Max Siegel is a postdoc in the Computational Cognitive Science group at MIT. His Ph.D work in the same laboratory was supervised by Josh Tenenbaum as well as Laura Schulz and Josh McDermott.

Max's research concerns recognition (or "identification") of concepts, in particular novel perceptual concepts, and their productive use in cognition. His thesis proposed that people can interpret a class of unfamiliar perceptual stimuli and scenarios -- compositional concepts -- by composing domain theories or "simulators", and gave behavioral and computational evidence for compositional simulation in adult and child perception and cognition.

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Sophie Bridgers is a Simons postdoctoral fellow in the Early Childhood Cognition Lab; she also works with Dr. Tomer Ullman (Harvard Psychology). Though humans are motivated to cooperate, figuring out how best to cooperate is far from trivial. You must understand what another person wants, you must balance what they want with what you want, and you must plan and execute an action that achieves the negotiated, joint goal. The overarching goal of Sophie’s research is to behaviorally, developmentally, and computationally characterize the social-cognitive mechanisms that support human cooperative decision-making in all of its complexity and nuance: when it is successful, when it backfires, and when it is intentionally subverted. Sophie completed her Ph.D. in Psychology at Stanford University, where she worked with Dr. Hyowon Gweon. She also holds a B.A. in Cognitive Science from UC Berkeley.

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Herrissa Lamothe is a postdoctoral fellow with Josh Tenenbaum and Laura Schulz. She previously completed her Ph.D. at Princeton University in Sociology. She is interested in intuitive sociology, that she characterizes in terms of social kinds which include social categories (e.g. race, class, gender); and social meanings which capture our symbolic hypotheses about the ways in which we are socially connected. She is also interested in developing a theory of central cognition that imports insights from the structure of our social concepts; and posits a computational model architecture for how the mind acquires its concepts and categories – including its social ones.

Rosie Aboody is an NSF SBE Postdoctoral Fellow in the Early Childhood Cognition Lab; she also works with Dr. Elizabeth Bonawitz (Harvard Graduate School of Education). She completed her PhD at Yale, working with Julian Jara-Ettinger.

Rosie studies how we come to understand and reason about other people's knowledge and beliefs—an ability that many uniquely-human behaviors rely on, from teaching to moral judgments. Drawing on developmental and computational approaches, Rosie studies how adults infer what others know or believe from their behavior, and how these capacities develop during the preschool years. On the side, Rosie has also been enjoying developing a theoretical account of fake-news beliefs that can explain why children and adults often find widely-repeated claims believable.

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I am the Executive Director of Lookit, a website that lets families participate in cognitive development experiments from home. Lookit hosts experiments for research groups around the world; if you are interested in getting started with the platform please have a look here! Previously, I was a graduate student and postdoc in BCS, and am returning to MIT after a stint at the Center for Open Science where I worked on a large-scale project studying the reliability of claims in social science journals.

I am passionate about improving our scientific practices as social scientists, including promoting replication, data sharing, and large collaborations to improve the reliability of what we learn about the minds of young children. My work combines creating solutions for researchers with empirical research on how our habits and tools as scientists impact the results we report. These interests are a direct result of my own research experiences, and I see attention to our scientific practices as intimately related to the specific theories we study and the data we collect and interpret.

My graduate and postgraduate research focused on how early cognitive development informs how we understand language learning, and how the resulting adult language reflects these early representations. Specifically, I am fascinated by how children learn to use syntactic structures such as the transitive (Jane broke the lamp) and periphrastic causative (Jane made the lamp break). This work finds that early conceptual representations of causation and motion support how young toddlers make inferences about particular events in the world and choose what to say to get their own meanings across. I have also conducted research on how these argument structures shape our linguistic abilities at the cognitive and neural levels.

I’m a software developer on the Lookit team who specializes in creating the software and systems used to run behavioral experiments online. Lookit is a website run by the ECCL that allows families to participate in cognitive developmental experiments from home. My work on the team involves adding new features, testing, debugging, improving documentation, and offering technical support.

Junyi Chu is a postdoc at the Harvard Computation, Cognition, and Development Labs with Tomer Ullman and Elizabeth Bonawitz. She completed her PhD in the ECCL, advised by Laura Schulz.

Junyi’s research explores the nature and developmental origins of creative thought, with recent work focusing on play. She designs behavioral experiments to study how people explore and reason in novel situations, and integrates psychological and computational theories to understand when and why thinking is fun.

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Nicole Coates received her BA in Cognitive Neuroscience from UC Davis and her MS in Psychology and Philosophy from San Jose State University. She is broadly interested in how children learn. More specifically, she is interested in the development of exploration, curiosity, problem-solving, and play. She hopes to integrate findings from learning in early childhood to inform AI.

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Shengyi Wu is a PhD student in the Early Childhood Cognition Lab at MIT. She graduated from University of California, Berkeley in May 2020, where she studied Psychology and Data Science. Prior to joining MIT, Shengyi worked as a project manager in the Computation and Language lab and the Kidd lab at UC Berkeley. Shengyi is broadly interested in using behavioral and computational approaches to study children’s social learning and attention.

Izabelė Jonušaitė is a PhD student at the Early Childhood Cognition Lab (PI: Laura Schulz) and the Computation Cognitive Science group (PI: Josh Tenenbaum). She is interested in combining computational and experimental approaches to study causal reasoning in naturalistic settings and how this capacity develops in children.

Prior to MIT, Izabelė was a Postgraduate Research Fellow at the Computation, Cognition and Development Lab at Harvard University (PI: Tomer Ullman) where she investigated people’s intuitive explanations in the domain of intuitive sociology. She received an MSc in Cognitive Science from the University of Amsterdam (Netherlands), and a BA in Philosophy from the University of York (United Kingdom).

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Jessica Chomik graduated from the Wilkes Honors College of Florida Atlantic University with a Bachelors in Biological and Physical Sciences and a concentration in Cognitive Neuroscience. From 2018 until 2020, Jessica worked in Alex Keene’s Drosophila lab where she examined the effects of toxic beta-amyloid expression on fly sleep. During her time there, she hosted and co-produced a science podcast, “The Research Diaries,” about her undergraduate research experience. Jessica has also worked in a clinical setting at a neuropsychological testing center where she administered cognitive assessments to at-risk patients in the geriatric population to screen for Alzheimer’s Disease and Dementia. Today, Jessica is analyzing causal behavior using fMRI in a joint-lab project under Dr. Laura Schulz and Dr. Nancy Kanwisher as a post-bacc researcher.

Maya Taliaferro is a K. Lisa Yang post-baccalaureate research scholar working concurrently in the ECCL and the language labs at MIT with Dr. Evelina Fedorenko and Dr. Ted Gibson. In 2021 Maya received her BA in Neuroscience from Hamilton College with a minor in Japanese. Her passion for learning the Japanese language is what ultimately inspired her to study language in the mind and brain generally. Her primary interests lie in understanding how multilingual speakers reason about language pragmatically – that is, the ability to understand non-literal aspects of language – and how this ultimately informs differences in communication between one’s native and non-native languages.

Lia Washington is a post-baccalaureate research scholar. She earned her B.A. in Psychology from New York University with minors in Computer Science and Korean language. At New York University she was a research assistant in another experimental developmental lab. Her primary interests lie in multilingualism and language acquisition, specifically, how learned languages and learning languages can affect how individuals understand and navigate the world.

Karla Perez is a post-baccalaureate research scholar. She earned her B.A. in Philosophy and Data Science from Lake Forest College, IL. At Lake Forest, she worked in an experimental philosophy lab on causal reasoning. Currently, her research interests are broad; she is interested in causal reasoning, how people acquire concepts and (use them to) form ideas, and developing cognitive models. At the intersection of philosophy and science, she is interested in the community and puzzle-building/solving aspect of science (à la Khun) and how cognitive scientists develop theories and characterize their findings.

Kiera Parece is a post-baccalaureate Research Assistant working concurrently in the ECCL and the Computational Cognitive Development Lab at Harvard with Dr. Tomer Ullman. Kiera graduated from Wellesley College with a degree in Psychology and Political Science. Prior to joining the ECCL, Kiera worked as a lab manager at Swarthmore College and as a preschool teacher and museum educator. Kiera is broadly interested in children’s social cognition and the role social influences play in children’s learning.

Sienna Radifera received their BA in Psychology from Boston University. There, she grew an interest for computer science and statistics. She is passionate about psychology related research, data science, and growing her programming skills. Working at ECCL MIT as a Lab Manager since summer of 2022.

I am a student at Smith College (‘24, gap year) studying neuroscience and Italian. I hope to pursue an MD/PhD; and, I envision studying pediatrics, child psychiatry, or child neurology in the medical route and either developmental psychology or developmental cognitive neuroscience in the university route. Although I am interested in attachment theory, play, and early adversity right now, I am so excited to hone my interests and continue the process of discovery! Beyond academics, I am a classical violist, and one of my favorite research endeavors is to explore music in different ways (for example, hosting my radio show, Memos From the World at Smith). I am always thrilled to talk about jazz, opera, classical, ethnomusicology, the neuroscience of music, and more! In my free time, I love to bike on the Charles River and on the Cape, attend music performances, and, most especially, travel to Rome.

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Asmita Mittal is an undergraduate student at Cornell University and has been working with the ECCL since high school. She is pursuing a BS in Human Development on a pre-medical track, alongside a Biomedical Engineering minor. Asmita is passionate about research regarding children’s play, persistence, and decision making. She is increasingly fascinated by the origins of children’s early understanding of the world and believes that curiosity should be infinite. As Asmita continues down this exciting path, she is eager to not only learn, but also uncover new aspects of human cognition along the way.