Humans have a unique capacity to reason about each other's minds, enabling us to communicate with each other; to share what we know and rely on others to learn what we don't; and to cooperate to achieve what no one can achieve alone. Our lab studies the computational basis of this capacity. Our goal is to understand the representations and computations that underlie our ability to reason about other people's minds, to uncover how this system emerges and develops, and to build machines with human-like social intelligence.

To tackle these problems, our group uses a wide range of methods, including computational modeling, developmental studies, and cross-cultural research. But, at its core, our research is driven by an engineering philosophy: If we really understand how something works, we should be able to build it. We therefore formalize theories as computational models, allowing us to ensure their precision, to understand their scope and limitations, and to generate testable quantitative predictions. Check out our publications to learn more!