I build computational models of everyday cognitive abilities, focusing on problems that are easier for people than they are for machines. The human mind is the best known solution to a diverse array of difficult computational problems: learning new concepts, learning new tasks, understanding scenes, learning language, asking questions, forming explanations, amongst many others. Machines also struggle to simulate other facets of human intelligence, including creativity, curiosity, self-assessment, and commonsense reasoning.

In this broad space of computational challenges, my work has addressed a range of questions: How do people learn a new concept from just one or a few examples? How do people act creatively when designing new concepts? How do people learn qualitatively different forms of structure? How do people ask questions when searching for information?