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Japanese scholar (born 1936) From Wikipedia, the free encyclopedia
Shun'ichi Amari (甘利 俊一, Amari Shun'ichi), is a Japanese engineer and neuroscientist born in 1936 in Tokyo, Japan.
Shun'ichi Amari | |
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甘利 俊一 | |
![]() Shun'ichi Amari | |
Born | 1936 (age 87–88) |
Nationality | Japanese |
Alma mater | University of Tokyo |
Known for | Information Geometry Amari distance |
Awards | IEEE Emanuel R. Piore Award (1997) |
He majored in Mathematical Engineering in 1958 from the University of Tokyo then graduated in 1963 from the Graduate School of the University of Tokyo.
His Master of Engineering in 1960 was entitled Topological and Information-Theoretical Foundation of Diakoptics and Codiakoptics. His Doctor of Engineering in 1963 was entitled Diakoptics of Information Spaces.
Shun'ichi Amari received several awards and is a visiting professor of prestigious universities.
He is the author of more than 200 peer-reviewed articles[1] and is best known for inventing a way for the recurrent neural network to learn based on the Ising model from quantum physics, which is now imprecisely known as Hopfield network.
He is currently holding a position of the prestigious RIKEN lab and is vice-president of Brain Science Institute, director of Brain Style Information Systems Group and team leader of Mathematical Neuroscience Laboratory.[2]
He was a winner of the IEEE Emanuel R. Piore Award (1997)[3]
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