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.