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Image of eighteen brain slices arranged in three rows

I had job options in US. But I decided to join the University of Toronto; one of the main reasons was CIFAR.

Hae-Young Kee
Senior Fellow, Quantum Materials

Neural Computation & Adaptive Perception

Hidden somewhere in the dense architecture of the human brain is the astounding power to convert the signals flowing along millions of sensory nerve fibres into a coherent model of the world.


Neural Computation & Adaptive Perception aims to unlock the mystery of how our brains convert sensory stimuli into information and to recreate human-style learning in computers. While this group focuses on visual systems, their research also points to broader explanations of how the brain processes other kinds of important information, including sounds, smells and tastes.

Not only has their research provided promising new explanations of how people learn, it has also bolstered efforts to create new artificial visual systems and synthetic neural networks that have brain-like learning capability.

One key to understanding how the brain processes visual information is to determine the algorithm, or computational principle, responsible for brain function. This algorithm can be used to create intelligent devices, such as artificial eyes wired directly into the nervous system, or security surveillance devices at airports that can pick out suspicious objects.

Beyond engineering applications, a deeper understanding of the brain could also provide new understanding of brain diseases such as Parkinson’s and Alzheimer’s. Researchers know that these diseases result when the brain’s algorithms break down, but they are not sure exactly how or why. A better understanding of the brain could help to figure out how to do maintenance on it and help to sustain a high mental quality of life.

Program members have backgrounds in computer science, psychology, electrical and computer engineering, neuroscience, and ophthalmology.

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CO-DIRECTOR

Yoshua Bengio

Neural Computation & Adaptive Perception

Yoshua Bengio received his PhD in Computer Science from McGill University in 1991. After two post-doctoral years, one at M.I.T. and one at AT&T Bell Laboratories, he became a Professor in the Department of Computer Science and Operations Research at Université de Montréal.

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CO-DIRECTOR

Yann Lecun

Neural Computation & Adaptive Perception

Dr. Yann LeCun is Silver Professor of Computer Science and Neural Science at New York University, where he is affiliated with the Courant Institute of Mathematical Sciences, and the Center for Neural Science.

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