Judea Pearl
✓ Source-basedfallingIsraeli-American computer scientist (born 1936)
Judea Pearl is an Israeli-American electrical engineer, computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks.
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The research questions that motivate most quantitative studies in the health, social and behavioral sciences are not statistical but causal in nature.
Pearl, Judea (2008) "Causal Inference," in: Pearl, Judea. The science and ethics of causal modeling. (2010).
Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample.
Pearl, Judea. "Causal inference in statistics: An overview." Statistics Surveys 3 (2009): 96-146.
Haavelmo was the first to recognize the capacity of economic models to guide policies.
Judea Pearl, "Trygve Haavelmo and the emergence of causal calculus." University of California Los Angeles, Computer Science Department, CA.
Awards 17
In their orbit 2
Connected to Judea 6
Geoffrey HintonAlso won Rumelhart Prize
Raymond KurzweilAlso won Dickson Prize in Science
Steven PinkerAlso won Fellow of the Cognitive Science Society
Herbert A. SimonAlso won AAAI Fellow
Kenneth ArrowAlso won Kampé de Fériet Award
William Lyon Mackenzie KingAlso won Honorary doctorate from University of TorontoAbout this person
Judea Pearl is an Israeli-American electrical engineer, computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks. He is also credited for developing a theory of causal and counterfactual inference based on structural models. In 2011, the Association for Computing Machinery (ACM) awarded Pearl with the Turing Award, the highest distinction in computer science, "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning". He is the author of several books, including the technical Causality: Models, Reasoning and Inference, and The Book of Why, a book on causality aimed at the general public.
Text from Wikipedia, CC BY-SA 4.0
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