Hengzhi He

I am a fourth-year PhD candidate at UCLA, working with Professor Guang Cheng. My research interests lie in applied probability, theoretical statistics, and theoretical computer science.

Email: hengzhihe@g.ucla.edu

Google Scholar

Current Focus

• Model Collapse: Understanding the benefits and risks of training models using synthetic data, and developing more efficient and reliable algorithms to leverage synthetic data.
• Statistical Watermarking: Designing watermarks to trace the origins of generated content, and developing more credible methods for evaluating watermarking techniques.

Selected Manuscripts

Watermarking Generative Tabular Data
Hengzhi He*, Peiyu Yu*, Junpeng Ren, Ying Nian Wu, Guang Cheng
Under Major Revision at Journal of the American Statistical Association (JASA), 2024
[arXiv]

Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework
Hengzhi He*, Shirong Xu*, Guang Cheng
This article has been accepted for publication in Journal of the Royal Statistical Society: Series B, published by Oxford University Press , 2026
[JRSSB]

"Noisier" Noise Contrastive Estimation is (Almost) Maximum Likelihood Estimation
Peiyu Yu*, Dinghuai Zhang*, Hengzhi He*, Xiaojian Ma, Sirui Xie, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu
Accepted at International Conference on Learning Representations (ICLR), 2026
[OpenReview]

Optimal Watermark Generation under Type I and Type II Errors
Hengzhi He, Shirong Xu, Alexander Nemecek, Jiping Li, Erman Ayday, Guang Cheng
This article has been accepted for publication in Biometrika, published by Oxford University Press, 2026
[Biometrika]

A Probabilistic Perspective on Model Collapse
Shirong Xu*, Hengzhi He*, Guang Cheng
Under R&R at Journal of Machine Learning Research (JMLR), 2026
[arXiv]

* denotes equal contribution. For a full list, please refer to my Google Scholar page.

Education

• Department of Statistics and Data Science, University of California, Los Angeles (UCLA), 2023 – Present
  PhD Student, Advisor: Prof. Guang Cheng
• School of Mathematical Sciences, Peking University, 2019 – 2023
  Undergraduate Student