Kate Nussenbaum


I am a computational cognitive (neuro)scientist interested in the development of adaptive, goal-directed behavior.

I focus specifically on how value-guided exploration, learning, and memory processes adapt to the statistical and causal structures of diverse learning environments. The statistics of the environments we experience — including the frequency with which we encounter particular states, the prevalence of reward, and the volatility of action-outcome contingencies — determine how we should explore and learn, and what information we should remember. Across development, how do we flexibly adapt our learning processes to the demands of varied contexts? How do we learn about the structure of the environment and then use that structural knowledge to guide subsequent learning and decision-making? How do we learn to learn over multiple timescales of experience?

To investigate these questions, I couple behavioral experiments with computational modeling and neuroimaging in large, developmental samples.

I am currently a C.V. Starr Fellow at the Princeton Neuroscience Institute, where I work with Nathaniel Daw. I recently received my Ph.D. from New York University, where I worked with Cate Hartley. Before that, I received an MSc by Research from the University of Oxford, under the mentorship of Kia Nobre and Gaia Scerif, and before that, I completed my Sc.B. in cognitive neuroscience at Brown University, where I worked with Dima Amso.


Here is my cv.

I can be reached at katenuss@gmail.com.