Rate My Professor Ari Kahn

Ari Kahn serves as Assistant Professor in Cognition & Neural Systems within the Department of Psychology and as Assistant Professor in the Cognitive Science Program at The University of Arizona, a position he began in 2026. He previously held a Postdoctoral Research Associate appointment at the Princeton Neuroscience Institute from 2020 to 2025. Kahn obtained his Ph.D. in Neuroscience from the University of Pennsylvania in 2020, advised by Danielle S. Bassett on behavioral and neural correlates of graph learning. He earned a B.S. in Computer Science and Chinese, with a minor in Physics, from Washington University in St. Louis in 2011, graduating cum laude with engineering honors. Earlier, he served as a Research Assistant at Tel Aviv University in 2012, focusing on computational modeling of the cerebellar microcircuit for sequential learning.

Kahn's research examines planning and decision making, investigating how complex behaviors in humans and animals arise from learning and using predictive models of the world. He studies the neural mechanisms of these models, their developmental paths, and their roles in adaptive behavior, employing computational methods including reinforcement learning and network science. Key areas include graph learning, neural representations, successor representations, visuomotor learning, and hierarchical graphs. His publications feature "Network Structure Influences the Strength of Learned Neural Representations" (Nature Communications, 2025, co-authored with Szymula et al.), "Humans Rationally Balance Mental Simulation and Temporally Abstract World Models" (Communications Psychology, 2025), "Trial-by-Trial Learning of Successor Representations in Human Behavior" (PLoS Computational Biology, 2025), "Network Constraints on Learnability of Probabilistic Motor Sequences" (Nature Human Behaviour, 2018), and "Structural Pathways Supporting Swift Acquisition of New Visuomotor Skills" (Cerebral Cortex, 2017). Influential earlier works include "Controllability of Structural Brain Networks" (2015, over 1,000 citations). Awards include the Sackler Colloquium “Brain Produces Mind by Modeling” Travel Award (2019), SIAM Student Travel Award (2018), and Jameson-Hurvich Travel Award (2016). He teaches PSY 333: Judgment & Decision-Making.