Our lab is interested in elucidating how neural circuits compute and building biologically-inspired Artificial Intelligence. To this end, we combine behavioral measurements, invasive neurophysiological recordings in the human brain and computational neuroscience models. The main topics of investigation center around visual recognition, learning, and memory. Within visual recognition, current projects include studying the mechanisms of pattern completion, visual search, context and task dependence, spatiotemporal integration and building machines that can see and interpret the world the way we do. Within learning and memory, current projects include studying real life memories, understanding how medial temporal lobe circuits lead to memory consolidation, and building biologically plausible models for episodic memory formation.