The staggering volume of data available today has generated a growing need for automated systems that can spot patterns, learn from examples, understand the “big picture” and make predictions. This trend makes machine learning one of the most important frontiers in modern science.
The University of Toronto’s Geoffrey Hinton is among the world’s foremost researchers in the field. His contributions to machine learning and artificial intelligence have benefited virtually every discipline in science, engineering, social science and medicine. These achievements have earned him the 2010 Gerhard Herzberg Canada Gold Medal for Science and Engineering from NSERC.
In the quest to create artificial intelligence, part of the challenge is to understand the principles of human learning and apply them to machines. As a result of Dr. Hinton’s research, computers are now better at finding complicated patterns in scientific, medical, economic or other data. He has developed algorithms used in applications such as creating better systems for voice recognition, automatically reading bank cheques and monitoring industrial plants for improved safety.
In addition to his work in machine learning, Dr. Hinton has contributed to cognitive psychology and neuroscience by proposing influential theories of how the brain generates its internal representations of the visual world from the sensory input it receives from the eyes.
Dr. Hinton’s numerous international awards include the inaugural David E. Rumelhart Prize in 2001, which recognizes outstanding contributions to the theoretical foundations of human cognition. He also received the 2005 International Joint Conferences on Artificial Intelligence Research Excellence Award, a prestigious honour that has been awarded to only 12 recipients over the past 24 years.