Principal Investigator
Alison Gopnik, PhD
Alison Gopnik, Ph.D. then and now
My research explores how young children come to know about the world around them. The work is informed by the "theory theory" -- the idea that children develop and change intuitive theories of the world in much the way that scientists do. Most recently, we have been concentrating on young children's causal knowledge and causal learning across domains, including physical, biological and psychological knowledge. In collaboration with computer scientists, we are using the Bayes Net formalism to help explain how children are able to learn causal structure from patterns of data, and we have demonstrated that young children have much more powerful causal learning mechanisms than was previously supposed.
email | website
Lab Manager
Maansi Narain
Maansi Narain, then and now
Hi! I’m the lab manager for Dr. Alison Gopnik’s lab. In 2024, I earned my B.S. in Developmental Psychology from UC San Diego, where I was part of several labs studying cognitive development and language. I am currently interested in studying how children explore the world around them, how they understand time, how they acquire language, and the role of imagination in childhood development. I hope to study some of these topics further in graduate school. For now, I’m excited to work with and learn from the incredible members of the Gopnik Lab.
email | linkedin
Visiting Scholar
Daphna Buchsbaum
Daphna Buchsbaum, Ph.D. then and now
My research investigates the complex and varied ways in which intelligent learners, such as human children and non-human animals (especially dogs), generate beliefs about the social and causal structure of the world. Recently, my research has moved in the direction of studying children's conceptual development and belief change. I am also interested in studying dog-human interaction as a model for understanding social cognition and communication, as well as as a model for robot-human interaction. In addition to traditional experiments, I apply computational models throughout my research.
I am excited to be a visiting scholar in the Gopnik Lab, where I also completed my PhD. I am visiting from Brown University, where I am a faculty member, and the PI of the Computational Cognitive Development and Brown Dog labs.
Post Doctoral Researchers
Joshua Rule, PhD
Dr. Josh Rule, then and now
My research uses behavioral experiments and computational methods to study how people develop conceptual systems and leverage them to accomplish their goals. My work revolves around an idea called the child as hacker—that symbolic programs provide the most compelling account of sophisticated mental representations and that learning is analogous to a particular style of programming called hacking. I want to understand how human programmers write code–the goals, activities, and tools they use to make code better–and apply these insights to better describe learning in children and adults.
email | website
Laura Lewis, PhD
Dr. Laura Lewis, then and now
I am fascinated by the evolution of great ape social cognition. Specifically, my research explores how humans and our closest living phylogenetic relatives, chimpanzees and bonobos, have evolved to recognize, remember, and represent one another. I use eye-tracking technology and other non-invasive methods with chimpanzees and bonobos living in zoos and sanctuaries around the world to explore how they attend to and process their social worlds. I graduated from Duke University in 2016 with a Bachelor of Science, and earned my PhD from Harvard University in the department of Human Evolutionary Biology in Spring 2022. I was awarded the UC President’s Postdoctoral Fellowship to pursue postdoctoral research here at UC Berkeley with Profs. Alison Gopnik and Jan Engelmann. Besides hanging out with great apes, I love swimming in the ocean, making pottery, and hiking in the Berkeley Hills.
email | website | twitter
Doctoral Students
Eliza Kosoy, 7th Year
Eliza Kosoy, then and now
I'm interested in the intersection of artificial intelligence and child development. How do kids learn new concepts so quickly and with so little data? How can we model this to create faster machine learning. I study this in two different domains. One through intersections with Brenden Lake's work on one-shot-learning and Omniglot. The other through curiosity and exploration with various faculty at BAIR (Berkeley Artificial Intelligence Research). Previously worked on intuitive physics with Josh Tenenbaum, Tomer Ullman and Liz Spelke.
email | website
Eunice Yiu, 5th Year
Eunice Yiu, then and now.
I am interested in studying how children make sense of and explore objects in their everyday lives. Questions I hope to address with my current studies include: What sorts of perceptual priors and biases emerge when children encounter a novel object? On what bases do they categorize objects, as well as how flexible and creative are they in their formulation of categories? How do these compare with the approaches of adults and neural networks take in object reasoning? Finally, what are takeaways from children’s object perception and exploration behaviors that can help us optimize learning in both humans and machines?
email | website
Annya Dahmani, 3rd Year
Annya Dahmani, then and now
My research is at the intersection of cognitive science and artificial intelligence. I am especially interested in how we can build artificial intelligence that draws directly from human cognition, particularly in the areas of learning, exploration, and reasoning. I take inspiration from decades of research showing how humans, specifically children, are able to learn so much about the physical and social world so rapidly and flexibly. Yet, there are certain things that young children can do that are still very far from anything that current state-of-the-art AI can do. During my PhD, I aim to leverage experimental and computational approaches to better understand the connection between learning, decision making, and reasoning.
email | website
Fei Dai, 2nd Year
I’m interested in understanding how children make sense of the world as a flexible learner. Questions I hope to address in my research include: How do children build causal models of the world? How do children effectively generalize prior experiences to novel situations? What cognitive mechanisms shape their exploration and learning? And lastly, how does the learning process of artificial agents diverge from that of children, and what insights can we draw from children's learning strategies to create more human-like artificial intelligence?
Thank you to our undergraduate research assistants!
Divya Sundar
Anais Jimenez
Nitya Sriram
Ray Huang
Charlie Wong
Shivalika Jhabua
Sophia Callandrillo
Miranda Zhang
Maria Rufova
Kaydee Manikhong
Tina Jojan
Deandra Han
Nareh Haroutonian
Janna Umagat
Catherine Cho
Nora Chen
Anisa Majhi
Thank you to our 2022 summer internship cohort!
Thank you to our 2021 summer internship cohort!
Recent Lab Alumni
ROSE REAGAN was the Gopnik Lab Manager for four years, during which she kept the lab running, supervised RAs, and conducted independent research in the realms of social causality, analogical reasoning, and AI capacities. Rose is now a PhD student at the University of California, San Diego working with Gail Heyman and Caren Walker.
DR. NY VASIL was a postdoc in the Gopnik Lab exploring how explanation and causal reasoning contribute to learning, inductive inference, and decision-making, and how this relationship varies with context, domain-specific experience and development. Dr. Vasil now leads the Cognitive Development (CoDe) Lab at California State University East Bay.
DR. DORSA AMIR was a postdoc in the Gopnik Lab investigating how preferences and decision-making vary across diverse cultures, with an emphasis during her time here on caregiving. She is curious about how differing cultural and ecological environments shape the developing mind. Dr. Amir now leads the Mind & Culture Lab at Duke University.
DR. REBECCA ZHU earned her PhD in the Gopnik Lab investigating how children acquire and learn from symbolic systems, such as language and pictures, and then completed a postdoc with Drs. Gopnik and Engelmann studying related questions. Dr. Zhu is now a postdoc at Stanford University working with Dr. Michael Frank.
DR. BENJAMIN PITT was a postdoc working with Drs. Alison Gopnik, Steve Piantadosi, and Ted Gibson (at MIT). Ben’s research investigates how people use the structure of space and language to represent abstract conceptual domains like time, number, and emotion. Dr. Pitt is now a postdoctoral fellow at the Institute for Advanced Study in Toulouse.
DR. MARIEL GODDU earned her PhD in the Gopnik Lab and went on to complete a postdoc studying play behavior in collaboration with Drs. Tomer Ullman and Elizabeth Bonawitz at Harvard University. Mariel is currently an Alexander von Humboldt postdoctoral fellow at the Centre for Advanced Study in the Humanities: "Human Abilities" & the Institut für Philosophie, Freie Universität Berlin. She plans on attending Stanford University for a PhD in Philosophy.
DR. EMILY LIQUIN earned her PhD in 2021 and was co-advised by Alison Gopnik and Tania Lombrozo at Princeton University. Dr. Liquin is currently a postdoc working with Dr. Todd Gureckis at New York University.
EMILY SARAH SUMNER: I was a postdoctoral researcher working with Alison Gopnik and Celeste Kidd. My research investigates how children make decisions and explore the world. Specifically, I am interested in how children's independent exploration can be beneficial to their psychological development. I use a combination of behavioral and computational methodologies to do this. I am a supporter of open science. More information about my research can be found on my personal website, www.emilysarahsumner.com Dr. Sumner is now a researcher at Toyota Research Institute. She continues to collaborate on a line of research investigating exploration and altruism in kids.
KATIE KIMURA: My research interests, broadly defined, are informed by two closely related questions about conceptual development: 1) how do children acquire abstract knowledge, such as complex causal relations, and 2) once children acquire this knowledge how does it interact with their existing beliefs to revise their theories about the world and facilitate the acquisition of new concepts? My work thus far explores abstract knowledge from the perspective of categorical relational learning and word learning (e.g., number word learning and adjectival word learning). Future work, however, will continue to expand upon these questions by examining other kinds of abstract knowledge including causal reasoning. Dr. Kimura received her PhD in 2020.
TERESA GARCIA: Over the last 7 years, I have spend my time working as a preschool teacher, research assistant, psychology student, and lab manager. All of these experiences have taught me a lot about children's learning and development and have motivated me to keep on learning more so that I can one day apply my knowledge to help children, parents, and teachers create environments where we can help our preschoolers be good helpers, teachers, and learners. Teresa Garcia was an undergraduate RA and then served as our Lab Manager. She is now the Lab Manager at Stanford’s Social Learning Lab.
SHAUN O’GRADY: Hi, my name is Shaun, and I am interested in learning more about the development of social cognition. I study how young children reason about other people’s actions, thoughts, and emotions. I would also like to investigate how these reasoning abilities change over time to allow children, adolescents, and adults to navigate increasingly complex social interactions such as communication, pedagogy, and joint action.
ADRIENNE WENTE: My research focused on how children develop an understanding of every day causal events in the world, both social and physical. I was interested in the interaction between innate constraints on conceptual development and cultural learning processes. I was working on a series of studies that compare Berkeley children to children in China. These studies explore the development of causal attributions for social and physical events and the development of beliefs about free will. I also worked on a series of studies exploring the relationship between culture, learning, and early education curriculum in Peru and the U.S.
ELIZABETH BONAWITZ: My research bridges two research traditions: Cognitive Development and Computational Modeling. By bridging these methods, I hope 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. Current webpage here.
Dr. Bonawitz worked as a post-doctoral fellow with Drs. Gopnik and Griffiths, and is now a faculty member at Harvard University.