Zhaonan Qu

Welcome to my personal website!

I recently received my PhD in January 2024 in the Department of Economics at Stanford University, where my advisor was Professor Guido Imbens. I was also mentored by Professor Alfred Galichon, Professor Han Hong, and Professor  Yinyu Ye. Currently I am a postdoctoral researcher in Professor Johan Ugander's group at Stanford University's MS&E department. 

My research interests include econometrics, causal inference, optimization, data science, and particularly the interactions between them in theoretical, empirical, and policy questions.

Here is my CV.

Select Works (* denotes co-first authors)

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting with Serina Chang*, Frederic Koehler*, Jure Leskovec, and Johan Ugander. Under Review (2024).

On Sinkhorn's Algorithm and Choice Modeling with Alfred Galichon and Johan Ugander. Under Review (2023).

Computationally Efficient Estimation of Large Probit Models with Patrick Ding, Guido Imbens, and Yinyu Ye (2023).

Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference with Ruoxuan Xiong*, Jizhou Liu, and Guido Imbens. Under Revision (2021).

Optimal Diagonal Preconditioning with Wenzhi Gao*, Oliver Hinder, Yinyu Ye, and Zhengyuan Zhou. Forthcoming at Operations Research (2024).

A Unified Linear Speedup Analysis of Stochastic FedAvg and Nesterov Accelerated FedAvg with Kaixiang Lin*, Zhaojian Li, Jiayu Zhou, and Zhengyuan Zhou. Journal of Artificial Intelligence Research 78: 1143-1200 (2023). 

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).