Lin Zhang, PhD

My research is based primarily on the development of Bayesian methodology for complex-structured data analysis in the presence of high dimensionality and/or a large sample size, with a focus on biomedical applications. The scientific questions involved in my research include functional connectivity analysis of neuroimaging data, spatial analysis of periodontal and prostate image data, and gene-based genome-side association studies. 

• 2016–2021,NIH Nat'l Heart, Lung, and Blood Inst., "Access to the cardiac catheterization laboratory in patients without ST-segment elevation myocardial infarction resuscitated from out-of-hospital ventricular fibrillation cardiac arrest (The ACCESS Trial- DCC)," Co-Investigator
• 2016–2021, Cystic Fibrosis FDN, "Impact of Insulin Therapy on Protein Turnover in Non-Diabetic CF Patients," Co-Investigator

Selected Recent Publications

• L. Zhang, V. Baladandayuthapani, H. Zhu, K.A. Baggerly, T. Majewski, B.A. Czerniak, J.S. Morris. " Functional CAR models for large spatially correlated functional datasets. JASA Theory and Methods, 
• Zhang L, Sarkar A, Mallick B. "Bayesian sparse covariance decomposition with a graphical structure," Statistics and Computing, Jan 2016
• Zhang L, et al. "Functional CAR models for large spatially correlated functional datasets," Journal of the American Statistical Association, Aug 2016
• Correll C, Spector L, Zhang L, Binstadt BA, Vehe RK. "Use of Rheumatology Laboratory Studies Among Primary Pediatricians," Clinical Pediatrics, Jan 2016