What we know about the world is much more than the sum of our direct experience with it. We draw rich, abstract inductive inferences that go beyond what we can observe, and what we observe is often mediated by, or even originates from, representations of the world that reside in other people’s minds. The fundamental challenge for theories of human learning is to understand how we combine our own experience with the world and information provided by others in order to learn so much, so quickly, and so accurately, in a complex, noisy environment.

My research tackles this challenge by bringing together developmental, computational, neural, and clinical methods to provide a unified description of the cognitive and neural mechanisms that underlie the representations and inferential processes that allow us to learn about the world, and to communicate what we know.

I have been working with the  Early Childhood Cognition Lab (PI: Laura Schulz) and the Social Cognitive Neuroscience Lab (PI: Rebecca Saxe) first as a graduate student (2007 - 2012) and currently as a post-doctoral associate in the Department of Brain and Cognitive Sciences at MIT.  In addition to working with both labs, many of my projects are done in collaboration with these awesome people:

    - Josh Tenenbaum and the CoCoSci group at MIT,

    - The Kanwisher Lab at MIT (developmental neuroimaging of children with autism) ,

    - Dan Hyde, Liz Spelke, & Susan Carey at Harvard (infant NIRS (Near-Infrared Spectroscopy)

        on goal  understanding),

    - Liz Bonawitz (UC Berkeley) and Pat Shafto (University of Louisville) on pedagogical learning,

    - Noah Goodman at Stanford  (fMRI of causal reasoning in social contexts)