I am a fellow at Insight Data Science, focusing on bringing the computational and communication skills I learned in science to solve problems in industry, in particular in health care.
I leverage machine learning, “big data” analytics, and data visualization to tackle persistent problem in medical care.
In my research, I studied the cognitive and neural bases of high level representation, using social cognition as a case study of abstract, yet structured, reasoning. With behavioral and functional neuroimaging (fMRI) techniques, my research focused on:
(i) The neural coding and implementation of social cognition: What is the feature space or compositional structure to mental state representation? What is the relationship between the neural organization and the cognitive architecture?
(ii) The developmental origins of, and constraints on, social cognition: What is required to successfully reason about another person’s internal states? To what extent does limited first person experience change the developmental course of mental state inference?
To answer these questions, I worked with children, blind adults, deaf adults, and adults with autism, as well as typical adults.