Ke Zhu

Ke Zhu

Postdoctoral Research Scholar in Statistics

I’m Ke Zhu, a Postdoctoral Research Scholar jointly affiliated with North Carolina State University and Duke University, mentored by Dr. Shu Yang and Dr. Xiaofei Wang. I received my PhD from Tsinghua University, where I was advised by Dr. Hanzhong Liu.

My research focuses on developing statistical methodology and theory for causal inference, data integration, and uncertainty-aware machine learning. Driven by real-world challenges, I apply these methods to clinical trials, precision medicine, and policy evaluation.

My CV is available here.

News

Professional Experience

Publications

(† indicates co-first author; * indicates corresponding author)

[1] Yi Liu, Ke Zhu, Larry Han, and Shu Yang* (2026). COADVISE: Covariate adjustment with variable selection in randomized controlled trials. Journal of the Royal Statistical Society: Series A, in press. [Package]

[2] Yi Liu, Alexander W. Levis, Ke Zhu, Shu Yang, Peter B. Gilbert, and Larry Han* (2026). Privacy-protected causal survival analysis under distribution shift. The 14th International Conference on Learning Representations (ICLR). [Package]

[3] Ke Zhu, Shu Yang*, and Xiaofei Wang (2025). Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing. Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR, 267: 80282-80309. [Slides] [Poster] [Package] [Code]

** Winner of the NISS New Researcher Presentation Award at the NISS Virtual New Researchers Conference

** Winner of the NSF Travel Award for the 10th Workshop on Biostatistics and Bioinformatics

[4] Ke Zhu†, Jianing Chu†, Ilya Lipkovich, Wenyu Ye, and Shu Yang* (2025). Doubly robust fusion of many treatments for policy learning. Proceedings of the 42nd International Conference on Machine Learning (ICML), PMLR, 267: 79772-79789. [Slides] [Poster]

[5] Haoyang Yu, Ke Zhu*, and Hanzhong Liu (2025). Sharp variance estimator and causal bootstrap in stratified randomized experiments. Statistics in Medicine, 44(13-14): e70139. [Paper] [Package] [Code]

[6] Ke Zhu, Hanzhong Liu*, and Yuehan Yang* (2025). Design-based theory for lasso adjustment in randomized block experiments and rerandomized experiments. Journal of Business & Economic Statistics, 43(3): 544-555. [Paper] [Slides] [Code]

[7] Ke Zhu, and Hanzhong Liu* (2024). Rejoinder to reader reaction “On exact randomization-based covariate-adjusted confidence intervals” by Jacob Fiksel. Biometrics, 80(2): ujae052. [Paper] [Code]

[8] Ke Zhu, and Hanzhong Liu* (2023). Pair-switching rerandomization. Biometrics, 79(3): 2127-2142. [Paper] [Code]

[9] Ke Zhu, and Hanzhong Liu* (2022). Confidence intervals for parameters in high-dimensional sparse vector autoregression. Computational Statistics & Data Analysis, 168: 107383. [Paper]

Submitted Papers

[10] Ke Zhu, Rima Izem, Peng Yang, Ying Yuan, Herbert Pang, Mark van der Laan, Lei Nie, Birol Emir, Pallavi Mishra-Kalyani, Hana Lee, and Shu Yang* (2026). Externally Controlled Trials: A Review of Design and Borrowing Through a Causal Lens.

[11] Chenxi Li, Ke Zhu, Shu Yang, and Xiaofei Wang* (2026). Selective Information Borrowing for Region-Specific Treatment Effect Inference under Covariate Mismatch in Multi-Regional Clinical Trials.

[12] Yi Liu, Alexander W. Levis, Ke Zhu, Shu Yang, Peter B. Gilbert, and Larry Han* (2025). Targeted Data Fusion for Region-Specific Survival Effects in the AMP HIV Prevention Trials.

[13] Jiajun Liu†, Ke Zhu†, Shu Yang, and Xiaofei Wang* (2025). Robust estimation and inference in hybrid controlled trials for binary outcomes: A case study on non-small cell lung cancer. [Package]

[14] Tingxuan Han†, Ke Zhu†, Hanzhong Liu*, and Ke Deng* (2025). Imputation-based randomization tests for randomized experiments with interference. [Package]

[15] Jiuyao Lu, Tianruo Zhang, and Ke Zhu* (2025) Fast rerandomization for balancing covariate in randomized experiments: A Metropolis–Hastings framework.

[16] Xin Lu, Wanjia Fu, Hongzi Li, Haoyang Yu, Honghao Zhang, Ke Zhu*, and Hanzhong Liu (2025). Design-based Theory for Causal Inference (in Chinese).

Interdisciplinary Collaborations

[17] Fei Xia, Ke Zhu, Yuanyuan Ren, and Ningyu Wang* (2024). Efficacy of the automated mechanical repositioning chairs treatment for patients with benign paroxysmal positional vertigo. The Journal of Laryngology and Otology, in press.

[18] Chenhao Hu, Ke Zhu, Kun Huang, Bo Yu, Wenchen Jiang, Kaiping Peng, and Fei Wang* (2022). Using natural intervention to promote subjective well-being of essential workers during public-health crises: A study during the COVID-19 pandemic. Journal of Environmental Psychology, 79: 101745.

[19] Huachen Zhang, Ke Zhu, Jiangdian Wang, and Xianli Lv* (2022). The use of a new classification in endovascular treatment of dural arteriovenous fistulas. Neuroscience Informatics, 2(2): 100047.

[20] Ke Zhu†, Yingkai Jiang†, Xiang Wang, Zhicheng Shi, Chao Yang, Hanzhong Liu*, and Ke Deng* (2022). A new framework of customized production product certification based on the combination of domain knowledge and data inference (in Chinese). Chinese Journal of Applied Probability and Statistics, 38(4), 581–602.