I’m Ke Zhu, a Postdoctoral Research Scholar jointly affiliated with North Carolina State University and Duke University. I completed my PhD at Tsinghua University under the guidance of Dr. Hanzhong Liu. Currently, I am mentored by Dr. Shu Yang and Dr. Xiaofei Wang, focusing on utilizing real-world data (RWD) to enhance the efficiency and robustness of causal inference in clinical trials. My research interests include the design and analysis of complex experiments, randomization inference, and high-dimensional statistics.

Education

• Ph.D. in Statistics, Tsinghua University, 2023
• B.A. in Economics, Peking University, 2018
• B.S. in Statistics, Beijing Normal University, 2017

Technical Reports

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

• [1] Liu, J.*, Zhu, K.*, Yang, S., & Wang, X.† (2025). Robust estimation and inference in hybrid controlled trials for binary outcomes: A case study on non-small cell lung cancer. Submitted.
• [2] Zhu, K.*, Chu, J.*, Lipkovich, I., Ye, W., & Yang, S.† (2025). Doubly robust fusion of many treatments for policy learning. Submitted.
• [3] Liu, Y., Levis, A. W., Zhu, K., Yang, S., Gilbert, P. B., & Han, L.† (2025). Targeted data fusion for causal survival analysis under distribution shift. Submitted.
• [4] Liu, Y., Zhu, K., Han, L., & Yang, S.† (2025). COADVISE: Covariate adjustment with variable selection in randomized controlled trials. Submitted. [Package]
• [5] Zhu, K., Yang, S.†, & Wang, X. (2024). Enhancing statistical validity and power in hybrid controlled trials: A randomization inference approach with conformal selective borrowing. Submitted. [Slides] [Poster] [Package]
• [6] Han, T.*, Zhu, K.*, Liu, H.†, & Deng, K.† (2024). Imputation-based randomization tests for randomized experiments with interference. Submitted. [Package]
• [7] Yu, H., Zhu, K.†, & Liu, H. (2024). Sharp variance estimator and causal bootstrap in stratified randomized experiments. Under revision. [Package]

Publications

• [8] Zhu, K., Liu, H.†, & Yang, Y.† (2024). Design-based theory for lasso adjustment in randomized block experiments and rerandomized experiments. Journal of Business & Economic Statistics, in press. [Paper] [Slides]
• [9] Zhu, K. & Liu, H.† (2024). Rejoinder to reader reaction “On exact randomization-based covariate-adjusted confidence intervals” by Jacob Fiksel. Biometrics, 80(2): ujae052. [Paper] [Slides] [Code]
• [10] Zhu, K. & Liu, H.† (2023). Pair-switching rerandomization. Biometrics, 79(3): 2127-2142. [Paper] [Code]
• [11] Zhu, K. & Liu, H.† (2022). Confidence intervals for parameters in high-dimensional sparse vector autoregression. Computational Statistics & Data Analysis, 168: 107383. [Paper]

Interdisciplinary Collaborations

• [12] Xia, F., Zhu, K., Ren, Y., & Wang, N.† (2024). Efficacy of the automated mechanical repositioning chairs treatment for patients with benign paroxysmal positional vertigo. The Journal of Laryngology and Otology, in press.
• [13] Hu, C., Zhu, K., Huang, K., Yu, B., Jiang, W., Peng, K., & Wang, F.† (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.
• [14] Zhang, H., Zhu, K., Wang, J., & Lv, X.† (2022). The use of a new classification in endovascular treatment of dural arteriovenous fistulas. Neuroscience Informatics, 2(2): 100047.