Papers

Preprints

• Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective
  Zhexiao Lin, Peter J. Bickel, and Peng Ding, 2026.

• Unifying regression-based and design-based causal inference in time-series experiments
  Zhexiao Lin and Peng Ding, 2025.

• Limit theorems of Chatterjee's rank correlation
  Zhexiao Lin and Fang Han, 2022. “R&R” at Annals of Statistics.

Journal Publications

• Supervised deep learning with gene functional annotation for cell classification
  Zhexiao Lin, Yuanyuan Gao, and Wei Sun. PLOS Computational Biology, 22(6): e1014327, 2026.

• On regression-adjusted imputation estimators of the average treatment effect
  Zhexiao Lin and Fang Han. Journal of Econometrics, 251: 106080, 2025.

• On Rosenbaum's rank-based matching estimator
  Matias D. Cattaneo, Fang Han, and Zhexiao Lin (alphabetical order). Biometrika, 112(1), 2025.

• On the failure of the bootstrap for Chatterjee's rank correlation
  Zhexiao Lin and Fang Han. Biometrika, 111(3): 1063-1070, 2024. (Cover Article in the Journal)

• Estimation based on nearest neighbor matching: from density ratio to average treatment effect
  Zhexiao Lin, Peng Ding, and Fang Han. Econometrica, 91(6): 2187-2217, 2023.

• On boosting the power of Chatterjee's rank correlation
  Zhexiao Lin and Fang Han. Biometrika, 110(2): 283-299, 2023. (Most Read Article in the Journal)

Conference Publications

• Nearest-Neighbor Radii under Dependent Sampling
  Yuanyuan Gao, Yilong Hou, and Zhexiao Lin (alphabetical order), 2026.

• Domain-Shift-Aware Conformal Prediction for Large Language Models
  Zhexiao Lin, Yuanyuan Li, Neeraj Sarna, Yuanyuan Gao, and Michael von Gablenz. International Conference on Machine Learning (ICML), 2026.

• Variance reduction combining pre-experiment and in-experiment data
  Zhexiao Lin and Pablo Crespo. Causal Learning and Reasoning (CLeaR), 2026. (Extended abstract accepted at 2024 CODE@MIT)

• BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation
  Tianhao Zhang*, Zhecheng Sheng*, Zhexiao Lin*, Chen Jiang*, and Dongyeop Kang (*=equal contributions). Empirical Methods in Natural Language Processing (EMNLP), 2025.

• RoVista: Measuring and Understanding the Route Origin Validation (ROV) in RPKI
  Weitong Li, Zhexiao Lin, Mohammad Ishtiaq Ashiq Khan, Emile Aben, Romain Fontugne, Amreesh Phokeer, and Taejoong Chung. ACM Internet Measurement Conference (IMC), 2023.

• Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization
  Y. Guo, N. Hanoian, Z. Lin, N. Liskij, H. Lyu, D. Needell, J. Qu, H. Sojico, Y. Wang, Z. Xiong, and Z. Zou, 2019.