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Joshua Tenenbaum is Professor of Cognitive Science and Computation at the MIT. He and his colleagues in the Computational Cognitive Science group want to understand that most elusive aspect of human intelligence: our ability to learn so much about the world, so rapidly and flexibly.

While their core interests are in human learning and reasoning, they also work actively in machine learning and artificial intelligence. These two programs are inseparable: bringing machine-learning algorithms closer to the capacities of human learning should lead to more powerful AI systems as well as more powerful theoretical paradigms for understanding human cognition.

Their current research explores the computational basis of many aspects of human cognition: learning concepts, judging similarity, inferring causal connections, forming perceptual representations, learning word meanings and syntactic principles in natural language, noticing coincidences and predicting the future, inferring the mental states of other people, and constructing intuitive theories of core domains, such as intuitive physics, psychology, biology, or social structure.

He is known for contributions to mathematical psychology and Bayesian cognitive science. Tenenbaum previously taught at Stanford University, where he was the Wasow Visiting Fellow from October 2010-January 2011.