Nobel Laureate · Chair of Google DeepMind · Chief Scientist of Alphabet
Sir Demis Hassabis is a Nobel Prize-winning AI researcher, entrepreneur and technology leader. He is the Chair of Google DeepMind and Chief Scientist of Alphabet, where he focuses on the future of artificial intelligence, artificial general intelligence and the application of AI to scientific discovery. He also continues to lead Isomorphic Labs, Alphabet's AI-powered drug discovery company.
Hassabis co-founded DeepMind in 2010 with the ambition of developing artificial general intelligence through an interdisciplinary approach combining artificial intelligence, neuroscience, mathematics, engineering and computing. DeepMind was acquired by Google in 2014 and later combined with Google Brain to form Google DeepMind.
He was previously CEO of Google DeepMind, leading the organization through major breakthroughs in artificial intelligence. In August 2026, he moved away from day-to-day operational leadership to become Chair of Google DeepMind and Chief Scientist of Alphabet, allowing him to focus more directly on strategic and global AGI matters, fundamental AI research and the application of AI to science.
Hassabis was a driving force behind AlphaGo, the pioneering AI system that defeated a world champion Go player, demonstrating the potential of advanced AI systems to solve complex problems previously considered exceptionally difficult. He also played a central role in AlphaFold, which transformed protein structure prediction and opened new possibilities for biological research and drug discovery.
In 2024, Hassabis was awarded the Nobel Prize in Chemistry, jointly with John Jumper and David Baker. Hassabis and Jumper were recognized for their work on AlphaFold, which enabled major advances in predicting protein structures.
Alongside his work at Google DeepMind, Hassabis is the founder and CEO of Isomorphic Labs, which applies advanced AI to drug discovery and the development of new approaches to human health.
His current work focuses on some of the most consequential questions in artificial intelligence: the development of increasingly capable AI systems, the future of AGI, AI safety, scientific discovery and the potential for AI to accelerate progress in fields such as medicine and biology.