I am a Ph.D. student supervised by Dr. Brian Tom and Dr. Robert Goudie. My research project focuses on Developing Dynamic Latent Process Methodology for High-Dimensional Biomarker Data with Correlated Latent Biological Processes, within a Bayesian framework. Prior to joining the MRC Biostatistics Unit, I completed my M.S. in Biostatistics from Yale University, where I worked on spatial-temporal models with Prof. Joshua Warren. Besides, I also had research experience in correcting for measurement error in longitudinal studies, supervised by Prof. Molin Wang and Prof. Donna Spiegelman. My current research interests include Bayesian Statistics, Gaussian Processes, and Sparse Factor Modeling. My linkedin account is available here.

Selected Papers

• Cai J, Zhang N, Spiegelman D, Wang M (2023). Correcting for bias due to mis-measured exposure history in longitudinal studies with continuous outcomes. Biometrics. 
• Zhao Y, Chen T, Cai J, Lichenstein S, Potenza M, Yip S (2022). Bayesian network mediation analysis with application to the brain functional connectome. Statistics in Medicine. 
• Warren JL, Cai J, Johnson NP, and Deziel NC (2021). A discrete kernel stick-breaking model for detecting spatial boundaries in hydraulic fracturing wastewater disposal well placement across Ohio. Journal of the Royal Statistical Society: Series C (Applied Statistics).
• Shioda K, Cai J, Warren JL, and Weinberger DM (2021). Incorporating information on control diseases across space and time to improve estimation of the population-level impact of vaccines. Epidemiology, 32(3):360-367.