Jian Kang is an Associate Professor in the Department of Biostatistics and is a faculty member of the Kidney Epidemiology and Cost Center (KECC) at the University of Michigan. He received his Ph.D. in Biostatistics from the University of Michigan in 2011. He was an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Radiology and Imaging Sciences at Emory University from 2011 - 2015. He was a core faculty member in the Center for Biomedical Imaging Statistics (CBIS) at Emory University. His primary research interests are in developing statistical methods for large-scale complex biomedical data with application in precision medicine, imaging, epidemiology and genetics.
- PhD, Biostatistics, University of Michigan, Ann Arbor, 2011
- MS, Mathematics, Tsinghua University, 2007
- BS, Statistics, Beijing Normal University, 2005
Research Interests & Projects
- Statistical Methods for Big data, Bayesian methods, Imaging Statistics (fMRI, PET and DTI), Spatial Statistics, Independent Component Analysis, Composite Likelihood, Graphical Models, Survival Analysis, Longitudinal data analysis, Functional data analysis, Bioinformatics and Statistical Genetics.
- Kang J, Hong GH, Li Y (2017) Partition-based ultrahigh dimensional variable screening, Biometrika, In Press.
- Hong GH, Kang J, Li Y (2017) Conditional screening for ultra-high dimensional covariates with survival outcomes. Lifetime Data Analysis, In Press.
- Kang J, Bowman FD, Mayberg H, Liu H (2016) A depression network of functionally connected regions discovered via multi-attribute canonical correlation graphs. NeuroImage, 41:431-441.
- An Q, Kang J, Song R, Hall HI (2016) A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates. Statistics in Medicine, 35(9):1471-1487.
- Zhang G, Huang KC, Xu Z, Tzeng JY, Conneely KC, Guan W, Kang J, Li Y (2016) Across-platform imputation of DNA methylation levels incorporating non-local information using penalized functional regression. Genetic Epidemiology, 40(4):333-340.
- Chen S, Kang J, Xing Y, Wang G (2015) A parsimonious statistical method to detect group wise differentially expressed functional connectivity networks. Human Brain Mapping, 36(12):5196-5206.
- Wager TD, Kang J, Johnson TD, Nichols TE, Satapute AB, Feldman Barrette L (2015) A Bayesian model of category-specific emotional brain responses. PLOS Computational Biology, 11(4): e1004066.
- Bai Y, Kang J, Song P (2014) Efficient pairwise composite likelihood estimation for spatial-clustered data. Biometrics, 70(3):661-670.
- Kang J, Nichols TE, Wager TD, Johnson TD (2014) A Bayesian hierarchical spatial point process model for multi-type neuroimaging meta-analysis. Annals of Applied Statistics, 8(3): 1800-1824
- Kang J, Zhang N, Shi R (2014) A Bayesian nonparametric model for multivariate spatial binary data with application to a multidrug-resistant tuberculosis (MDR-TB) study. Biometrics, 70(4):981-992.
- Xue W, Kang J, Bowman FD, Guo J, Wager TD (2014) Identifying functional co-activation patterns in neuroimaging studies via Poisson graphical models. Biometrics, 70(4):812-822.
- Zhao Y, Kang J, Yu T (2014) A Bayesian nonparametric mixture model for selecting gene and gene-sub network. Annals of Applied Statistics, 8(2):999-1021.
- Kang J, Ye W, Wang L, Veiga-Lopez A, Padmanabhan V, Song P (2012) Local mixed-effects fitting for detecting reproductive hormone surge times. Statistics in BioSciences, 4(2):245-261.
- Taylor SF, Kang J, Brege IS, Tso IF, Hosanagar A, Johnson TD (2012) Meta-analysis of functional neuroimaging studies of emotion perception and experience schizophrenia. Biological Psychiatry, 71(2):136-145.
- Kang J, Johnson TD, Nichols TE, Wager TD (2011) Meta analysis of functional neuroimaging data via Bayesian spatial point processes. Journal of the American Statistical Association, 106(493):124-134.
- Yang Y, Kang J (2010) Joint analysis of mixed Poisson and continuous longitudinal data with nonignorable missing values. Computational Statistics & Data Analysis, 54:193-207.
- Yang Y, Kang J, Mao K, Zhang J (2007) Regression models for mixed Poisson and continuous longitudinal data. Statistics in Medicine, 26:3782-3800.
- 2016 Program Chair, Section on Imaging Statistics, American Statistical Association
- Member, American Statistical Association
- Member, International Biometrics Society
- Member, International Society for Bayesian Analysis