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.

I am on the 2023-2024 job market.

Select Works (* denotes co-first authors)

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).

Machine Learning Workflow for Single-Cell Antimicrobial Susceptibility Testing of Klebsiella pneumoniae to Meropenem in Sub-Doubling Time with Kristel Tjandra, Nikhil Ram-Mohan, Manuel Roshardt, Elizabeth Zudock, Kathleen Mach, Okyaz Eminaga, Joseph Liao, Samuel Yang, and Pak Kin Wong. Under Review at Journal of the American Medical Informatics Association (2022).

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).