Josh Tenenbaum is Professor of Computational Cognitive Science at the Massachusetts Institute of Technology in the Department of Brain and Cognitive Sciences, the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Center for Brains, Minds and Machines (CBMM). His long-term goal is to reverse-engineer intelligence in the human mind and brain, and use these insights to engineer more human-like machine intelligence. In cognitive science, he is best known for theories of cognition as Bayesian inference, with a focus on explaining how humans can learn so much so quickly, from so little data. In AI, he has developed influential approaches to dimensionality reduction, unsupervised learning and structure discovery, and probabilistic programming. His current research focuses on probabilistic program models of common sense in humans and machines, grounding language and perception in these representations, and learning based on program synthesis. His papers have been recognized with more than fifteen awards at major conferences in Cognitive Science and AI, and he is the recipient of the Troland Award from the National Academy of Sciences, the Warren Medal from the Society of Experimental Psychologists, a MacArthur Fellowship, the Fyssen Foundation International Prize, and membership in the American Academy of Arts and Sciences.
Josh Tenenbaum 2023 Senior Fellow