Cheng Yong Tang

Dr. Cheng Yong Tang is currently Associate Professor and the SeymourWolfbein Senior Research Fellow of Fox School of Business at Temple University. He is an Associate Editor for Reproducibility of Journal of the American Statistical Association, Application and Case Studies, an Associate Editor of Journal of Business and Economic Statistics. He served as the Director of the Graduate Programs in Statistics of the Department of Statistical Science in 2016-2019. Dr Tang is an Elected Member of the International Statistical Institute, a member of the American Statistical Association, a member of the Institute of Mathematical Statistics, and a member of the International Chinese Statistical Association.

Dr. Tang’s research is broad on data science and statistical methodology for solving practical problems. His current interests include empirical likelihood, longitudinal and dependent data analysis, high-dimensional inferences and nonparametric methods. Dr Tang’s research experience covers applied topics in data sciences, finance, econometrics, sampling survey statistics, statistical and machine learning.

Dr. Tang has published 30 research articles, with 18 of them in top econometrics and statistics journals, including the Journal of Econometrics, Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of the Royal Statistical Society, Series B, and Annals of Applied Statistics. Dr Tang’s research has been funded by the NSF. He has been the sole PI of two NSF Grants, one on methods for longitudinal data analysis supported by the Division of Social and Economics Sciences, and the other on ensemble learning methods with random projections supported by the BIGDATA program.

Dr. Tang has been the recipient of numerous honors and awards. He received the distinguished 2019 ICSA President’s Citation Award. In the Fox School of Business and Management of Temple University, he has received awards including the Dean’s Research Honor Roll, Top 10 Highly Cited Faculty Members, and High Achievements in Sponsored Projects. He also received the National University of Singapore’s Young Scientist Award and Teaching Excellence Award, the IMS Laha Award, and Iowa State University’s Research Excellence and Teaching Excellence Awards.

Research Areas

• Empirical likelihood
• Longitudinal and dependent data analysis
• High-dimensional data analysis
• Financial statistics and econometrics
• Sampling statistics and analysis of missing data
• Nonparametric and semiparametric statistical methods

Education

• 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.

Sample Publications

• TANG, C. Y., ZHANG, W., AND LENG, C. (2019). Discrete longitudinal data modeling with a mean-correlation regression approach. Statistica Sinica. 29 853-876.
• CHANG, J., TANG, C. Y., ANDWU, T. T. (2018). Anew scope of penalized empirical likelihood with high-dimensional estimating equations. Annals of Statistics. 46, 3185-3216.
• CHANG, J., TANG, C. Y. § AND WU, Y. (2016). Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood. Annals of Statistics. 44 515-539.
• 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.
• Tang, CY, WU, TT. (2014). Nested coordinate descent algorithms for empirical likelihood. Journal of Statistical Computation and Simulation.
• Chang, J, Tang, CY, Wu, Y. (2013). Marginal empirical likelihood and sure independence screening. Annals of Statistics. 41 2132-2148.
• Liu, C, Tang, CY. (2013). A state space model approach to integrated covariance matrix estimation with high frequency data. Statistics and Its Interface (Special FERM2012 Issue, invited article). 6 463-475.

Awards and Honors

• ICSA 2019 President’s Citation Award.
• Seymour Wolfbein Senior Research Fellow, Fox School of Business, Temple University.
• Dean’s Research Honor Roll, Fox School of Business, Temple University.
• High Achievements in Sponsored Projects, Fox School of Business, Fox School of Business, Temple University.
• Top 10 Highly Cited Faculty Members, Fox School of Business, Temple University.
• Young Scientist Award, Faculty of Science, National Univ. of Singapore.
• Elected member, International Statistical Institute (ISI), 2012.

Teaching

• Fall 2019 STAT 8001 Probability and Statistical Theory I
• Spring 2019 STAT 8004 Statistical Methods II
• Spring 2019 STAT 8114 Survival Analysis I
• Fall, 2018 STAT 8003 Statistical Methods I
• Spring, 2018 STAT 9190 Topics on Longitudinal Data Analysis
• Spring, 2018 STAT 8004 Statistical Methods II
• Fall, 2017 STAT 8003 Statistical Methods I
• Spring, 2017 STAT 8114 Survival Analysis I
• Spring, 2017 STAT 8004 Statistical Methods I
• Fall, 2016 STAT 8003 Statistical Methods I
• Spring, 2016 STAT 8004 Statistical Methods II
• Spring, 2016 STAT 8102 Statistical Methods III
• Spring, 2015 STAT 8004 Statistical Methods II
• Spring, 2015 STAT 8114 Survival Analysis I
• Fall, 2014 STAT 8102 Statistical Methods III