Geoffrey Hinton is an Emeritus University Professor with the Department of Computer Science at
the University of Toronto, Canada. Professor Hinton joined Google Inc. as Distinguished
Researcher in March 2013 when his company, DNNresearch Inc, was acquired. He now divides
his time working for Google and University of Toronto.
A computer scientist with an interest in neuroscience and psychology, he is most noted for his
pioneering work on the back-propagation and Boltzmann Machine learning algorithms for training
neural networks and has revolutionized machine learning several times over. Professor Hinton
helped establish the field of machine learning and has dedicated his research to understanding
how the human brain works and how this knowledge can be applied to provide machines with
brain-like capabilities for performing complex tasks. He aims to discover an efficient learning
procedure to identify complex structure in large, high-dimensional datasets and to show that this
is how the brain learns to see. He is an important figure in the deep learning movement where
some of his work provides new models of biological learning. By employing multiple levels, it is
capable of producing the type of deep hierarchies of abstract representations that are known to
exist in the brain. His work has provided revolutionary changes in speech recognition and object
recognition technology and his algorithms have been applied to many other tasks, including
collaborative filtering. His other contributions to neural network research include distributed
representations, time-delay neural nets, mixtures of experts, variational learning, products of
experts and deep belief nets.
Professor Hinton received his BA in experimental psychology from Cambridge in 1970 and his
PhD in Artificial Intelligence from Edinburgh in 1978. He did postdoctoral work at Sussex
University and the University of California San Diego, and spent five years as a faculty member in
the Computer Science Department at Carnegie-Mellon. He spent three years from 1998 until
2001 setting up the Gatsby Computational Neuroscience Unit at University College London.
Professor Hinton is a fellow of the Royal Society, the Royal Society of Canada, and the
Association for the Advancement of Artificial Intelligence. He is an honorary foreign member of
the American Academy of Arts and Sciences, and a former president of the Cognitive Science
Society. He has received honorary doctorates from the University of Edinburgh, the University of
Sussex, and the University of Sherbrooke. He was awarded the first David E. Rumelhart prize
(2001), the IJCAI award for research excellence (2005), the IEEE Neural Network Pioneer award
(1998), the ITAC/NSERC award for contributions to information technology (1992) the Killam
prize for Engineering (2012) and the NSERC Herzberg Gold Medal (2010) which is Canada's top
award in Science and Engineering.
About the IEEE Frank Rosenblatt Award
The award was established in 2004 and is named in honor of Frank Rosenblatt, who is widely
regarded as one of the founders of neural networks. Basing his research on study of fly vision, he
developed the single-layer input layer and an output layer of neural cells. Frequent presentation
of a pattern or patterns resulted in changes in the input to output connections, facilitating future
recognition of these patterns, or memory. His work influenced and even anticipated many modern
neural network approaches. At IEEE, recipient selection is administered through the Technical
Field Awards Council of the IEEE Awards Board.