Hanzhong Liu Associate Professor

Research Areas: high dimensional statistical inference, causal inference

Office: Room 212-B, Weiqing Building, Tsinghua University

Phone: +86-10-62780575

Email: lhz2016@tsinghua.edu.cn

  • Ph.D in Statistics, Peking University
  • Visiting Student, Department of Statistics, University of California at Berkeley
  • Postdoctoral Scholar, Department of Statistics, University of California at Berkeley

  • Liu, H., Xu, X., & J. J. Li (2020). A bootstrap Lasso + Partial Ridge method to construct confidence intervals for parameters in high-dimensional sparse linear models. Statistica Sinica, 30, 1333-1355.
  • Liu, H., & Yang, Y. (2019). Regression-adjusted average treatment effect estimates in stratified randomized experiments. Biometrika.
  • Liu, H., & Yu, B. (2017). Comments on: High-dimensional simultaneous inference with the bootstrap. Test26(4), 740-750.
  • Bloniarz, A., Liu, H., Zhang, C. H., Sekhon, J. S., & Yu, B. (2016). Lasso adjustments of treatment effect estimates in randomized experiments. Proceedings of the National Academy of Sciences113(27), 7383-7390.
  • Wu, L., Yang, Y., & Liu, H. (2014). Nonnegative-lasso and application in index tracking. Computational Statistics & Data Analysis70, 116-126.
  • Liu, H., & Yu, B. (2013). Asymptotic properties of Lasso+ mLS and Lasso+ Ridge in sparse high-dimensional linear regression. Electronic Journal of Statistics7, 3124-3169.