Tian Guoliang

Professor Department of Statistics and Data Science

Guo-Liang Tian, Ph.D., is a Full Professor of Statistics at Department of Statistics and Data Science of Southern University of Science and Technology (SUSTech). He was an Associate Professor of Statistics at Department of Statistics and Actuarial Science of the University of Hong Kong. He was a senior bio-statistician at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (Baltimore, Maryland, USA) from 2002 to 2008, a Postdoctoral Research Associate at Department of Biostatistics, St. Jude Children's Research Hospital (Memphis, Tennessee, USA) from 2000 to 2002, and a Postdoctoral Fellowship at Department of Probability and Statistics, Peking University (Beijing, P.R. China) from 1998 to 2000. He earned his Ph.D. in statistics in 1998 from the Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing. He obtained his Master of Statistics in 1988 from Wuhan University. He was an Elected Member of International Statistics Institute. His current research interests include biostatistics, social statistics and computational statistics. He was the author of 14 top tier biostatistics papers and more than 90 other statistics papers in peer-reviewed international academic journals.

Personal Profile

Professional Experience:

2019.8.22 – Present, Professor. Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen City, Guangdong Province, P. R. China

2016.8.1 – 2019.8.21, Professor. Department of Mathematics, Southern University of Science and Technology, Shenzhen City, Guangdong Province, P. R. China

2008.9.1 – 2016.7.31, Associate Professor. Department of Statistics and Actuarial Science,  The University of Hong Kong, Hong Kong, P. R. China

2002.7.1 – 2008.8.31, Senior Biostatistician. Division of Biostatistics, University of Maryland, Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA

2002.7.1 – 2008.8.31, Instructor. Department of Epidemiology and Preventive Medicine, University of Maryland , School of Medicine, Baltimore, Maryland, USA

2000.5.1 – 2002.6.30, Postdoctoral Research Associate. Partner: Prof. Ming Tan. Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

1998.9.1 – 2000.4.30, Postdoctoral Fellowship. Partner: Prof. Zhi Geng. Department of Probability and Statistics, Peking University, Beijing, P. R. China 

1988.8.1 – 1995.8.31,Senior Engineer (Engineer, Assistant Engineer).  Chinese Academy of Air Vehicle, The Ministry of Aerospace Industry, Beijing, P. R. China.

Educational Background:

Ph.D., Statistics. Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing, China 

M.Sc., Statistics. Wuhan University, Wuhan, Hubei Province, P. R. China 

B.Sc., Mathematics. Hunan Normal University, Changsha, Hunan Province, P. R. China.

Honor and Awards:

Peacock Plan Award (Tier B), Shenzhen, 2017 

Professional Memberships:

2000.5 – Present    Member, American Statistical Association

2000.5 – Present    Permanent Member,  International Chinese Statistical Association

2014.6 – Present    Elected member,  International Statistical Institute (ISI)

Professional Services:

Associate Editor, Statistics and Its Interface, 2013 – Present   

Associate Editor, Communications in Statistics - Theory and Methods, 2013 – Present 

Associate Editor, Communications in Statistics - Simulation and Computation, 2013 --– Present 

Associate Editor, Computational Statistics and Data Analysis, 2014 – Present


○ Biostatistics:Multivariate zero-inflated count data analysis, Incomplete categorical data and missing data analysis, Skewed and asymmetric continuous data analysis, Continuous proportional and compositional data analysis, Constrained parameter models and variable selection , Experimental design for drug combination studies, Cancer clinical trial and design


○ Computational Statistics: EM algorithm, MM algorithm


○ Social Statistics: Sample surveys with sensitive questions


MAT7008/MA413,Advanced Statistics, 2016 Autumn Semester

MA204,Mathematical Statistics, 2017, 2018, 2019 Spring Semester

MAT7035, Computational Statistics, 2017, 2018, 2019 Autumn Semester

Publications Read More

Biostatistics Journal 1:

· Statistical Methods in Medical Research [Impact Factor=4.472; Ranking No. 1 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (6 papers)

· Shen X, Ma CX, Yuen KC and Tian GL* (2019). Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data, in press.

· Tian GL, JU D,Yuen KC and Zhang C* (2018). New expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine, 27(8), 2459-2477.

· Tian GL, Zhang C* and Jiang XJ (2018). Valid statistical inference methods for a case-control study with missing data, 27(4), 1001–1023.

· Tian GL and Li HQ (2017). A new framework of statistical inferences based on the valid joint sampling distribution of observed counts in an incomplete contingency table, 26(4) 1712–1736.

· Tian GL, Tang ML, Wu Q and Liu Y (2017). Poisson and negative binomial item count techniques for surveys with sensitive question, 26(2), 931–947.

· Tian GL, Tang ML, Liu ZQ, Tan M and Tang NS (2011). Sample size determination for the non-randomized triangular model for sensitive questions in a survey, 20(3), 159-173.

·Biostatistics Journal 2:

· Statistics in Medicine [Impact Factor=1.825; Ranking No. 3 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (7 papers)

· Pei YB, Tian GL and Tang ML (2014). Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomize clinical trials, 33(25), 4370-4386.

· Tang ML, Ling MH, Ling L and Tian GL (2010). Confidence intervals for a difference between proportions based on paired data, 29(1), 86-96.

· Tang ML, Ling MH and Tian GL (2009). Exact and approximate unconditional confidence intervals for proportion difference in the presence of incomplete data, 28, 625-641.

· Tian GL, Yu JW, Tang ML and Geng Z (2007). A new non-randomized model for analyzing sensitive questions with binary outcomes, 26(23), 4238-4252.

· Fang HB, Tian GL, Xiong XP and Tan M (2006). A multivariate random-effects model with restricted parameters: Application to assessing radiation therapy for brain tumors, 25(11), 1948-1959.

· Tan M, Fang HB, Tian GL and Houghton PJ (2005). Repeated-measures models with constrained parameters for incomplete data in tumor xenograft experiments, 24(1), 109-119.

· Tan M, Fang HB, Tian GL and Houghton PJ (2003). Experimental design and sample size determination for testing synergism in drug combination studies based on uniform measures, 22(13), 2091-2100.

· Biostatistics Journal 3: Biometrics [Impact Factor=1.568; Ranking No. 4 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (1 paper)

· Tan M, Fang HB, Tian GL and Houghton PJ (2002). Small-sample inference for incomplete longitudinal data with truncation and censoring in tumor xenograft models, 58(3), 612-620.

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About Us

The Department of Statistics and Data Science was established in April 2019. As a newly established department, we currently have 8 faculty members including 1 Chair Professor, 2 Professors, 2 Associate Professors , 2 Tenure-track Assistant Professors and 1 Visiting Assistant Professor and anticipant to rapidly expand to a team of more than 20 members. All faculty members of the department have extensive overseas study or work experiences. One member is an invited speaker at the International Congress of Mathematicians, an IMS Medallion Lecturer and a winner of the prestigious State Natural Science Award (2nd class). The department has 2 research directions, Statistics and Data Science, which cover a broad array of research areas including Biostatistics, Financial Statistics, Experiment Design, Clinical Trials, High Dimensional Data, Time series, Probability Theory, Data Science and Big Data Technology.
At present, the department has an undergraduate program as well as two graduate programs(M.Phil and PhD). The department is in the process of developing a Major Program in Data Science and Big Data Technology. In 2019, the first batch of 38 undergraduate students in Statistics received the bachelor degree from SUSTech. 5 M.Phil students in Statistics also graduated in the same year. There are currently 9 M.Phil students, 7 PhD students in Statistics and 2 Postdoctoral Fellows. As the department grows in size and strength, the number of graduate students is expected to rise substantially from the current level and the areas of graduate studies will also expand to include Data Science and Big Data Technology.
This is the age of big data which offers exciting opportunities to researchers in Statistics and Data Science. Our department is expected to grow rapidly in the coming years. We invite outstanding scholars to join us in our journey to become a first-class department in Statistics and Data Science. We also welcome brilliant undergraduate and graduate students to apply for our programs. At the same time, we actively recruit excellent postdoctoral candidates.
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