Hinton among seven engineers to win 2025 Queen Elizabeth Prize for Engineering

The 2025 Queen Elizabeth Prize for Engineering (QEPrize) has been awarded to seven engineers—Yoshua Bengio, Geoffrey Hinton, John Hopfield, Yann LeCun, Jensen Huang, Bill Dally, and Fei-Fei Li—in recognition of their seminal contributions to the advancement of Modern Machine Learning, a foundational component driving progress in artificial intelligence (AI).  

The combined work of these innovators has been critical in pushing forward the three main components of Modern Machine Learning: advanced algorithms, high-performance computing hardware, and high-quality datasets. Together, these elements support the widespread use and advancement of AI systems, thanks to the contributions and foresight of this year's awardees. 

Modern Machine Learning, which enables systems to learn from data, recognise patterns, and make predictions without explicit programming has transformed AI by enabling models to autonomously improve with new data. Yoshua Bengio, Geoffrey Hinton, John Hopfield, and Yann LeCun have been key in promoting artificial neural networks, now the leading framework in machine learning. Their research established the essential theories for this innovative method, allowing machines to understand and learn from extensive sets of data in unprecedented ways. 

Jensen Huang and Bill Dally have been pioneers in developing the hardware essential for running modern machine learning algorithms. Fei-Fei Li’s contribution is the creation of ImageNet, an image database, which has provided access to millions of labelled images, proving vital in training and assessing computer vision algorithms.

Professor Geoffrey Hinton graduated from the University of Edinburgh with a PhD in Artificial Intelligence in 1978. He is also an honorary graduate of the University of Edinburgh with a degree of Doctor of Science in awarded in 2001. He’s a fellow of the Royal Society, the Royal Society of Canada, and the Association for the Advancement of Artificial Intelligence.

He was awarded the first David E. Rumelhart prize (2001), the IJCAI award for research excellence (2005), the Killam prize for Engineering (2012), the IEEE James Clerk Maxwell Gold medal (2016), and the ACM Turing Prize (2018) among other awards.

He worked at Sussex University, University College London, the University of California San Diego, Carnegie-Mellon University, and the University of Toronto, where he is now an emeritus distinguished professor.

Awarded annually, the Queen Elizabeth Prize for Engineering (QEPrize) is awarded annually for engineering-led advances that are judged to be of tangible and widespread benefit to the public.  

 The £500,000 prize celebrates engineering’s visionaries, inspiring young minds to consider engineering as a career choice and to help to solve the challenges of the future.  

 The Prize also encourages engineers to help extend the boundaries of what is possible across all disciplines and applications. 

Edinburgh has been at the forefront of AI research for more than six decades, establishing Europe’s first dedicated research group on the topic in 1963.  

 The University is today one of Europe’s largest centres for AI research, with hundreds of researchers conducting leading-edge research into fundamental and applied AI.  

 The Generative AI Laboratory (GAIL) – which opened in 2023 – unites the University’s world-leading research and innovation in AI to develop safe solutions and systems for industry and government and bring substantial benefits to those who use them.