Joshua Tenenbaum

Tenenbaum grew up in California. His mother was a teacher{{Cite web |url=https://www.rdmag.com/article/2018/12/ai-cognitive-science-researcher-josh-tenenbaum-phd-named-r-d-magazine-2018-innovator-year |title=AI, Cognitive Science Researcher Josh Tenenbaum Named R&D Magazine's 2018 Innovator of the Year |last=Panjwani |first=Laura |work=R & D Magazine |quote=Tenenbaum’s scientific work currently focuses on two areas: describing the structure, content and development of people’s common sense theories, especially intuitive physics and intuitive psychology, and understanding how people are able to learn and generalize new concepts, models, theories and tasks from very few examples, a concept known as “one-shot learning.” |date=December 18, 2018 |accessdate=February 10, 2019}} {{Cite web |url=https://ed.stanford.edu/news/alumna-bonnie-tenenbaum-educator-and-philanthropist-remembered-her-generosity-students |title=Eulogy|date=8 December 2020 }} and his father is Internet commerce pioneer Jay Martin Tenenbaum.{{Cite web |url=https://www.technologyreview.com/s/407860/marty-tenenbaum-64-sm-66/ |title=Marty Tenenbaum '64, SM '66 |last=Luttrell |first=Sharon Kahn |work=MIT Technology Review |quote=Meanwhile, his son Josh Tenenbaum, PhD ‘98, has followed his father’s footsteps to MIT. He’s an assistant professor in the Department of Brain and Cognitive Science. |date=May 7, 2007 |accessdate=February 10, 2019}}

His research direction was strongly influenced by his parents' interest in teaching and learning, and later by interactions with cognitive psychologist Roger Shepard, during his years at Yale.

Tenenbaum received his undergraduate degree in physics from Yale University in 1993, and his Ph.D. from MIT in 1999. His work focuses on analyzing probabilistic inference as the engine of human cognition and as a means to develop machine learning. According to the MacArthur Foundation, "Tenenbaum is one of the first to develop and apply probabilistic and statistical modeling to the study of human learning, reasoning, and perception, and to show how these models can explain a fundamental challenge of cognition: how our minds understand so much from so little, so quickly."

At MIT, Tenebaum is a professor of computational cognitive science and a member of CSAIL, MIT’s Computer Science and Artificial Intelligence Laboratory. He leads MIT's Computational Cognitive Science lab and is also head of an AI project called the MIT Quest for Intelligence.{{Cite web |url=https://www.technologyreview.com/s/612002/a-plan-to-advance-ai-by-exploring-the-minds-of-children/ |title=A plan to advance AI by exploring the minds of children |last=Knight |first=Will |work=MIT Technology Review |quote=For instance, in 2015 he and two other researchers created computer programs capable of learning to recognize new handwritten characters, as well as certain objects in images, after seeing just a few examples. This is important because the best machine-learning programs typically require huge quantities of training data. |date=September 12, 2018 |accessdate=February 10, 2019}}

In 2018, R & D Magazine named Tenenbaum their "Innovator of the Year."

In 2019, Tenenbaum was named a MacArthur Fellow. The MacArthur webpage describes his work as follows: "Combining computational models with behavioral experiments to shed light on human learning, reasoning, and perception, and exploring how to bring artificial intelligence closer to the capabilities of human thinking."{{Cite web|url=https://www.macfound.org/fellows/1050/|title=Joshua Tenenbaum - MacArthur Foundation|website=www.macfound.org|access-date=2019-10-16}}

Tenenbaum's recent research includes teaching AI systems to imitate human face-recognition methods{{Cite news |url=https://news.mit.edu/2020/computer-model-brain-vision-0304 |title=A new model of vision |last=Trafton |first=Anne |work=MIT News |quote='What we were trying to do in this work is to explain how perception can be so much richer than just attaching semantic labels on parts of an image, and to explore the question of how do we see all of the physical world,' says Josh Tenenbaum, a professor of computational cognitive science and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Center for Brains, Minds, and Machines (CBMM). |date=March 4, 2020 |access-date=March 20, 2021}} and programming AI to understand cause and effect.{{Cite magazine |url=https://www.wired.com/story/ai-smart-cant-grasp-cause-effect/ |title=If AI's So Smart, Why Can't It Grasp Cause and Effect? |last=Knight |first=Will |magazine=Wired |quote=The test devised by Tenenbaum is important, says Kun Zhang, an assistant professor who works on causal inference and machine learning at Carnegie Mellon University, because it provides a good way to measure causal understanding, albeit in a very limited setting. |date=March 9, 2020 |access-date=March 20, 2021}}

Tenenbaum has a list of his publications on his [http://web.mit.edu/cocosci/josh.html MIT web page] and on [https://scholar.google.com/citations?hl=en&user=rRJ9wTJMUB8C&view_op=list_works&sortby=pubdate Google Scholar].

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Category:Living people

Category:Yale University alumni

Category:Massachusetts Institute of Technology School of Science faculty

Category:Fellows of the Cognitive Science Society

Category:Massachusetts Institute of Technology School of Science alumni

Category:Fellows of the Society of Experimental Psychologists

Category:American artificial intelligence researchers

Category:MIT Computer Science and Artificial Intelligence Laboratory people

Category:1972 births