My research sits at the interface between computational neuroscience and statistical machine learning. We develop statistical tools for making sense of high-dimensional neural datasets and seek to understand how neurons process and transmit information using spike trains. We collaborate closely with experimentalists to study neural encoding and decoding, and the transformation of neural representations between brain areas. We also develop models for the brain's ability to learn, perceive, and make decisions, and seek to uncover the theoretical principles governing the design of sensory systems.