Biosketch

Geoffrey Hinton received his PhD in Artificial Intelligence from Edinburgh in 1978. After five years as a faculty member at Carnegie-Mellon he became a fellow of the Canadian Institute for Advanced Research and moved to the Department of Computer Science at the University of Toronto where he is now an Emeritus Professor and Chief Scientific Adviser at the Vector Institute. From 2013 to 2023 he was a VP Engineering fellow at Google.

He was one of the researchers who introduced the backpropagation algorithm and the first to use backpropagation for learning word embeddings. His other contributions to neural network research include Boltzmann machines, distributed representations, time-delay neural nets, mixtures of experts, variational learning and deep learning. His research group in Toronto made major breakthroughs in deep learning that revolutionized speech recognition and object classification.

Geoffrey Hinton is a fellow of the UK Royal Society and a foreign member of the US National Academy of Engineering and the American Academy of Arts and Sciences. His awards include the David E. Rumelhart prize, the IJCAI award for research excellence, the Killam prize for Engineering, the IEEE Frank Rosenblatt medal, the NSERC Herzberg Gold Medal, the IEEE James Clerk Maxwell Gold medal, the NEC C&C award, the BBVA award, the Honda Prize, The Royal Medal of the Royal Society and the Turing Award.

Research Interests

Learning in artificial neural nets and its relationship to learning in real neural nets. Shape representation in neural nets.

Membership Type

International Member

Election Year

2023

Primary Section

Section 52: Psychological and Cognitive Sciences

Secondary Section

Section 34: Computer and Information Sciences