The last decade has seen an unprecedented explosion of data. In medicine, data are increasingly being generated and linked across electronic health records, administrative databases, and biobanked samples. These resources hold tremendous promise for improving human health and achieving precision medicine, which will only be realized by thoughtful study designs and innovative analyses.

My lab uses novel computational methods grounded in genetic epidemiology and statistical genetics to capitalize on today’s big data resources. We aim to understand how genetic and epigenetic differences between people contribute to variation in disease susceptibility, response to treatment, and recovery. A primary goal of our research is to reduce the suffering associated with psychiatric disorders, many of which first manifest in childhood and adolescence. We conduct studies in large population datasets, with a major interest in electronic health records and biobanks, and we work at the intersection of genetics, epidemiology, statistics, bioinformatics, and computer science.