Deep learning People

Geoffrey Hinton is a computer scientist born in London whose research on neural networks, including back-propagation and deep convolutional networks, is central to deep learning. He shared the 2018 ACM A.M. Turing Award and the 2024 Nobel Prize in Physics.

Yann LeCun is a French computer scientist known for convolutional neural networks, which learn to recognise images directly from pixels. He co-authored the 1998 paper that introduced LeNet-5 and shared the 2018 ACM A.M. Turing Award.

Canadian computer scientist whose work on sequence models, word embeddings and attention helped lay foundations for modern language models. He shared the 2018 ACM A.M. Turing Award with Geoffrey Hinton and Yann LeCun.

Israeli-Canadian computer scientist born in 1986 who co-built AlexNet, co-founded OpenAI and served as its chief scientist, and later founded Safe Superintelligence Inc.

Marvin Minsky (1927–2016) was an American scientist who co-founded MIT’s AI laboratory and co-signed the 1955 Dartmouth proposal. With Seymour Papert he wrote the 1969 book Perceptrons, which analysed the limits of simple neural networks.

Frank Rosenblatt (1928–1971) was an American psychologist who developed the perceptron, an early learning machine that adjusted its weights from examples. His Mark I Perceptron is now held by the Smithsonian Institution.

American physicist born in 1933 who invented the Hopfield network in 1982, a model that stores and recalls patterns using ideas from spin physics, and who received half of the 2024 Nobel Prize in Physics.

David Rumelhart (1942–2011) was an American cognitive psychologist. His 1986 work with colleagues helped bring back-propagation and neural-network models to a wide audience.

Protein scientist at the University of Washington in Seattle, known for computational protein design: he designed a protein unlike any in nature in 2003 and received one half of the 2024 Nobel Prize in Chemistry.

German computer scientist and co-author, with Sepp Hochreiter, of the 1997 LSTM paper. He has directed the Swiss AI lab IDSIA since 1995 and has publicly argued that some contributions to AI deserve more credit.

German computer scientist who co-developed the long short-term memory (LSTM) network, a recurrent neural network design for learning from sequences such as text and speech. He led the xLSTM work in 2024.

American computer scientist known for Google's core infrastructure — MapReduce, Bigtable and Spanner — and for leading work on Google Brain, TensorFlow and, from 2023, the role of Google's chief scientist.

Stanford computer scientist Fei-Fei Li created ImageNet, the large-scale image dataset and challenge that gave data-driven computer vision a common benchmark, and has led AI research in both academia and industry.

British computer scientist born in 1976 who specialises in reinforcement learning. He led DeepMind's AlphaGo project, co-authored the 2013 deep Q-network paper and later founded Ineffable Intelligence.

Demis Hassabis is a British AI researcher and entrepreneur who co-founded DeepMind and was the last author of the 2016 AlphaGo paper. He shared the 2024 Nobel Prize in Chemistry for work on predicting protein structures.

Czech computer scientist and lead author of word2vec, the 2013 methods that learn word vectors from text. His later work includes the fastText library and research on mathematical models that grow in complexity.

American scientist (born 1985) who worked on AlphaFold at Google DeepMind and shared half of the 2024 Nobel Prize in Chemistry with Demis Hassabis for protein structure prediction.

AI researcher and educator, born in Bratislava and raised partly in Toronto, who co-founded OpenAI, led AI at Tesla, taught Stanford's CS231n course, and later joined Anthropic's pre-training team.

Chelsea Finn is a computer scientist and assistant professor at Stanford University whose research spans meta-learning, deep reinforcement learning and robot learning; she is a co-founder of Physical Intelligence.

Jakob Uszkoreit is one of the eight authors of “Attention Is All You Need” and the founder of Inceptive, a company using AI to design biological molecules.[^1][^4]

Chris Olah is a Canadian machine learning researcher and co-founder of Anthropic, known for work on mechanistic interpretability, the effort to understand the internal workings of neural networks.

Andrew G. Barto is a computer scientist who helped establish reinforcement learning as a general framework and shared the 2024 ACM A.M. Turing Award with Richard Sutton.

Richard Sutton is a computer scientist at the University of Alberta known for his work on reinforcement learning; he co-authored the field's standard textbook and shared the 2024 ACM A.M. Turing Award with Andrew Barto.

Koray Kavukcuoglu is a DeepMind computer scientist who co-authored the first deep Q-network paper and later, as Google DeepMind's CTO and Google's chief AI architect, fronted successive Gemini model launches.

Durk Kingma is a machine learning researcher and co-author of the variational autoencoder and the Adam optimizer; he has worked at OpenAI, Google Brain / DeepMind and Anthropic.

Ian Goodfellow is a machine learning researcher and first author of the 2014 paper that introduced generative adversarial networks, which train a generator and a discriminator against each other. He has worked at OpenAI, Google Brain, Apple and Google DeepMind.

Jensen Huang is a founder of NVIDIA and has served as its president, CEO and board member since the company was founded in 1993. NVIDIA credits the company's invention of the GPU and its work in accelerated computing to that era.

Quoc Le is a machine-learning researcher whose 2013 Stanford Ph.D. thesis was on scalable feature learning. He co-authored papers on large-scale unsupervised learning, sequence-to-sequence models, neural architecture search and EfficientNet; the sequence-to-sequence paper won a NeurIPS 2024 Test of Time award.

Niki Parmar is one of the eight authors of "Attention Is All You Need", the 2017 paper that introduced the Transformer architecture, and is named in Google's own account of that work.

Llion Jones is one of the eight authors of the 2017 paper "Attention Is All You Need" and a co-founder and CTO of Sakana AI.

Illia Polosukhin is one of the eight authors of the 2017 Transformer paper and a co-founder of NEAR Protocol. A 2024 NEAR post identifies him as CEO of the NEAR Foundation.[^1][^3][^6]

Christopher Manning is a Stanford professor of linguistics and computer science, former SAIL director, and former ACL president, recognized with fellowships and academy memberships.

Pieter Abbeel is a UC Berkeley professor who directs the Berkeley Robot Learning Lab and co-directs BAIR; his honors include the ACM Prize in Computing and IEEE Fellow status.

Noam Shazeer is an AI researcher who co-wrote the Transformer paper and was first author of the paper on sparsely gated mixture-of-experts layers. He co-founded Character.AI, returned to Google in 2024, and announced a move to OpenAI in 2026.

Ashish Vaswani is a computer scientist best known as the first-listed author of “Attention Is All You Need,” the 2017 paper that introduced the Transformer architecture. He also co-founded the AI companies Adept and Essential AI.

Kaiming He is a computer-vision and deep-learning researcher, first author of the 2015 ResNet paper that introduced residual connections, now a tenured associate professor at MIT.

Aidan Gomez is a Canadian computer scientist, co-founder and CEO of Cohere, and one of the eight authors of the 2017 paper that introduced the Transformer architecture.

Sergey Levine is a computer scientist who studies how robots can learn control behaviour from data. He is a professor at UC Berkeley and a co-founder of Physical Intelligence.

Tang Xiaoou (1968–2023) was a Chinese computer vision researcher at the Chinese University of Hong Kong and co-founder and chairman of SenseTime, one of China's best-known AI companies.

Spanish computer scientist (born 1983) who co-invented sequence-to-sequence learning, led DeepMind's AlphaStar research group, and became a technical lead on Gemini before leaving to start Discovery Loop.

Canadian machine-learning researcher who was one of Geoffrey Hinton's earliest hires at Google Brain's Toronto office, co-founded the natural language processing company Cohere in Toronto in 2019, and is lead vocalist of the indie rock band Good Kid.

Karol Hausman is a roboticist working on robot learning, sim-to-real transfer and embodied AI. He was a senior research scientist at Google Brain and Google DeepMind, is an adjunct professor at Stanford, and co-founded Physical Intelligence.

Shun-ichi Amari (born 1936) is a Japanese mathematical engineer who founded information geometry and built theoretical foundations for machine learning and neural networks; he received the 2025 Kyoto Prize in Advanced Technology.

Jacob Devlin is a research scientist and first author of BERT, a language model Google introduced in 2018 that reads text in both directions. He earlier worked on neural machine translation at Microsoft Research.

Thomas Wolf is a co-founder and chief science officer of Hugging Face, and the first author of the 2019 paper that introduced the company's open-source Transformers library to researchers and practitioners.

Shane Legg is a New Zealand AI researcher and co-founder of DeepMind, known for helping popularise the term "artificial general intelligence" and for leading the company's AGI safety work.

Sun Jian was a computer-vision scientist who spent 13 years at Microsoft, co-created ResNet, and later became chief scientist at Megvii. He died aged 45 after a sudden illness in June 2022.