A structured reference to the individuals shaping artificial intelligence across research, industry, governance, ethics, and public discourse. Curated as a resource for professionals navigating the AI landscape. For more see the full list at AI People.

Deep Learning and Representation Learning

Geoffrey Hinton | Deep Learning, AI Safety | Canada The "godfather of deep learning" whose persistence through two AI winters kept neural network research alive. His work on backpropagation, deep belief networks, and representation learning enabled modern AI. Left Google in 2023 to speak openly about existential risks. Co-recipient of the 2024 Nobel Prize in Physics. Key works: Backpropagation papers, deep belief networks, Boltzmann machines

Yann LeCun | Convolutional Networks, Computer Vision | United States Invented convolutional neural networks in the 1980s-the architecture that now powers image recognition, medical imaging, and autonomous vehicles. Chief AI Scientist at Meta and vocal advocate for self-supervised learning as the path to more capable AI. Co-recipient of the 2018 Turing Award. Key works: LeNet, convolutional neural networks for vision

Yoshua Bengio | Deep Learning, AI Safety | Canada Pioneered neural language models and deep learning techniques. Co-authored the "Deep Learning" textbook that trained a generation. Recently pivoted to AI safety research, becoming one of the most prominent technical researchers warning about advanced AI risks. Co-recipient of the 2018 Turing Award. Key works: "Deep Learning" (2016), neural language models, safety research

Jürgen Schmidhuber | Recurrent Networks, Sequence Learning | Switzerland Co-invented LSTM networks with Sepp Hochreiter, solving the vanishing gradient problem that had stymied recurrent neural networks. LSTM became the foundation for speech recognition, machine translation, and language models until the transformer era. Key works: LSTM architecture, recurrent learning

Sepp Hochreiter | LSTM, Recurrent Networks | Austria Co-invented Long Short-Term Memory (LSTM) networks, enabling neural networks to learn from sequences and remember over long time spans. This breakthrough powered a decade of advances in speech recognition and natural language processing. Key works: "Long Short-Term Memory" (1997)

Ian Goodfellow | Generative Models, Adversarial ML | United States Invented Generative Adversarial Networks (GANs) in 2014, creating a new paradigm for generating realistic images, videos, and other content. Also pioneered adversarial examples research, revealing how easily neural networks can be fooled. Key works: "Generative Adversarial Nets" (2014), adversarial ML research

Alex Krizhevsky | Computer Vision, GPU Computing | Canada Created AlexNet with Hinton and Sutskever, winning the 2012 ImageNet competition by a dramatic margin and triggering the deep learning revolution. Demonstrated that GPUs could train neural networks far faster than CPUs, reshaping the field's infrastructure. Key works: "ImageNet Classification with Deep Convolutional Neural Networks" (2012)

Ilya Sutskever | Deep Learning, Foundation Models | United States Co-created AlexNet and sequence-to-sequence learning. As Chief Scientist at OpenAI, led research behind GPT models. Co-founded Safe Superintelligence Inc. in 2024, focusing exclusively on building safe superintelligent AI. One of the most influential figures in the foundation model era. Key works: AlexNet, seq2seq, GPT research leadership

Kaiming He | Computer Vision, Architecture Design | United States Invented ResNet (residual networks), which solved the degradation problem in very deep networks and enabled training of networks with hundreds of layers. Also created Mask R-CNN for instance segmentation. His architectural innovations are embedded in most modern vision systems. Key works: ResNet, Mask R-CNN

Fei-Fei Li | Computer Vision, AI Ethics | United States Created ImageNet, the dataset and competition that catalysed the deep learning revolution. Founded Stanford's Human-Centered AI Institute, advocating for AI development that considers human values. Bridges technical research with broader societal concerns. Key works: ImageNet dataset and challenge, Human-Centered AI leadership

Diederik P. Kingma | Generative Models, Optimisation | United States Co-invented Variational Autoencoders (VAEs) and created the Adam optimiser-now the default for training neural networks. His work on generative models and optimisation techniques is embedded in virtually every modern deep learning system. Key works: VAE papers, Adam optimiser

Kunihiko Fukushima | Neural Networks, Vision | Japan Created the neocognitron in 1980-a precursor to convolutional neural networks that introduced key concepts like hierarchical feature extraction. His work anticipated modern computer vision architectures by decades. Key works: Neocognitron (1980)

Oriol Vinyals | Sequence Learning, Game AI | United Kingdom Led the AlphaStar project that achieved grandmaster level in StarCraft II. Pioneered sequence-to-sequence learning and attention mechanisms. His work spans from neural machine translation to game-playing AI, demonstrating deep learning's versatility. Key works: Seq2seq contributions, AlphaStar, pointer networks

Chelsea Finn | Meta-Learning, Robotics | United States Created Model-Agnostic Meta-Learning (MAML), enabling AI systems to learn new tasks from small amounts of data. Her work on meta-learning and robot learning addresses one of AI's key limitations: the need for massive training data. Key works: MAML, robot learning research

How to Use This Directory

For research: Each entry includes key works and affiliations for deeper investigation.

For event planning: Filter by geographic base, domain, or public engagement experience.

For understanding the field: The categorisation reveals how different communities, from technical researchers, ethicists, policymakers, industry leaders all shape AI development.

For identifying perspectives: Note whose voices are included and whose might be missing from any particular AI conversation.

This directory is maintained as a resource for the AI age. Last updated: 2026.

Curated by Rahim Hirji for thesuperskills.com.

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