Laura Schulz - Primary Investigator
The infrastructure of human cognition -- our commonsense understanding of the physical and social world -- is constructed during early childhood. I study the representations and learning mechanisms that underlie this feat. My research looks at 1) how children infer the concepts and causal relations that enable them to engage in accurate prediction, explanation, and intervention; 2) the factors that support curiosity and exploration, allowing children to engage in effective discovery and 3) how these abilities inform and interact with social cognition to support intuitive theories of the self and others.

Computational models of human cognition inform much of the research in the lab. I have been especially interested in understanding trade-offs in the inferential process, such that the same inductive biases that constrain the hypothesis space and allow us to draw rich inferences from sparse data can also make it difficult for us to revise our beliefs. This paradox poses a challenge for educators but also provides insight into the factors that might promote effective learning and teaching.

Most of the research in the lab involves babies and children. Since babies and children have limited prior knowledge and no formal training, understanding how children reason about the world can give us insight into the origins of knowledge and fundamental principles of learning. We have on-site laboratories that constitute the PlayLab at the Boston Children's Museum, where we use a variety of approaches, ranging from infant-looking time methods to free-play paradigms in our studies.

Curriculum Vitae (updated November, 2017)



Postdoctoral Researchers


Melissa Kline - Postdoctoral Researcher
How does language help us break our understanding of the dynamic world around us into just the right pieces for communication? How do babies and children build the system of structured and abstract representations that make up sentence-level meaning? I study the intersections between cognitive development and language acquisition, in particular how pre- or non-linguistic concepts like causation, agency and physical space get mapped into language. I am interested in how children (and adults) use syntactic structures to make inferences about what sentences mean, and to choose the right things to say to get their own meanings across.

Tobias Gerstenberg - Postdoctoral Researcher
I am interested in causality, counterfactuals, and responsibility. In my work, I investigate the ways in which these different concepts are linked. For example, when judging whether one event caused another event to happen, people often compare what actually happened with what they think would have happened in the absence of the causal event. People make use of their intuitive understanding of a given domain, such as physics or psychology, to simulate what would have happened in the relevant counterfactual world. I try to understand how the ability to simulate counterfactual situations develops and how it helps us to make sense of events in the world, and the actions of other people.



Graduate Students



Julia Leonard - Graduate Student

What determines whether a child flourishes cognitively and emotionally? How does this depend on environmental factors, such as stress and socioeconomic status? Most importantly, can we use the lessons learned from the study of positive development to create interventions that foster resilience in children from all backgrounds? These questions drive my interest in child development and I'm currently exploring them, employing both behavioral and neuroimaging methods, in collaboration with Laura Schulz and John Gabrieli.


Rachel Magid - Graduate Student

My research focuses on how children deploy their rational learning abilities to problems of reasoning about the self. Gaining new skills and achieving new goals through self-directed actions requires not only representing aspects of a given task, but also aspects oneself. I'm investigating the ways in which metacognition impacts children's exploration, motivation, and decisions about how to collaborate. My current projects in the Schulz Lab are collaborations with several others: Mary DePascale, Julia Leonard, Kary Richardson, and Max Siegel, as well as Josh Tenenbaum.


Hilary Richardson - Graduate Student

I am a graduate student in Rebecca Saxe's lab earning my PhD in cognitive neuroscience. I am most fascinated by questions about brain development: how does our brain change as we get older, and what kinds of neural changes support or predict cognitive feats such as successfully reasoning about the minds of other people? To ask these questions, I ask "MIT Junior Brain Scientists" (i.e., kids!) to visit the lab, have their brain pictures taken, and play special picture-book and word games.


Junyi Chu - Graduate Student

An important precursor to successful learning and discovery is the generation of ideas. Given limited resources (e.g. prior knowledge, tools) and uncertain costs (e.g. time), being able to identify "good" ideas prior to exploration can help direct our efforts towards a more constrained space of possibilities, thus making learning and discovery more effective. My research takes a developmental and computational perspective to study the mechanisms and constraints underlying idea generation, in the service of learning and problem solving.


Max Siegel - Graduate Student

I would like to understand how people, even young children, can recognize familiar things in unfamiliar situations, like meeting someone in the day and recognizing them at night. I think that this ability is an active one - we "know what to look for" to identify an object, just by being told the context in which we'll meet it. In the lab, we've investigated these questions by studying children's ability to imagine the sound that an object would make if it was shaken in a box, and we also attempt to use computational models to clarify and understand these issues.


Pedro Tsividis - Graduate Student

Children are incredibly capable learners - they form rich, structured representations of the world with exposure to far sparser data than what state-of-the-art computational models require for similar performance. I believe that a key component of children's ability to learn so well and so quickly is their sensitivity to statistical distributions in the world, and in particular, their use of this information to guide decisions about what events and objects to pay attention to. I am currently investigating the ways in which children are optimal learners in this respect. I am also interested in concept acquisition and representation, and in moral reasoning.


Yang Wu - Graduate Student

Emotion understanding is crucial for human beings. It could not only advance our knowledge about the world, but also assist our social interactions and communications. For example, if a child frowns at a plate of broccoli, we infer that the child does not like it; if a lady screams when she looks towards a corner, we infer that she sees something unpleasant, such as a spider. What are the representations in our minds that make these inferences so rich and efficient? In my research I look at how people's understanding of emotions is structurally and causally intertwined with other factors such as beliefs, desires, and actions that could support reasoning from one to another within this structure. I combine behavioral experiments with computational models to capture this representational structure in human adults and how it develops over infancy and childhood.


Maddie Pelz - Graduate Student

Children learn an incredible amount about the world by exploring the environment, testing hypotheses, asking questions of others, and cooperating with peers. Despite its centrality to our lives as both children and adults, learning can also sometimes feel impossible. I am interested in understanding how certain behaviors can be encouraged and/or modified in order to improve learning outcomes. I hope to understand what drives different aspects of learning using a combination of behavioral studies and computational modeling.




Lab Staff



Kary Richardson - Lab Manager and Technical Associate


Kim Scott - Research Scientist

I run the online branch of our lab, Lookit (, where families can participate in developmental studies from home. I'm especially interested in broadening access to developmental research for both participants and researchers, making it easier to collect larger datasets to do more robust and reproducible research, and improving our understanding of developmental methods using longitudinal sampling.




Lab Alumni


Julian Jara-Ettinger - Assistant Professor at Yale University

I study the fundamental representations and computations that underlie our ability to navigate the social and physical world. My work spans across ages, cultures, and clinical populations, but my primary focus is on early childhood. My research combines behavioral studies with mathematical models and computer simulations to develop and test cognitive theories. To date, much of my work specifically looks at how we represent and reason about other people's minds and on how we infer what they know, think, and want.

Paul Muentener - Assistant Professor at Tufts University

My research explores the development of causal reasoning in infancy and early childhood. What is the range of events that we are able to reason about causally early in development? What kind of information enters into these causal representations? I am particularly interested in the role that representations of intentional agency play in causal reasoning. In my infant studies, I employ looking time measures and action-based tasks to explore our earliest causal reasoning skills. I also study children’s descriptions of causal events to investigate the relationship between children’s conceptual and linguistic representations of causality across development.


Hyowon Gweon - Asistant Professor at Stanford University

Humans possess a powerful learning mechanism which allows them to make sophisticated inferences from very sparse data. This mechanism not only allows us to learn so much from so little but also to learn from many different sources of information. The data can sometimes be generated by the learner, by a naturally occurring events, from another person’s unintentional actions, and sometimes by someone who has the explicit intent to teach. And in each of these contexts, the learner makes different assumptions and inferences. How can we formally characterize the differences between these contexts, and how do they affect what is learned? How do learners make use of others’ knowledge in order to learn about what they have no direct access to? What is the role of Theory of Mind in social learning, and what neural mechanisms underlie our ability to learn from others?

Elizabeth Bonawitz - Assistant Professor at Rutgers University

Elizabeth is an Assistant Professor of Psychology at Rutgers University - Newark. Her research bridges two research traditions: Cognitive Development and Computational Modeling. By bridging these methods, she hopes to understand the structure of children's early causal beliefs, how evidence and prior beliefs interact to affect children's learning, the developmental processes that influence children's belief revision, and the role of social factors (such as learning from others) in guiding learning.


Andrew Shtulman - Associate Professor at Occidental College

Andrew Shtulman is an Associate Professor in the Departments of Psychology and Cognitive Science at Occidental College. He holds an A.B. in Psychology from Princeton University and a Ph.D. in Psychology from Harvard University. His research explores conceptual development and conceptual change, particularly as they relate to science education, and his work has appeared in cognitive journals (Cognition, Cognitive Psychology), developmental journals (Child Development, Cognitive Development), and education journals (Educational Psychologist, Journal of Educational Psychology). Currently, Dr. Shtulman is pursuing research on the "\Causes and Consequences of Conceptual Change" funded by an Early Career Development Award from the NSF.



Undergraduate Research Assistants


Fatima Gunter-Rahman

I am a freshman at MIT, interested in brain and cognitive sciences. I'm thrilled to be working with Julia and Rachel on a project studying metacognition in four and five-year-olds. I'm looking forward to working with children and learning more about how they process their own learning.