Zhigen Zhao

Profile Picture of Zhigen Zhao

Zhigen Zhao

  • Fox School of Business and Management

    • Statistics, Operations, and Data Science

      • Associate Professor

      • Beury Research Fellow


Zhigen Zhao graduated from Cornell University in 2009. Dr. Zhao’s research interests include Bayesian/empirical Bayesian statistics, high dimensional data analysis, multiple comparison, bioinformatics, selective confidence intervals. Dr. Zhao has published papers in top tier journals, such as Journal of the Royal Statistical Society, Series B, Journal of the American Statistical Association. Dr Zhao’s current research is supported by national science foundation.

Research Interests

  • High Dimensional Data Analysis
  • Bayesian/Empirical Bayesian Statistics
  • Confidence Intervals
  • Selective Inference
  • Multiple Comparison
  • Bioinformatics
  • Sufficient Dimension Reduction in High Dimensions

Courses Taught




STAT 2512

Intermediate Statistics


STAT 8112

Statistical Methods for Business Research I


STAT 8113

Statistical Methods for Business Research II


Selected Publications


  • Kwon, Y. & Zhao, Z. (2022). On F-modelling-based empirical Bayes estimation of variances. BIOMETRIKA. 10.1093/biomet/asac019

  • Sarkar, S.K. & Zhao, Z. (2022). Local false discovery rate based methods for multiple testing of one-way classified hypotheses. Electronic Journal of Statistics, 16(2). Institute of Mathematical Statistics. doi: 10.1214/22-ejs2080.

  • Xing, X., Zhao, Z., & Liu, J.S. (2021). Controlling False Discovery Rate Using Gaussian Mirrors. JOURNAL of the AMERICAN STATISTICAL ASSOCIATION. 10.1080/01621459.2021.1923510

  • Zhao, Z. (2021). Where to find needles in a haystack? Test. doi: 10.1007/s11749-021-00775-x.

  • Zhao, Z., Lin, Q., & Liu, J. (2021). Global testing under the sparse alternatives for single index models. In Festschrift in Honor of R. Dennis Cook Fifty Years of Contribution to Statistical Science. Springer Nature.

  • Lin, Q., Zhao, Z., & Liu, J.S. (2019). Sparse Sliced Inverse Regression Via Lasso. J Am Stat Assoc, 114(528), 1726-1739. United States. 10.1080/01621459.2018.1520115