Geoffrey Hinton

Geoffrey Everest Hinton (born 6 December 1947 in Wimbledon is a British cognitive psychologist and computer scientist who became a naturalized Canadian. Known for his contributions to the development of machine learning, he is considered one of the most influential researchers in the development of deep learning. He is an emeritus professor at the University of Toronto and a former VP and Engineering Fellow at Google.

In 1986 he published with David Rumelhart and Ronald J. Williams a particularly influential paper, which popularized the already known use of the error backpropagation algorithm for the training of multi-level neural networks. In 2012, AlexNet, a deep neural network designed in collaboration with his students Alex Krizhevsky and Ilya Sutskever, achieved breakthrough results in the image classification problem, improving the results of the ImageNet challenge in 2012 by a large margin and paving the way for the application of deep neural networks in computer vision problems.

In 2018, he received, together with Yoshua Bengio and Yann LeCun, the Turing Award for his contributions to the development of deep learning. In 2024 he was awarded the Nobel Prize in Physics for his contributions to machine learning.

Image credit Johnny Guatto, University of Toronto