My research interests center on the memory, learning, and decision processes which allow us to carry out intelligent and adaptive behaviors. I am particularly interested in how people uncover important and useful regularities about the environment through experience. For example, how do we all come to agree on a similar idea of the concept "mammal"? How do our learning experiences shape our perception of the world around us? How do we acquire new skills and behaviors? The goal of my research is to enrich our understanding of the mechanisms which support these diverse behaviors, how they might develop and change over the course of our lives, and how they might be impacted by disease or brain damage.
Central to my work is the use of computational models as a tool for integrating and directing research. Computational models are psychological theories which have been specified in enough detail to be run as computer programs. Computational modeling provides a powerful scientific framework for evaluating theories of cognitive function. For example, models can help organize diverse sets of findings which might seem otherwise unrelated, and predictions derived from competing models can be used to guide empirical research. In addition, insights from cognitive models can inform the development of artificial systems capable of learning on their own.
For more information about the research conducted in my lab please see my lab webpage.
I received a B.S. in Computer/Electrical Engineering (2001) from the University of Texas at Austin and a M.A. and Ph.D. (2005) in psychology from UT Austin under Brad Love. After completing my Ph.D., I was employed as a postdoctoral research associate in the Psychological and Brain Sciences Department at Indiana University. I started as a faculty member in the NYU psychology program Jan. 2008.
Please see my lab webpage for a full list of publications