Max Gupta

Psychology ✕ Computer Science

I am a computer scientist interested in the heuristics that human and machine minds acquire to learn new tasks quickly. My work explores how neural network models of the brain can learn to learn the human-like inductive priors that enable us to learn so efficiently in new environments. The primary domains I study to understand this question are conceptual, relational, and geometric reasoning. Currently, I am a second year MSE student at Princeton University, where I work in the CoCoSci lab with Professor Tom Griffiths. Previously, I spent some time in Germany, working on Bayesian pragmatic reasoning at the University of Tübingen and on human-AI psychological experiment design at the Center for Humans and Machines in Berlin. Prior to 3-years in software engineering, I received my Bachelor's in mathematics from Columbia University, where I worked on Bayesian uncertainty quantification at the Azizi Lab.