Our research lies at the interface of human genetics, computational statistics, and data science. Current research focuses on understanding diverse behaviors of cells using machine learning, network theory, and quantum computation. We develop analytical frameworks to study single-cell omics data gathered from various types of cells. We also study the genetic basis of phenotypic variability in the human population and develop computational tools to identify variants underlying susceptibility to genetic disorders.
