I am currently an Associate Professor in the School of Computer Science and Technology at Nanjing University of Posts and Telecommunications. I earned my Ph.D. in Computer Science and Technology from Nanjing University.

My research focuses on deep learning under imperfect data and in open-environments, particularly in areas such as learning with noisy labels and distribution shift. I welcome collaboration and inquiries and am passionate about academic exchange. I look forward to working with scholars and researchers from diverse fields to explore new research directions together.

Publications

Mingcai Chen, Baoming Zhang*, Zongbo Han, Yuntao Du, Wenyu Jiang, Yanmeng Wang, Shuai Feng, Bingkun Bao.
Test-Time Selective Adaptation for Uni-Modal Distribution Shift in Multi-Modal Data.
Proceedings of The Forty-second International Conference on Machine Learning (ICML 25)
[Acceptance Rate: ~27%]

Mingcai Chen, Yuntao Du, Wenyu Jiang, Baoming Zhang, Shuai Feng, Yi Xin, Chongjun Wang.
Robust Logit Adjustment for Learning with Long-Tailed Noisy Data. Proceedings of The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 25)
[Acceptance Rate: ~23%]

Mingcai Chen, Yu Zhao*, Bing He, Zongbo Han, Junzhou Huang, Jianhua Yao.
Learning with Noisy Labels over Imbalanced Subpopulations.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Mingcai Chen, Yu Zhao*, Bing He, Zhonghuang Wang, Jianhua Yao.
A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification.
Proceedings of The 32nd International Joint Conference on Artificial Intelligence (IJCAI’23).
[Acceptance Rate: ~15%]

Mingcai Chen, Hao Cheng, Yuntao Du, Ming Xu, Wenyu Jiang, Chongjun Wang.
Two Wrongs Don’t Make a Right: Combating Confirmation Bias in Learning with Label Noise.
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI’23).
[Acceptance Rate: ~20%]

Mingcai Chen, Yuntao Du , Yi zhang, Shuwei Qian, and Chongjun Wang.
Semi-Supervised Learning with Multi-Head Co-Training.
Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI’22).
[Acceptance Rate: ~15%]

Mingcai Chen, Yang Li, Yi-Heng Zhu, Fang Ge, Dong-Jun Yu.
SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network.
Journal of Chemical Information and Modeling (JCIM)

Wenyu Jiang, Hao Cheng, MingCai Chen, Chongjun Wang, Hongxin Wei.
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection. Accepted by the 12nd International Conference on Learning Representations (ICLR’24)

Wenyu Jiang, Yuxin Ge, Hao Cheng, Mingcai Chen, Shuai Feng, Yuxin Ge, Chongjun Wang.
READ: Aggregating Reconstruction Error into Out-of-distribution Detection.
Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI’23).

Baoming Zhang, Ming Xu, Mingcai Chen, Mingyuan Chen, Chongjun Wang.
CopGAT: Co-propagation Self-supervised Graph Attention Network.
In Proceedings of ISPA 2022.

Shuai Feng, Wenyu Jiang, Mingcai Chen, Yuntao Du, Hao Cheng, Chongjun Wang.
CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection.
In Proceedings of SDM 2023.

Yuntao Du, Juan Jiang, Hongtao Luo, Haiyang Yang, Mingcai Chen, Chongjun Wang.
Bidirectional View based Consistency Regularization for Semi-Supervised Domain Adaptation.
Transactions on Machine Learning Research.

Services

• Reviewer: CVPR 22,23 & AAAI 23 & ECCV 22 & ICCV 23