, Gao Huang
International Conference on Machine Learning (ICML), 2024