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Qi Zheng, PhD

Bioinformatics and Biostatistics

Assistant Professor 
Room No.123, 485 E. Gray St
Louisville, KY 40202
Phone: 502-852-8780
Fax: 502-852-3294 
qi.zheng@louisville.edu

CURRICULUM VITAE

Background

Postdoctoral fellow (2015) Bioinformatics and Biostatistics, Emory University.

Ph.D. (2013) Mathematical Science, Clemson University.

B.S. (2006) Mathematics and Applied Mathematics, Nanjing University, China

I joined the Department of Bioinformatics and Biostatistics in Fall of 2015.

Research Interests

My primary research interests are high dimensional data analysis, semiparametric and nonparametric models, varying effects survival analysis, personalized treatments, tree-based learning methods, and statistical applications in epidemiology and biomedical sciences.

Publications

Zheng, Q., Peng, L., and He, X. (2017) Censored quantile regression in ultrahigh dimensional survival data. Annals of Statistics.

Cui, Y. and Zheng, Q. (2017) Conditional maximum likelihood estimation for a class of observation- driven time series models for count data. Accepted Statistics & Probability Letters

Zheng, Q., Gallagher, C., and Kulasekera, K.B. (2017) Robust adaptive Lasso for variable selection.  Communication in Statistics - Theory and Methods 46 (9), 4642--4659.

Zheng, Q. and Peng, L. (2017) Consistent model identification of varying coefficient quantile regression with BIC tuning parameter selector. Communication in Statistics - Theory and Methods 46 (3), 1031--1049.

Li, J., Zheng, Q., Peng, L., and Huang, Z. (2016) Survival impact index and ultrahigh-dimensional model-free screening with survival outcomes.  Biometrics 72 (4), 1145--1154.

Zheng, Q., Peng, L., and He, X. (2015) Globally adaptive quantile regression with ultrahigh dimensional data. Annals of Statistics, 43 (5), 2225--2258.

Zheng, Q., Gallagher, C., and Kulasekera, K.B. (2013) Adaptively weighted kernel regression, Journal of Nonparametric Statistics, 25 (4), 855-872.

Zheng, Q., Kulasekera, K.B., and Gallagher, C. (2013) Adaptive penalized quantile regression for high dimensional data, Journal of Statistical Planning and Inference, 142 (6), 1029-1038.

Zheng, Q., Gallagher, C., and Kulasekera, K.B. (2013) The growth rate of significant regressors for high dimensional data, Statistics & Probability Letters, 83 (9), 1969-1972.

Zheng, Q., Kulasekera, K.B., and Gallagher, C. (2010) Local adaptive smoothing in kernel regres- sion estimation, Statistics & Probability Letters, 80 (7-8), 540-547.

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