John Hopfield | |
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Born | John Joseph Hopfield July 15, 1933 Chicago, Illinois, U.S. |
Education | Swarthmore College (AB) Cornell University (PhD) |
Known for | Hopfield network Modern Hopfield network Hopfield dielectric Polariton Kinetic proofreading |
Awards |
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Scientific career | |
Fields | Physics Molecular biology Complex systems Neuroscience |
Institutions | Bell Labs Princeton University University of California, Berkeley California Institute of Technology |
Thesis | A quantum-mechanical theory of the contribution of excitons to the complex dielectric constant of crystals (1958) |
Doctoral advisor | Albert Overhauser |
Doctoral students | Steven Girvin Gerald Mahan Bertrand Halperin David J. C. MacKay José Onuchic Terry Sejnowski Erik Winfree Li Zhaoping |
John Joseph Hopfield (born July 15, 1933)[1] is an American physicist and emeritus professor of Princeton University, most widely known for his study of associative neural networks in 1982. He is known for the development of the Hopfield network. Previous to its invention, research in artificial intelligence (AI) was in a decay period or AI winter, Hopfield work revitalized large scale interest in this field.[2][3]
In 2024 Hopfield, along with Geoffrey Hinton, was awarded the Nobel Prize in Physics for their foundational contributions to machine learning, particularly through their work on artificial neural networks.[4][2] He has been awarded various major physics awards for his work in multidisciplinary fields including condensed matter physics, statistical physics and biophysics.