Jin Jin, PhD
Assistant Professor of Biostatistics
Dr. Jin’s research focuses on developing statistical methods and computational tools to address cutting-edge problems in public health and medicine by integrating large-scale, multi-source datasets. Her research areas include health equity issues in disease risk prediction, statistical genetics, and Bayesian hierarchical models for high-dimensional, complex-structured data. Dr. Jin’s methods to build risk models based on genetic, behavioral, and sociodemographic factors has led to insights into nephrology, mental health, and COVID-19, including a lead author paper in Nature Medicine, and can be broadly applied to other medical settings. She will develop and apply these approaches to build multi-modal risk models for underrepresented minority communities that promise to make substantial contributions to characterizing and understanding health disparities and improving health outcomes for underrepresented minority populations.
Content Area Specialties
Disease risk prediction, polygenic risk score, genetic epidemiology, health equity.
Bayesian Modeling, statistical genetics, predictive modeling, Mendelian randomization.