Systems, Man & Cybernetics - April 2015 - 40

Awards

2014 IEEE Frank
Rosenblatt Award

P

rof. Geoffrey Hinton was
named the 2014 IEEE Frank
Rosenblatt Award recipient.
Prof. Hinton is an emeritus university professor with the Department of
Computer Science at the University of
Toronto, Canada. Prof. 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 the 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 he has revolutionized machine
learning several times over. He 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. Prof. Hinton aims to discover an efficient learning procedure
to identify complex structure in large,
high-dimensional data sets 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

Digital Object Identifier 10.1109/MSMC.2015.2442171
Date of publication: 16 September 2015

40

Prof. Geoffrey Hinton (right) accepts
the 2014 IEEE Frank Rosenblatt
Award.

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 objectrecognition technology, and his algorithms have been applied to many
other tasks, including collaborative
filtering. Prof. Hinton's 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.
Prof. Hinton earned his B.A. degree
in experimental psychology from Cambridge University, United Kingdom, in
1970 and his Ph.D. degree in artificial
intelligence from the University of
Edinburgh, United Kingdom, in 1978.
He did postdoctoral work at Sussex
University in the United Kingdom and
the University of California, San Diego,
and spent five years as a faculty member in the Computer Science Depart-

IEEE Systems, Man, & Cybernetics Magazine A pr il 2015 	

ment at Carnegie-Mellon University,
Pittsburgh, Pennsylvania. From 1998
to 2001 he set up the Gatsby Computational Neuroscience Unit at University
College London.
Prof. 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/National Sciences and Engineering Research Council of Canada
(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 the
study of fly vision, he developed the
single-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 the IEEE, a recipient
selection is administered through the
Technical Field Awards Council of
the IEEE Awards Board.



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2015

Systems, Man & Cybernetics - April 2015 - Cover1
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Systems, Man & Cybernetics - April 2015 - 1
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Systems, Man & Cybernetics - April 2015 - Cover3
Systems, Man & Cybernetics - April 2015 - Cover4
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