Publications

Representative Works

The following works best describe who I am as a researcher. For a list of complete works, see my CV.

Note: * indicates co-first authors

Econometrics & Statistics

1. Distributionally Robust Instrumental Variables Estimation

with Yongchan Kwon. Working Paper (2024).

2. Handling Heteroskedastic and Sparse Non-negative Data: A Bias-Variance Trade-off Approach

with Agostino Capponi. Working Paper (2024).

3. Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference

with Ruoxuan Xiong*, Jizhou Liu, and Guido Imbens. Under Revision at Journal of Business and Economic Statistics (2024).

4. Computationally Efficient Estimation of Large Probit Models

with Patrick Ding, Guido Imbens, and Yinyu Ye. Under Review (2023).

5. Ensemble Methods for Causal Effects in Panel Data Settings

with Susan Athey, Mohsen Bayati, and Guido Imbens. American Economic Association Papers and Proceedings 109: 65-70 (2019).

Operations Research, Machine Learning & AI

6. Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting

with Serina Chang*, Frederic Koehler*, Jure Leskovec, and Johan Ugander. 41st International Conference on Machine Learning (ICML) (2024).

7. On Sinkhorn’s Algorithm and Choice Modeling

with Alfred Galichon and Johan Ugander. Under Revision at Operations Research (2023).

8. Optimal Diagonal Preconditioning

with Wenzhi Gao*, Oliver Hinder, Yinyu Ye, and Zhengyuan Zhou. Operations Research (2023).

9. A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg

with Kaixiang Lin*, Zhaojian Li, Jiayu Zhou, and Zhengyuan Zhou. Journal of Artificial Intelligence Research 78: 1143-1200 (2023).