Professor Linderman's research is focused on machine learning, computational neuroscience, and the general question of how computational and statistical methods can help decipher neural computation. His work aims at developing rich statistical models for analyzing neural data. This endeavor comprises two challenges that are intimately related: developing new statistical methodologies that are well suited to extract information from that data, and applying those methods to experimental data. His work has helped to reveal latent structure underlying neural activity and its relation to sensory inputs and behavioral outputs.