Biography
Wanrong Zhu, Ph.D., is an Assistant Professor in the Department of Statistics at the University of California, Irvine. She received her Ph.D. in Statistics from the University of Chicago in 2024, where she was advised by Rina Foygel Barber and Wei Biao Wu. Her research focuses on statistical learning and inference, with particular emphasis on stochastic optimization and conformal prediction. Building on prior work, her current research centers on understanding generalization and memorization in modern machine learning by analyzing their underlying learning dynamics.
Zhu’s research has appeared in leading journals and conferences, including the Journal of the American Statistical Association, Journal of Machine Learning Research, Electronic Journal of Statistics, and AISTATS. Her work addresses theoretical and methodological challenges in statistical inference and optimization, alongside ongoing projects in conformal prediction and inference for stochastic optimization.
At UC Irvine, she teaches courses in probability and statistics, and she serves as a reviewer for journals including the Journal of the Royal Statistical Society: Series B, Bernoulli, and the Journal of the American Statistical Association.
Return to topEducation
- Ph.D. in Statistics, University of Chicago, 2024
- M.S. in Statistics, University of Chicago, 2018
- B.S. in Mathematics and Statistics, Nanjing University, 2016
Areas of Expertise
- Statistical Learning and Inference
- Stochastic Gradient Descent
- Online Covariance Matrix Estimation
- Conformal Prediction
Recent Publications
- Ruiting Liang, Wanrong Zhu, Rina Foygel Barber, “Conformal prediction after data-dependent model selection”, Journal of the American Statistical Association, 2026.
- Wanrong Zhu, Rina Foygel Barber, “Approximate co-sufficient sampling with regularization”, Electronic Journal of Statistics, vol. 20, no. 2, pp. 3807-3838, 2026.
- Ziyang Wei, Wanrong Zhu, Wei Biao Wu, “General Weighted Averaging in Stochastic Gradient Descent: CLT and Adaptive Optimality”, 2026. Presented at The 29th International Conference on Artificial Intelligence and Statistics.
- Ziyang Wei, Wanrong Zhu, Jingyang Lyu, Wei Biao Wu, “Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction”, 2026. Presented at The 29th International Conference on Artificial Intelligence and Statistics.
- Wanrong Zhu, Xi Chen, Wei Biao Wu, “Online Covariance Matrix Estimation in Stochastic Gradient Descent”, Journal of the American Statistical Association, vol. 118, no. 541, pp. 393–404, 2023.
- Zhipeng Lou, Wanrong Zhu, Wei Biao Wu, “Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for SGD”, Journal of Machine Learning Research, vol. 23, no. 46, pp. 1–22, 2022.
Contact Information
Website: https://zhuwr0423.github.io
Email: wanronz1@uci.edu
Phone: (949) 824-3276
Address: 2226 Bren Hall
Return to topThis profile was created with the help of AI.
Last updated on 8/22/2026.