Team

Julian Jara-Ettinger

Principal Investigator. CV (updated 12/2023).

Rui Zhang

Lab Manager.

Urvi Suwal

Postbac Research Associate.

Ben Morris. Everyday conversation is a ubiquitous testbed of mental-state reasoning. Broadly, I am interested in how children rely on and exploit mental reasoning in conversational contexts. To become smooth conversationalists, young children must learn to extract mental information from language to learn about people, and also recruit mental reasoning to learn language. In much of my work, I explore how children infer mental states not from what someone says, but from how (and especially how quickly) they say it.

Mika Asaba. Who am I? Who do you think I am? As humans, we are highly motivated to learn about the self and to learn about what others think of us. These processes are especially important to study in young children who are developing their initial beliefs about the self. My research uses developmental and computational methods to investigate how children build a self through their social interactions with others.

Isaac Davis. Humans are remarkably good at reasoning and forming beliefs about things that we cannot directly observe. In physical systems, we infer the existence of hidden causes driving observable phenomena. In social systems, we infer richly structured mental states from other agents’ observable behavior. In my research, I seek to understand how we learn and reason about things we can’t observe, how our causal cognition and learning interacts with our social cognition and theory of mind, and the theoretical limits of what we can learn about hidden things.

Daniel Horschler. As humans, our ability to represent others' mental states allows us to make sense of others’ actions and predict what others might do next. But how did our 'theory of mind' evolve, and to what extent is it shared with other species? To address these questions, my work in the Computational Social Cognition Lab involves building and evaluating computational models of non-human primate theory of mind. By blending computational approaches with comparative field experiments, I aim to advance our fundamental understanding of the cognitive mechanisms that guide social behavior.

Aaron Baker. The social world is a profoundly complex space that we seem to navigate with relative ease. Every day, we interact with individuals and groups in a variety of ways, and often times with complete strangers. I'm concerned with the representations we use that can be flexibly applied across many situations to solve social problems. For example, how do social roles guide or modulate our representations of an agent's behavior? I leverage developmental and computational perspectives to find answers to these questions.

John Muchovej. Our most behaviorally successful computational models of mind often have diverging representations from those that humans intuitively have. Further, these models tends to scale poorly to more realistic domains. My work aims to endow computational models with human-like representations and explores how we can scale these algorithms to more realistic and multi-agent domains. My research primarily uses behavioral and computational methods.

Marlene Berke. Typically, the information available to an observer is quite impoverished. In the domain of perception, people must infer the latent causes of what they sense from surprisingly poor data. In social cognition, people must make inferences about other minds from observing behavior. I study the role of generative models and simulation in these inference processes. I’m especially interested in mental imagery, and how it fits into this framework. My research uses behavioral and computation methods to address these questions.

Amanda Royka. In the broadest terms, I am interested in theory of mind. More specifically, I study how we use our ability to infer others’ mental states and predict others’ actions in order to make our own behavior more understandable to those around us. Most obviously, this occurs in the context of communicative interactions in which you are trying to make both your communicative goal and specific message apparent to your intended recipient. However, I’m also interested in the ways in which we broadcast our mental states outside of explicitly communicative moments as well. I use behavioral, comparative, cross-cultural, and computational approaches to gain a fuller picture of this incredible capacity to flexibly reveal our own mental states.
Personal Website

Xiuyuan Flora Zhang. I am particularly interested in how people think about their ability to acquire new objects (through ownership) and new skills (through learning), and how these interact with each other (e.g., how ownership could promote learning). Drawing inspirations from cognitive science, social psychology, and philosophy, I use a combination of behavioral experiments and computational modeling to pursue these questions in adults and children.
Personal Website

Zihan Wang. With a short period of observation of social interactions, we appear to discern the potential relationships or dynamics between the people involved. What cues do we look for or rely on when making such social inferences? How do we extract relevant details from a rich social context? How can we instill such inductive biases into models so they can reason, infer, and predict in a human-like manner? Which social rules, norms, or structures are easier or harder to learn? What empowers social learning and communication? I aim to explore the uniqueness of social intelligence through both developmental and computational modeling.

Sophie Lau.

Julia Miller.

Ben Sterling.

Emma Carollo.

Misho Gabashvili.

Olivia White Storti.

Tan Zhi Yi.

Michael Lopez-Brau Graduate Student -> Industry.

Mackenzie Briscoe Lab Manager -> Graduate student, Psychology, Harvard University.

Marieke Woensdregt Postdoc -> Postdoc, Max Planck Institute.

Rosie Aboody Graduate student -> Postdoc, Harvard University.

Colin Jacobs Lab manager -> Graduate student, Psychology, UC Berkeley.

Madison Flowers Lab manager -> Law student, Georgetown University.

Undergraduate researchers

Jenna Landy -> Graduate student, Psychology, NYU.

Zhangir Azerbayev -> Graduate student, Computer Science, Princeton.

Annya Dahmani -> Graduate student, Psychology, UC Berkeley.

Tanushree Burman -> Graduate student, Computer Science, Tufts.

Caiqin Zhou -> Graduate student, Psychology, Brown University.

Sam Fereidooni -> Graduate student, Computer Science, Columbia University.

Joseph Kwon -> researcher at BCS, MIT.

Lukas Burger -> Head of Engineering at Probably Genetic.

Annie Chen -> Chan Zuckerberg Initiative.

Maria Maier -> Law student, BU.

Ethan Weinberger -> Graduate student, Computer science, UW.

Breanna McBean -> Graduate student, Bioengineering, University of Michigan.

Holly Huey -> Graduate student, Psychology, UCSD.