Research Fields: Theoretical Statistics, Econometrics, Integration of Economic Models, Machine Learning, and Operations Research

Research Interests: High-Dimensional Estimation and Inference, Nonasymptotic Statistics, Semiparametric and Nonparametric Methods, Panel/Longitudinal Data Analysis (with Both i.i.d. and Temporal Features), Integration of Economic Models and Machine Learning, Causal Inference, Bayesian Methods

• Inference in Approximately Sparse Correlated Random Effects Probit Models with Panel Data by Jeffrey Wooldridge, Ying Zhu (alphabetical author ordering) - The Journal of Business & Economic Statistics, 38, 1-18, 2020 (rejoinder appears in 25-26).
• High Dimensional Inference in Partially Linear Models by Ying Zhu, Zhuqing Yu, Guang Cheng,  AISTATS 2019, PMLR, 89, 2760-2769.
• Sparse Linear Models and l1-Regularized 2SLS with High-Dimensional Endogenous Regressors and Instruments {Additional materials from 2013} by Ying Zhu - The Journal of Econometrics, 202, 196-213, 2018
• Nonasymptotic Analysis of Semiparametric Regression Models with High-Dimensional Parametric Coefficients {Supplementary materials} by Ying Zhu - The Annals of Statistics, 45, 2274–2298, 2017
• Nonparametric Density Estimation Based on Truncated Mean {Supplementary materials} by Ying Zhu - Statistics and Probability Letters, 83, 445-451, 2013 

• Ordinary Differential Equations (ODE): Metric Entropy and Nonasymptotic Theory for Noisy Function Fitting by Ying Zhu, Mozhgan Mirzaei 
• Omitted Variable Bias of Lasso-Based Inference Methods: A Finite Sample Analysis by Kaspar Wuthrich, Ying Zhu (alphabetical author ordering)
• Statistical Inference and Feasibility Determination: A Nonasymptotic Approach by Ying Zhu
• Behavior of Pooled and Joint Estimators in Probit Model with Random Coefficients and Serial Correlation by Alyssa Carlson, Jeffrey Wooldridge, Ying Zhu