Research in the Ge Lab broadly focuses on statistical genetics and neuroimaging genetics. We develop new statistical, computational and machine learning methods to analyze and integrate large-scale genomic, neuroimaging, behavioral and electronic health records data, in order to (i) understand the genetic architecture of human complex traits and common diseases; (ii) unravel the biological basis of brain structure and function, and the genetic and neural underpinnings of mental disorders; and (iii) improve individualized prediction of disease risk, development, severity and progression.