Kathryn Roeder

I began my career as a biologist, but found that every question that interested me could only be answered by solving an even more intriguing statistical puzzle. Thus my career path veered into statistics. However, much of my work, both theoretical and applied, remains motivated by my scientific training.

The collaborative research I have enjoyed most is in the area of statistical genetics and genomics. Right now, a topic that interests me greatly is the use of statistical tools applied to genetic and genomic data to understand the workings of the human brain, and the interplay with genetic variation. My collaborative work is primarily motivated by the goal of understanding the genetic etiology of autism. We develop new tools for the analysis of single-cell RNA sequencing data and other multiomic data. These methods rely on various statistical methods, including graphical modeling, network community estimation and latent space embedding, sparse PCA and high dimensional nonparametric techniques. We aim to develop cutting edge statistical tools based on the latest ideas in statistics and machine learning, remembering that the most satisfying aspect of statistics, occurs when methods we develop are applied to answer important scientific questions.