My lab works on problems at the intersection of neuroscience, statistics, and machine learning. We develop statistical methods for characterizing structure in high dimensional data, and collaborate very closely with experimental groups to study neural systems and the computations they perform. We are also interested in the brain's ability to perform statistical inference in naturalistic tasks, and in the theoretical principles governing the function and design of sensory systems. Current research topics include sensory-motor decision making, working memory, latent variable models, dimensionality reduction, scalable methods for large-scale datasets, regression models for electrophysiology and calcium imaging data, and quantitative methods for behavior.