About

I am a postdoctoral researcher at the Princeton Neuroscience Institute, working with Nathaniel Daw. Previously, I completed my Ph.D. under Dani Bassett at University of Pennsylvania. My research focuses on how we plan in complex environments.

From city navigation to jazz improvisation to life choices, our actions unfold over temporally extended timeframes, necessitating the ability to predict the possible long-term outcomes associated with our choices. Temporal abstraction provides a mechanism for heuristically guided planning, allowing actions to reflect knowledge about the value of outcomes separately from how to achieve those outcomes.

My research addresses these typics by by examining (1) how we learn predictive models, as well as (2) how and when we rely on those models to plan and make decisions. In one arm of my research, I seek to characterize the processes that allow people to learn predictive models from simple observations. In a second arm, I study how people and animals dynamically adapt their decision making betwe cheap predictive models and costly mental simulation.

My research utilizes advances in network science, control theory, and reinforcement learning, behavior in humans and animals, and human neuroimaging to study how the brain supports complex planning and decision making over temporally-extended sequences of events.