Computational and developmental studies of human social cognition
Humans have a unique capacity to reason about each other's minds. This ability enables us to communicate with each other, share what we know, rely on others to learn what we don't, and cooperate to achieve what no one can achieve alone. The Computational Social Cognition Lab studies the computational basis of this capacity. Their 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, the research group uses a wide range of methods, including computational modeling, developmental studies, and cross-cultural research. But, at its core, their research is driven by an engineering philosophy: If we truly understand how something works, then we should be able to build it. Therefore, the lab formalizes theories as computational models to ensure their precision, understand their scope and limitations, and generate testable quantitative predictions.
Methods
Topics
Biography
Julian Jara-Ettinger holds 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. In his free time, Julian enjoys modular synthesis.