I'm a sixth-year PhD student at the Princeton Neuroscience Institute, where I am jointly advised by Nathaniel Daw and Ilana Witten. My primary thesis research is concerned with how the brain can use experience replay to build cognitive maps that are robust to changes in behavioural incentives. In a more general sense, I am interested in neuroeconomics (how the values of choices and stimuli are learned, represented, and transformed into decisions in the brain) and structure learning (how agents may develop models of their world or the task they are executing in order to facilitate learning or planning) -- and how they can be applied to the design of artificial agents.

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I received a B.S.E. with high honors in Computer Science from Princeton University, during which I developed formal computational models characterizing optimal multitasking behaviour in Bayesian agents with Jonathan Cohen. A subset of this work was awarded the Computational Modeling Prize in Higher Level Cognition at the Annual Meeting of the Cognitive Science Society.

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You can find my CV here and my GitHub here.

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