About me
I am a second-year Ph.D. student in the GSAI-ML Group, Renmin University of China, advised by Prof. Chongxuan Li fortunately.
Before that, I received my B.E. degree from the School of Computer Science, Wuhan University in 2023.
Research interests
I focus on understanding and improving the
optimization, generalization and scalability of deep learning.
Selected Papers
[* indicates the equal contribution, # indicates the corresponding author]
Foundation Models (2023~)
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Scaling Diffusion Transformers Efficiently via μP
Chenyu Zheng, Xinyu Zhang, Rongzhen Wang, Wei Huang, Zhi Tian, Weilin Huang, Jun Zhu, Chongxuan Li
Preprint, 2025
[Paper]
[Code]
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On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
Advances in Neural Information Processing Systems (NeurIPS), 2024
[Paper]
[Code]
Machine Learning Theory (2022~)
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Toward Understanding Generative Data Augmentation
Chenyu Zheng, Guoqiang Wu, Chongxuan Li
Advances in Neural Information Processing Systems (NeurIPS), 2023
[Paper]
[Code]
[Slides]
[Blog]
[Poster]
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Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
International Conference on Machine Learning (ICML), 2023
[Paper]
[Code]
[Slides]
[Blog]
[Poster]
Experience
Honors
- Outstanding Innovative Talents Cultivation Funded Programs, Renmin Univertity of China, 2025
- Outstanding Graduate & Bachelor Thesis Award, Wuhan University, 2023
- Finalist, International Mathematical Contest in Modeling (MCM), 2022
- China National Scholarship, Ministry of Education of China, 2020
Academic Services
Journal Reviewer
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Signal Processing (TSP)
Conference Reviewer
- Advances in Neural Information Processing Systems (NeurIPS): 2024, 2025
- International Conference on Machine Learning (ICML): 2025
- International Conference on Learning Representations (ICLR): 2025
- International Conference on Artificial Intelligence and Statistics (AISTATS): 2025
Tutorials/Talks
- Tutorial: A Brief Review of In-Context Learning Theory, 2024.05 [Slides]
- Tutorial: Classical Machine Learning Theory, 2023.06 [Slides]
Miscellaneous
© 2025.05 Chenyu Zheng