Professor, Mathematical Sciences
Endowed Henes Professorship
- PhD, Statistics, Peking University, Beijing, China
- MS, Statistics, Northeast Normal University, Changchun, China
- BS, Mathematics, Hebei Normal University, Shijiazhuang, China
Shuanglin Zhang is an endorsed Henes professor in the Department of Mathematical Sciences at Michigan Technological University. He earned his PhD in Statistics in 1999 from Peking University, China. He did his postdoctoral training in statistical genetics in the Department of Epidemiology and Public Health at Yale University, School of Medicine, from 1999 to 2001.
From 1988 to 1999, he was a faculty member in the Department of Mathematics at Heilongjiang University, China. He has published more than 70 papers in peer reviewed journals. His research was supported by NIH and NSF. In 2008, Professor Zhang received the Michigan Tech research award. Zhang’s research interests lie in various areas of theoretical statistics and statistical genetics. His research topics in theoretical statistics include: nonparametric estimation of density function; regression function and variance function; Profile likelihood based methods; semi-parametric models; and multivariate analysis. In statistical genetics, his research topics include: developing statistical methods and computational tools to map complex disease genes both based on family data and population data; developing statistical methods for genome-wide association studies and sequence data analysis; developing statistical methods for rare variant association; and microarray data analysis.
Links of Interest
Areas of Expertise
- Statistical genetics
- Theoretical Statistics
- Sha Q, Wang X, Wang X, *Zhang SL (2012) Detecting association of both rare and common variants by testing an optimally weighted combination of variants. Genetic Epidemiol 36:561-571
- Sha Q, *Zhang SL (2011) A test of Hardy Weinberg equilibrium in structured populations. Genetic Epidemiol 35:671-678
- Sha Q, Zhang Z, *Zhang SL (2011) An improved score test for multi-marker association. Genetic Epidemiol 35:350-359
- Qin H, Feng T, Zhang SL, Sha Q (2010) A data-driven weighting scheme for family-based genome-wide association studies. Eur J Hum Genet 18:596-603.
- Wang X, Zhang SL, Sha Q (2009) A new association test to test multiple-marker association. Genetic Epidemiol 33:164-171
- Zhang Z, Zhang SL, Wong MY, Wareham NJ, Sha Q (2008) Ensemble learning approach jointly modeling main and interaction effects in genome-wide association studies. Genetic Epidemiol 32:285-300
- Qin H, Feng T, Harding S, Tsai CJ and *Zhang SL (2008) An efficient method to identify differentially expressed genes in microarray experiments. Bioinformatics 24:1583-1589
- Sha Q, Chen H, Zhang SL (2007) New association tests based on haplotype similarity. Genetic Epidemiol 31(6):577-93