Principal Investigator

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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 curiosity, and the role of social factors (such as learning from others) in guiding learning. We are proud members of the Rutgers Newark Child Research Labs and close partners with the CoDaS (Computational Data Science) Group at RU-N.

Departmental Webpage              CV

Lab Manager

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Zachary Walden

Zach Walden graduated from Franklin & Marshall College in 2016 with a B.A. in Psychology. His interests lie in children’s emotion regulation abilities, reactions to emotionally valenced stimuli, and how early life experiences may precipitate and predict later behaviors.

Project Manager

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Lauren Leotti

Lauren began her psychology research career in a developmental cognitive neuroscience lab at Georgetown University, working with Chandan Vaidya. In 2009, under the mentorship of Tor Wager, Lauren received her Ph.D. in psychology from Columbia University, and then completed a  post-doc with Mauricio Delgado at Rutgers University. After having two children of her own, she has renewed personal interest in developmental psychology. Her research interests relate broadly  to understanding learning, self regulation, and decision making, using behaviorial, psychophysiological and neuroimaging tools. 

Post-doctoral Fellows

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Yue Yu

Yue is a postdoctoral researcher in the Psychology Department of Rutgers University-Newark. Originally from Shanghai, China, he received his PhD in developmental psychology from Cornell University, advised by Prof. Tamar Kushnir. Yue's research focuses on understanding children’s learning in a social environment. Using experimental, observational and computational methods, he explores how children infer from social and contextual cues to guide their learning and exploration, and how these inferences are shaped by everyday experiences. His research in CoCoDev Lab mainly focuses on the effect of "pedagogical questions", a type of questions commonly used by teachers and parents to help children learn. Other work also explore topics of (over-)imitation, causal learning, and category learning.

From September 2018 Yue will start as a research scientist in the National Institute of Education of Singapore, and he will be hiring research assistants (both full-time and part-time). More information can be found on his personal website.Personal Webpage

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Yang Yang

Yang is originally from Beijing, China. She received her Bachelor of Medicine and Bachelor of Science in psychology from Peking University in China, her Master of Education from Harvard University, and her PhD from Cornell University. She is interested in children’s cognitive and emotional development in different cultural contexts. Her graduate work has focused on the developmental patterns, the antecedents, and the consequences of children’s emotional understanding. As a postdoctoral associate in CoCoDev lab, she is interested in using computational tools to investigate children's emotion and learning.

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Koeun Choi

I study cognitive development in the context of media technology. My work uses experimental designs, individual difference measures, eye-tracking methodologies, and statistical techniques to understand the cognitive processes and mechanisms involved in children’s learning and transfer from media. Much of my work focuses on the impact of new technology such as interactive touch screens on children’s exploration and learning in multiple domains (e.g., STEM). I am particularly interested in understanding whether and how digital media would provide benefits in delivering educational content to young learners. Personal Webpage

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Emily Daubert

Emily is a postdoctoral fellow at Rutgers University - Newark in the Computational Cognitive Development Lab in the Psychology Department and also in the Cognitive and Data Science Lab.She received her PhD while working with Dr. Geetha Ramani at the University of Maryland, College Park and her BA in developmental psychology from Temple University. Her research interests center on how children learn through play. Specifically, she is interested in the role of questioning in playful settings for improving STEM learning outcomes and how individual differences, such as socioeconomic and dual-language- learner status influence how children learn through play. CV

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Kimele Persaud

My research interests center on understanding visual working and long-term memory. Specifically, I employ naturalistic and arbitrary stimuli to evaluate the contribution of knowledge and expectations for the statistical regularities of the environment to episodic memory. I also investigate whether differences in expectations, as a function of development, culture, and expertise, differentially influence the reconstruction of events from memory. I use Bayesian and computational methods to characterize this relationship.  Personal Webpage

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Jenny Wang

My research centers around the question: how do basic cognitive structures enable our learning of complex symbolic knowledge, such as language and math? I am broadly interested in the relationship between core cognition and symbolic knowledge, and what kind of beliefs people have about knowledge. I am excited to take a computational approach to characterize the process of conceptual change in young children and adults. Personal Webpage

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Libby Barak

I am a postdoctoral associate in the department of Mathematics and Computer Science at Rutgers University - Newark and collaborating with Dr. Bonawitz. I completed my M.Sc. at Bar-Ilan University working on text classification and earned my Ph.D. from the University of Toronto while working on models of verb acquisition. I then spent two years as a post-doc in the Psychology department at Princeton University working with Adele Goldberg exploring models of language learning.

My research interests are in the areas of cognitive modeling of language and learning. My goal is to create computational models that simulate plausible representations of the learner and the input by accounting for theoretical findings from experimental observations on human behavior. By using this modeling approach, I aim to clarify how learning and linguistic factors interact to facilitate the rapid pace of natural language learning and how learning may vary given individual differences among learners. 

Graduate Students

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Lonnie Bass

Lonnie Bass graduated from Oberlin College in 2014 with a BA and high honors in Psychology. She is broadly interested in how children learn, specifically the factors and cognitive mechanisms that are involved in children’s evaluations of informants in informal pedagogical contexts. As Dr. Bonawitz's doctoral student, Lonnie hopes to utilize computational modeling techniques to investigate how young children distinguish good teachers from bad ones.

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Carla Macias

I am interested in the ways external environment and internal goals influence human decision making in early development. More specifically, I am interested in the empirical study of both implicit and explicit decision-making processes (e.g.,attention in visual exploration and exploration during play) and how these processes influence learning across development.

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Joseph Colantonio

Joseph Colantonio received his BA in Applied Mathematics jointly from Rutgers University – Newark and NJIT in 2016, graduating Summa Cum Laude. He then participated in the PREP program at Rutgers – Newark as a post-Bachelor Research Technician. He is interested in decision making and learning across the lifespan, such as how various factors (i.e. socioeconomic status or emotions) may affect the way children learn through play and exploration. As a Graduate student, Joseph plans to use methods found in computational modeling and machine learning to bridge his research interests in psychology with his background in mathematics.

Post-bac Research Assistants & Masters students

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Milagros Grados

Milagros is a recent graduate from Rutgers-University-Newark. Her research interests are in decision making, feedback expectancy and the effect it has on learning. Moreover, she is interested in abnormal aspects of child development, especially childhood anxiety disorders, and child/adolescent mental health.


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Jack Fredricks

Jack is a recent graduate from Rutgers University – Newark with a major in Psychology. He completed his Honors Thesis in Dr. Bonawitz’s lab in 2016. His interests and current projects concern feedback expectancy and the effect it on has on learning.

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Elizabeth Lapidow

Liz Lapidow graduated from Sarah Lawrence College in 2014, and has been working with Professor Bonawitz since January 2015. She is particularly interested in learning by exploration, and how agents learn and reason about causal relationships.

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Lewis Baker

Lewis received his BS from Loyola University New Orleans and his PhD in Psychology from Vanderbilt University. His research spans developmental, computational and vision science methods to investigate selective attention in social events. One line of inquiry explores joint attention, the ability of adults and children to rapidly attend to where another person can see. Another attempts to predict episodic memories from the structure of events. Lewis is currently working on a new NSF-funded initiative investigating children's learning through discovery, in a collaboration between Elizabeth Bonawitz, Vanessa LoBue and Pat Shafto.

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Katy-Ann Blacker

Katy-Ann is a recently graduated doctoral student. Her research explores how young children acquire causal knowledge about illness transmission and whether this knowledge promotes adaptive behaviors that prevent children from becoming sick or transmitting contagious illnesses to other people.