Computational and developmental studies of human social cognition
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. My 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.
Julian Jara-Ettinger has a Bachelor's degree in Physics and Mathematics from Universidad Michoacana in Mexico (2011) and a PhD in Cognitive Science from MIT (2016). He joined Yale University in 2017, where he currently runs the computational social cognition lab. In his free time Julian does modular synthesis.
Nature Communication (2022)
The social basis of referential communication: Speakers construct physical reference based on listeners' expected visual searchPsychological Review (2021)
Current Opinion in Behavioral Sciences (2019)
Trends in Cognitive Science (2016)