Geoffrey Hinton

Geoffrey E. Hinton ( born December 6, 1947 in Wimbledon, United Kingdom) is a British scientist who is best known for his contributions to the theory of artificial neural networks.

Life

Geoffrey Hinton studied from 1967 to 1970 Experimental Psychology at the University of Cambridge (England) and in 1978 received his PhD in Artificial Intelligence from the University of Edinburgh ( Scotland). After living at the University of Sussex (England), the University of California, San Diego ( USA) and the Carnegie - Mellon University (Pittsburgh, USA), 1987 he was Professor at the Computer Science Department of the University of Toronto ( Canada). From 1998 to 2001 under his management, the Gatsby Computational Neuroscience Unit at University College London, since he continues to work as a professor at the University of Toronto. Since March 2013 Hinton works in addition to his work at the University of Toronto at Google.

Services

Geoffrey Hinton examines the application of artificial neural networked in the areas of learning, memory, perception and symbol processing. He was among the researchers who introduced the back-propagation algorithm ( in a Nature article from 1986 with David Rumelhart and Ronald Williams) and developed, among others, the concepts of the Boltzmann machine and the Helmholtz machine. Easy to understand introductions to his scientific work can be found in his articles in Scientific American in 1992 and 1993.

In 2001 he received the first Rumelhart Prize.

Works

• How neural networks learn from experience. In: Scientific American. 9/1992
• DC Plaut and T. Shallice: Simulating brain damage. In: Scientific American. 10/1993