I recently received my PhD in Econometrics and Statistics from the University of Chicago Booth School of Business, where I was mentored by Azeem Shaikh and Christian Hansen between 2020 and 2024. In Autumn 2024, I joined Amazon as a Postdoctoral Scientist, where I work on panel data methods and machine learning for policy evaluation with Eric Tchetgen Tchetgen.

My research focuses on causal inference and econometrics, with a particular interest in the design and analysis of randomized experiments.

Curriculum Vitae

Working Papers

Inference for Two-stage Experiments under Covariate-Adaptive Randomization

Revision Requested at the Jour­nal of Econo­met­rics.

Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference (with Zhaonan Qu, Ruoxuan Xiong and Guido Imbens)

Revision Requested at the Journal of Business & Economic Statistics.

On the Effi­ciency of Finely Strat­i­fied Exper­i­ments (with Yuehao Bai, Azeem Shaikh and Max Tabord-Meehan)

We study the efficient estimation of a large class of treatment effect parameters that arise in the analysis of experiments.

Randomization Inference for Two-Sided Market Experiments (with Azeem Shaikh and Panos Toulis)

We propose a randomization inference framework to analyze outcomes from two-sided market experiments.

Publications and Forthcoming Papers

Inference in Cluster Randomized Trials with Matched Pairs (with Yuehao Bai, Azeem Shaikh and Max Tabord-Meehan)

Jour­nal of Econo­met­rics, 245(1), 105873. (2024)

Inference for Matched Tuples and Fully Blocked Factorial Designs (with Yuehao Bai and Max Tabord-Meehan)

Quan­ti­ta­tive Eco­nom­ics, 2024, 15(2), 279–330. (2024)

Revisiting the Analysis of Matched Pair and Stratified Experimental Designs in the Presence of Attrition (with Yuehao Bai, Meng Hsuan Hsieh, and Max Tabord-Meehan)

Jour­nal of Applied Econo­met­rics, 2024, 39(2), 256–268. (2024)

Proximal Causal Inference for Synthetic Control with Surrogates (with Eric J. Tchetgen Tchetgen and Carlos Varjão)

The 27th International Conference on Artificial Intelligence and Statistics (AISTATS). 2024

Learning Intuitive Policies Using Action Features (with Mingwei Ma, Samuel Sokota, Max Kleiman-Weiner, Jakob Foerster)

International Conference on Machine Learning (ICML), 2023

Work in Progress

Auto-G-Computation of Doubly Robust Estimation on a Network (with Eric J. Tchetgen Tchetgen)