I am an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Minnesota, affiliated with the CSE Data Science Initiative. My research lies at the interface of statistics, optimization, and machine learning, inspired by engineering applications.
Previously: I was an Assistant Professor in the School of Data Science at The Chinese University of Hong Kong, Shenzhen. I received my Ph.D. in Industrial Engineering from Georgia Institute of Technology, and my B.S. in Statistics from the University of Science and Technology of China in 2016.
I am actively looking for Ph.D. students to join my research group in Fall 2025 or 2026. Please send me an email with your CV and transcript if you are interested.
Research Interest
- Optimization and Machine Learning: diffusion generative models, large language models, transfer learning, differential privacy, adversarial robustness.
- Statistical Inference: time series analysis, sequential hypothesis testing and change detection.
- Applications: healthcare, including wearable sensors and electronic health record data; spatio-temporal data analysis; community detection; and manufacturing quality control.
Currently Teaching
- IE3521: Statistics, Quality, and Reliability. Fall 2024, Fall 2025.
- IE5533: Operations Research for Data Science. Spring 2025, Spring 2026.
Selected Publications [full list]
- Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching. Zhengyan Wan, Yidong Ouyang, Liyan Xie, Fang Fang, Hongyuan Zha, and Guang Cheng. ICLR, 2026.
- Sequential Change Detection with Differential Privacy. Liyan Xie and Ruizhi Zhang. IEEE Transactions on Information Theory, 2025. (Code)
- Transfer Learning for Diffusion Models. Yidong Ouyang, Liyan Xie, Hongyuan Zha, and Guang Cheng. NeurIPS, 2024. (GitHub)
- Window-Limited CUSUM for Sequential Change Detection. Liyan Xie, George V. Moustakides, and Yao Xie. IEEE Transactions on Information Theory, 2023.
- MissDiff: Training Diffusion Models on Tabular Data with Missing Values. Yidong Ouyang, Liyan Xie, Chongxuan Li, and Guang Cheng. preprint, 2023. (GitHub)
- Sequential Change Detection: Classical Results and New Directions. Liyan Xie, Shaofeng Zou, Yao Xie, and Venugopal V. Veeravalli. IEEE Journal on Selected Areas in Information Theory, 2021. Survey paper.
- Sequential Subspace Change-Point Detection. Liyan Xie, Yao Xie, and George V. Moustakides. Sequential Analysis, 2020.
- Robust hypothesis testing using Wasserstein uncertainty sets. Rui Gao, Liyan Xie, Yao Xie, and Huan Xu. NeurIPS, 2018. Spotlight.