Jianhui Zhou
Professor
Department of Statistics
University of Virginia
Office: 113 Halsey Hall
Tel: (434) 924-3355
Fax: (434) 924-3076
Email: jz9p at virginia dot edu
Jianhui Zhou
Professor
Department of Statistics
University of Virginia
Office: 113 Halsey Hall
Tel: (434) 924-3355
Fax: (434) 924-3076
Email: jz9p at virginia dot edu
Education
2005 Ph.D. in Statistics University of Illinois at Urbana-Champaign
2000 B.S. in Mathematics University of Science and Technology of China
Research Interests
Dimension Reduction
Robust Statistics
Longitudinal Data Analysis
Functional Data Analysis
Quantile Regression
Growth Curve Modeling
Ph.D. Students
David Perez-Suarez, December 2023. Current Position: Data Scientist contractor.
Tonghao Zhang, May 2021. Current Position: Data Scientist at Facebook.
Ye Lin, May 2020. Current Position: Quantitative Analyst at Barclays.
Yin Zhang, May 2018. Current Position: Machine Learning Engineer at Facebook.
Miao Lu, December 2016. Current Position: Research Scientist at Yahoo Research.
Xiaoming Li (co-advised with Prof. Feifang Hu, now at George Washington University), September 2015. Current Position: Senior Statistician at Johnson & Johnson Pharmaceutical Research & Development.
Feiyang Niu, September 2015. Current Position: Applied Scientist at Amazon.
Yue Liu (co-advised with Prof. Lei Liu, now at Washington University at St. Louis), December 2012. Current Position: Senior Principal Statistician at Takeda Oncology.
Publications ( * denotes Ph.D. students advised or co-advised)
[29] Tang, D., Tong, X., Zhou, J., and Boichuk, J. (2025). A Comparative Evaluation of a Conditional Median-Based Bayesian Growth Curve Modeling Approach with Missing Data. Structural Equation Modeling: A Multidisciplinary Journal. Accepted.
[28] Zhng, T.*, Tong, X., Zhou, J. (2022). Disentagling the Influence of Data Contamination in Growth Curve Modeling: A Median Based Bayesian Approach. Journal of Behavioral Data Science, 2(2), 1-22.
[27] Xu, P., Yue, Y., Sun, J., Sun, X., Du, H., Liu, Z., Simha, R., Zhou, J., Zeng, C, and Lu, H. (2022). Pattern Decorrelation in the Mouse Medial Prefrontal Corte Enables Social Preference and Requires MeCP2. Nature Communications, 13, 3899.
[26] Kim, S., Tong, X., Zhou, J., and Boichuk, J. (2021). Conditional Median Based Bayesian Growth Mixture Modeling for Nonnormal Data. Behavior Research Methods. Accepted.
[25] Tong, X., Zhang, T.*, and Zhou, J. (2021). Robust growth curve modeling using conditional medians. British Journal of Mathematical and Statistical Psychology, 74, 286-312.
[24] Lin, Y.*, Zhou, J., Kumar, S., Xie, W., Jensen, S., Haque, R., Nelson, C., Petri, W., and Ma, J. (2020). Group penalized generalized estimating equation for correlated event-related potentials and biomarker selection. BMC Medical Research Methodology, 20, 221.
[23] Liu,, Y.*, Lin, Y.*, Zhou, J., and Liu, L. (2020). A semi-parametric joint latent class model with longitudinal and survival data. Statistics and Its Interface, Vol. 13, No. 3, 411-422.
[22] Li, X.*, Zhou, J., and Hu, F. (2018). Hypothesis testing under adaptive randomization to balance continuous covariates. Statistical Methods in Medical Research. 2019, Vol 28(6): 1609:1621. Published online before print May 17, 2018.
[21] Lu, M.*, Zhou, J., Naylor, C., Kirkpatrick, B., Haque, J., Petri, W., and Ma, J. (2017). Application of penalized linear regression methods to the selection of environmental enteropathy biomarkers. Biomarker Research. 2017 5:9.
[20] Zhang, Y.*, Zhou, J., Niu, F.*, Donowitz, J., Haque, J., Petri, W., and Ma, J. (2017). Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis. BMC Pediatrics. 2017 17:84.
[19] Wang, P., Zhou, J., and Qu, A. (2016). Correlation structure selection for longitudinal data with diverging cluster size. The Canadian Journal of Statistics, Vol. 44, Issue. 3, 343-360.
[18] Liu, Y.*, Liu, L., and Zhou, J. (2015). Joint latent class model of survival and longitudinal data: An application to CPCRA study. Computational Statistics and Data Analysis, Vol. 91, 40-50.
[17] Niu, F.*, Zhou, J., Le, T., and Ma, J. (2015). Testing the trajectory difference in a semi-parametric longitudinal model. Statistical Methods in Medical Research. 2017, Vol. 26(3): 1519-1531. Published online before print May 13, 2015.
[16] Liu, Z., Veeraraghavan, M, Zhou, J., and Li, Y. (2013). On causes of GridFTP transfer throughput variance. Proceedings of 3rd IEEE/ACM International Workshop on Network-aware Data Management.
[15] Hong, H. G. and Zhou, J. (2013). A multi-index model for quantile regression with ordinal data. Journal of Applied Statistics, Vol. 40, No. 6, 1231-1245.
[14] Zhou, J., Wang, NY, and Wang, N. (2013). Functional linear model with zero-value coefficient function at sub-region. Statistica Sinica, Vol. 23, No. 1, 25-50.
[13] Wang, H., Zhou, J., and Li, Y. (2013). Variable selection for censored quantile regression. Statistica Sinica, Vol. 23, No. 1, 145-167.
[12] Zhou, J., and Qu, A. (2012). Informative estimation and selection of correlation structure for longitudinal data. Journal of the American Statistical Association, Vol. 107, No. 498, 701-710.
[11] Wang, L, Zhou, J., and Qu, A. (2012). Penalized generalized estimating equations for high-dimensional longitudinal data analysis. Biometrics, Vol. 68, 353-360 .
[10] Gwise, T., Zhou, J., and Hu, F. (2011). An optimal response adaptive biased coin design with K heteroscedastic treatments. Journal of Statistical Planning and Inference. Vol. 141, No. 1, 235-242.
[9] Xue, L, Qu, A., and Zhou, J. (2010). Consistent model selection for marginal generalized additive model for correlated data. Journal of the American Statistical Association. Vol. 105, No. 492, 1518-1530.
[8] He, X. and Zhou, J. (2010). Discussion of "Envelope models for parsimonious and efficient multivariate linear regression" by Cook, Li and Chiaromonte. Statistica Sinica. Vol. 20, No. 3, 971-978.
[7] Zhou, J. (2009). Robust dimension reduction based on canonical correlation. Journal of Multivariate Analysis. Vol. 100, No. 1, 195-209.
[6] Wang, H., Zhu, Z., and Zhou, J. (2009). Quantile regression in partially linear varying coefficient models. Annals of Statistics, Vol. 37, No. 6, 3841-3866.
[5] Zhou, J. and He, X. (2008). Dimension reduction based on constrained canonical correlation and variable filtering. Annals of Statistics. Vol. 36, No. 4, 1649-1668.
[4] Ni, L., Wang, H., Tsai, C.-H., and Zhou, J. (2008). Variable selection via multivariate adaptive group lasso. Proceedings of the Joint Statistical Meetings.
[3] Zhou, J., Zhu, Z., and Fung, W. K. (2008). Robust testing with generalized partial linear models for longitudinal data. Journal of Statistical Planning and Inference. Vol. 138, No. 6, 1871-1883.
[2] Boente, G., He, X., and Zhou, J. (2006). Robust estimates in generalized partially linear models. Annals of Statistics, Vol. 34, No. 6, 2856-2878.
[1] Simpson, D., Ho, M., Yang, Y., Zhou, J., Zachary, J., and O'Brien, W. (2004). Excess risk thresholds in ultrasound safety studies: statistical methods for data on occurrence and size of lesions. Ultrasound in Medicine and Biology, Vol. 30, 1289-1295.