Research InterestsÂ
My research mainly focuses on developing effective and efficient statistical learning methods and computational tools to address emerging challenges in complex biomedical data and improve clinical practice in diverse populations. In particular, I have been working on (1) data integration methods for incorporating multiple types of auxiliary information with time-to-event data, (2) statistical optimization algorithms for integrative analysis of complex and potentially heterogenous databases, (3) joint modeling of genotype and survival data based on electronic health records (EHR) linked biobanks, and (4) genetic risk prediction in diverse-ancestry populations.
I am also passionate about collaborative research in renal disorders, kidney transplantation, diabetes prevention, precision medicine, and cancer research.
Methodology: Data integration, survival analysis, statistical learning, high dimensional data analysis, and statistical genetics.
Application: Risk prediction, precision medicine, kidney transplantation, diabetes prevention, and cancer research.