Jian Huang

Professor of Statistics and Actuarial Science, College of Liberal Arts and Sciences

Contact Information

Primary Office: 241 Schaeffer Hall (SH)


  • PhD in Statistics, University of Washington, Seattle, Washington, 1994
  • MS in Mathematical Statistics, Wuhan University, Wuhan, China, 1987
  • BS in Mathematics, Wuhan University, Wuhan, China, 1985

Areas of Research Interest

  • High-dimensional statistics
  • Semiparametric inference: Area of Research Interest
  • Statistical genetics: Area of Research Interest
  • Survival analysis: Area of Research Interest

Selected Publications

  • Ma, S., Huang, J. (2017). A concave pairwise fusion approach to subgroup analysis. Journal of the American Statistical Association, 112(517), 410-423. DOI: 10.1080/01621459.2016.1148039.
  • Huang, Y., Zhao, Q., Zhang, S., Huang, J. & Ma, S. (2017). Promoting similarity of sparsity structures in integrative analysis with penalization. Journal of the American Statistical Association, 112, 342-350.
  • Yi, C., Huang, J. (2017). Semismooth Newton coordinate descent algorithm for elastic-net penalized Huber loss regression and quantile regression. Journal of Computational and Graphical Statistics, 26, 547-557.
  • Lin, H., He, Y. & Huang, J. (2016). A global partial likelihood estimation in the additive Cox proportional hazards model. Journal of Statistical Planning and Inference, 169, 71-78. DOI: 10.1016/j.jspi.2015.08.002.
  • Tan, A., Huang, J. (2016). Bayesian inference for high-dimensional linear regression under mnet priors. The Canadian Journal of Statistics, 44(2), 189-197.
  • Huang, J., Breheny, P., Lee, S., Ma, S. & Zhang, C. (2016). The Mnet method for variable selection. Statistica Sinica, 26, 903-923.
  • Shi, X., Zhao, Q., Huang, J., Xie, Y. & Ma, S. (2015). Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach. Bioinformatics, 31, 3977-3983. DOI: 10.1093/bioinformatics/btv518.
  • Jiang, D., Huang, J. (2015). Concave 1-norm group selection. Biostatistics, 16(2), 252-267. PMID: 25417206.
  • Breheny, P., Huang, J. (2015). Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors. Statistics and Computing, 25, 173-187.
  • Liu, J., Huang, J. & Ma, S. (2014). Integrative analysis of cancer diagnosis studies with composite penalization. Scandinavia Journal of Statistics, 41, 87-103. DOI: 10.1111/j.1467-9469.2012.00816.x.
Last Modified Date: March 23, 2020