Research Interests
Research Interests
Causal inference
Design and analysis of randomized controlled trials
Observational studies
Large language models
Causal inference
Design and analysis of randomized controlled trials
Observational studies
Large language models
FM Polo, X Wang (co-first authors), M Yurochkin, G Xu, M Banerjee, Y Sun (2025), Bridging Human and LLM Judgments: Understanding and Narrowing the Gap, Advances in Neural Information Processing Systems (arxiv)
X Wang, T Wang, and H Liu (2023), Rerandomization in Stratified Randomized Experiments, Journal of the American Statistical Association, 118:542, 1295-1304, DOI: 10.1080/01621459.2021.1990767 (link)
X Wang, BB Hansen, Design-Based Hájek Estimation for Clustered and Stratified Experiments, Submitted (arxiv)
X Wang, BB Hansen, Design-Based Covariance Estimation for Clustered and Stratified RCTs with Multiple Treatments
Bridging Human and LLM Judgments: Understanding and Narrowing the Gap
Annual Conference on Neural Information Processing Systems (NeurIPS), December 2025
Student Seminar Internship Panel
Department of Statistics, University of Michigan, September 2025
Design-based SE of Hájek Estimators for Causal Effects in Stratified and Clustered Experiments
International Biometric Conference (IBC), December 2024
Student Seminar Internship Panel
Department of Statistics, University of Michigan, September 2024
Design-based analysis of the covariate-adjusted Hájek estimator in stratified and clustered designs
The American Causal Inference Conference (ACIC), May 2024
Design-based variance estimation for Hájek estimators of causal effects in finely stratified and clustered experiments
International Chinese Statistical Association (ICSA), June 2023
Design-based variance estimation for Hájek estimators of causal effects in finely stratified and clustered experiments
The American Causal Inference Conference (ACIC), May 2023