The ten most-cited AI researchers in our monthly ranking. Explore the full list in our Top 50.
Explore the Top 50 10 people
Université de Montréal +2
Full Professor
Bengio’s 2003 neural language model helped lay the foundations of language AI. His group introduced attention, which lets models focus on relevant input, and GANs, which generate images. Attention paved the way for Transformer models behind ChatGPT. He shared the 2018 Turing Award with Hinton and LeCun and co-leads LawZero, which aims to build safer AI.
University of Toronto
University Professor Emeritus
Hinton is a pioneer of deep learning. His 1986 work popularized backpropagation—training neural networks by correcting errors. With Alex Krizhevsky and Ilya Sutskever, he developed AlexNet, the 2012 image-recognition breakthrough. He shared the 2018 Turing Award and 2024 Nobel Prize in Physics. In 2023 he left Google to speak freely about AI risks.
MIT +1
Associate Professor
He led ResNet, which lets information take shortcuts through a neural network and made far deeper models practical. He also helped create systems that locate and outline objects in images, and methods that teach visual AI by asking it to reconstruct missing parts of a picture.
Safe Superintelligence Inc.
Co-founder and CEO
Sutskever co-created AlexNet, a breakthrough in image recognition, and sequence-to-sequence learning for translating sentences. As OpenAI’s co-founder and chief scientist, he helped shape the GPT models and training larger models that led to ChatGPT. In 2024 he left to co-found Safe Superintelligence, aiming to build AI smarter than humans safely.
Independent
Sun helped lead Microsoft Research Asia’s work on ResNet, which made deeper image-recognition models practical, and Faster R-CNN, which sped up finding objects in images. He mentored a generation of computer-vision researchers and joined Megvii in 2016 as chief scientist and dean of its research institute. He died in June 2022 at age 45.
Anthropic
Member of Technical Staff
Girshick reshaped how AI finds objects in images through the R-CNN family of models and Detectron, an open-source toolkit for building such systems. He co-founded Vercept in 2024 to build AI that operates software. Anthropic acquired it in February 2026 and brought its team into Claude’s computer-use work.
University of Oxford
Professor of Computer Vision Engineering and Royal Society Research Professor
Zisserman helped establish how computers combine photographs to reconstruct three-dimensional scenes. His book with Richard Hartley, Multiple View Geometry in Computer Vision, became a standard reference. He also helped develop influential image-recognition systems and built an internationally recognised computer-vision research group at Oxford.
University of Science and Technology of China +1
Endowed Chair Professor
Ren was the lead author of Faster R-CNN, which made accurate object detection much faster, and co-authored ResNet, whose design enabled far deeper vision systems. Both became foundations for later image recognition and detection work; he now brings that expertise to autonomous driving at NIO.
AMI Labs +1
Co-founder and Executive Chairman
LeCun pioneered convolutional neural networks, which recognise patterns in images. His LeNet model powered a commercial system that read millions of bank checks. A shared 2018 Turing Award recipient, he advocates world models that learn how their environment works from observation, aiming to help AI reason and plan beyond predicting text.
Discovery Loop
Co-founder
Le helped found Google Brain and co-created sequence-to-sequence learning for translation, neural architecture search for designing networks, and EfficientNet for recognising images with less computing power. A Google Fellow who helped develop Gemini, he left Google DeepMind in 2026 to co-found Discovery Loop, which aims to automate scientific research.