I am a cognitive scientist studying how we learn from interaction with the environment, and how learning can lead to changes in mental health.
My research combines computational approaches (e.g. reinforcement learning, Bayesian inference) with behavioral experiments, eye-tracking and neuroimaging. A current focus is on developing methods to study goal-directed learning in virtual reality.
Here is an overview of past and ongoing work.
Moore-Sloan Faculty Fellow, Center for Data Science (CDS)
Collaborator, Computation and Cognition Lab & CCN group
New York University
I received my Ph.D. in Psychology and Neuroscience from Princeton University, where I did research in Yael Niv's group.
It's easiest to reach me via e-mail. You can also find me on Google Scholar, GitHub and Twitter.
May 2021. In Sept '22, I will be starting as an Assistant Professor at Mt. Sinai's Center for Computational Psychiatry in New York. If you are a prospective graduate student interested in working together, Mt. Sinai offers two tracks: a PhD in Neuroscience, and an MD/PhD. Other openings coming soon!
March 2021. New blog post on a narrative-based approach to computational psychiatry research
September 2020. First day at CDS!
May 2020. Defended!
April 2020. Our paper, From Heuristic to Optimal Models in Naturalistic Visual Search, was live at the Bridging AI and Cognitive Science ICLR workshop.