I am the UPMC Professor of Statistics and Life Sciences in the Departments of Statistics and Data Science and Computational Biology. I have developed statistical and machine learning methods in a wide spectrum of areas, including high dimensional data problems in genetics. My work focuses on statistical methods to reveal the genetic basis of complex disease. I am one of the leaders of the Autism Sequencing Consortium, an international organization dedicated to discovering the genetic etiology of autism. I received the Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award (1997), Snedecor Award for outstanding work in statistical applications (1997) and Distinguished Achievement Award and Lectureship (2020). In 2013, I received the Janet L. Norwood Award for outstanding achievement by a woman in statistical sciences. I am an elected fellow of the American Statistical Association, the Institute of Mathematical Statistics and AAAS. In 2019 I was elected to the National Academy of Sciences.
A primary goal of my research group is to develop statistical tools for finding associations between patterns of genetic variation and complex disease. To solve biologically relevant problems, we utilize modern statistical methods such as high dimensional statistics, statistical machine learning, nonparametric methods and networks. Data arises from primarily from Next Generation Sequencing and gene expression arrays. Our methodological work is motivated by our studies of schizophrenia, autism and other genetic disorders.