Faculty Directory

Minshuo Chen

Assistant Professor of Industrial Engineering and Management Sciences

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Minshuo Chen's Website

Departments

Industrial Engineering and Management Sciences

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Research Interests

My research focuses on developing principled methodologies and theoretical foundations of learning and decision-making. I am particularly interested in

• Generative AI: diffusion models for data modeling and beyond
• Foundations of learning: approximation, optimization and efficiency 
• (Deep) reinforcement learning: diagnosis and control in complex systems

Selected Publications

• Fu, Hengyu; Dou, Zehao; Guo, Jiawei; Wang, Mengdi; Chen, Minshuo, DIFFUSION TRANSFORMER CAPTURES SPATIAL-TEMPORAL DEPENDENCIES, International Conference on Learning Representations, ICLR (2025).
• Hu, Jerry Yao Chieh; Wu, Weimin; Lee, Yi Chen; Huang, Yu Chao; Chen, Minshuo; Liu, Han, ON STATISTICAL RATES OF CONDITIONAL DIFFUSION TRANSFORMERS, International Conference on Learning Representations, ICLR (2025).
• Dou, Zehao; Chen, Minshuo; Wang, Mengdi; Yang, Zhuoran, Theory of Consistency Diffusion Models, Proceedings of Machine Learning Research (2024).
• Chen, Minshuo; Meng, Jie; Bai, Yu; Ye, Yinyu; Vincent Poor, H.; Wang, Mengdi, Efficient Reinforcement Learning with Impaired Observability, IEEE Transactions on Information Theory (2024).
• Wu, Yuchen; Chen, Minshuo; Li, Zihao; Wang, Mengdi; Wei, Yuting, Theoretical Insights for Diffusion Guidance, Proceedings of Machine Learning Research (2024).
• Li, Zihao; Ji, Xiang; Chen, Minshuo; Wang, Mengdi, Policy Evaluation for Reinforcement Learning from Human Feedback, Proceedings of Machine Learning Research (2024).
• Chen, Minshuo; Mei, Song; Fan, Jianqing; Wang, Mengdi, Opportunities and challenges of diffusion models for generative AI, National Science Review (2024).
• Wu, Shenghao; Zhou, Wenbin; Chen, Minshuo; Zhu, Shixiang, Counterfactual Generative Models for Time-Varying Treatments, Association for Computing Machinery (2024).