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Jonathan Pillow is a Professor at Princeton Neuroscience Institute, where his research focuses on the intersection of neuroscience, statistics, and machine learning. His lab develops statistical methods for characterizing the structure of high-dimensional data and collaborates closely with experimental groups to study the neural systems' computations. He is particularly interested in the brain's ability to perform statistical inference in naturalistic tasks and the theoretical principles that govern the functioning and design of sensory systems. Current research topics include sensory-motor decision making, working memory, latent variable models, and dimensionality reduction. He also explores scalable methods for large-scale datasets and regression models for electrophysiology and calcium imaging data, alongside quantitative methods for behavior analysis.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.