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.
I am currently examining how rational process models (approaches that approximate rational inference) shed insight on learning behavior that may sometimes appear "non-optimal", such as whether children evaluate a sampled subset of possible hypotheses during causal learning and induction.
Scientific American: The educational value of creative disobedience. (July, 2011)
I received my PhD from the Massachusetts Institute of Technology Department of Brain and Cognitive Sciences in April of 2009; working in the Lab of Laura Schulz, I studied causal learning and conceptual change in children.
I am now a post-doc at University of California, Berkeley working with Professor Tom Griffiths in the Computational Cognitive Science Lab and collaborating with Professor Alison Gopnik.