Dr. Cheng Yong Tang is Professor and the Cyrus C.K. Curtis Senior Research Fellow in the Department of Statistics, Operations, and Data Science in the Fox School of Business of Temple University.
He is an Associate Editor of Journal of the American Statistical Association, Theory and Methods, an Associate Editor of Journal of Business and Economic Statistics, an Associate Editor of Statistica Sinica, and an Associate Editor of Computational Statistics and Data Analysis. He was an Associate Editor for Reproducibility (2019-2022) of Journal of the American Statistical Association, Applications and Case Studies. Dr. Tang is the Director of PhD program in Statistics; he was the Director of the Graduate Programs in Statistics of the Department of Statistical Science in 2016-2019. Dr. Tang is a Fellow of the Institute of Mathematical Statistics, an Elected Member of the International Statistical Institute, a member of the American Statistical Association, and a member of the International Chinese Statistical Association.
Dr. Tang earned his Ph.D. in Statistics from the Department of Statistics, Iowa State University. This is his Mathematical Genealogy. His research interests are methods, theory, and applications in statistics and data science.
- Room 276 Building 1810
1810 Liacouras Walk
Philadelphia, PA 19122-6083
- Phone: (215) 204-3191
- Email: yongtang at temple.edu
- Ph.D in Statistics, Iowa State University, 2008, Advisor: Song X. Chen.
- M.S. in Statistics, National University of Singapore, 2003.
- B.S. in Management Science and Computer Science, University of Science and Technology of China, 2001.
- Guo, X. and Tang, C.Y. (2020). Specification tests for covariance structures in high-dimensional statistical models. Biometrika. 108, 335-351.
- Bruce, S.A., Tang, C.Y., Hall, M. H., and Krafty, R.T. (2020). Empirical frequency band analysis of nonstationary time series. Journal of the American Statistical Association, Theory and Methods. 115, 1933-1945.
- Tang, C.Y., Fang, E.X., and Dong, Y. (2020). High-dimensional interactions detection with sparse principal hessian matrix. Journal of Machine Learning Research. 21(19) 1-25.
- Chang, J., Tang, C.Y., and Wu, T.T. (2018). A new scope of penalized empirical likelihood with high-dimensional estimating equations. Annals of Statistics. 46, 3185-3216.
- Zhang, W., Leng, C. and Tang, C.Y. (2015). A joint modeling approach for longitudinal studies. Journal of the Royal Statistical Society, Series B. 77, 219-238.
- Liu, C. and Tang, C.Y. (2014). A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data. Journal of Econometrics. 180, 217-232.
- Fan, Y. and Tang, C.Y. (2013). Tuning parameter selection in high dimensional penalized likelihood. Journal of the Royal Statistical Society, Series B. 75, 531-552.
- Tang, C.Y. and Leng, C. (2010). Penalized high dimensional empirical likelihood. Biometrika. 97, 905-920.
- Chen, S.X., Tang, C.Y. and Mule, V. T. (2010). Local post-stratification in dual system accuracy and coverage evaluation for the US Census. Journal of the American Statistical Association, Applications and Case Studies. 105, 105-119.