Who’s Who In AI: A curated directory of influential builders, researchers, founders, engineers, investors, writers, and public figures shaping the future of artificial intelligence.
About This Directory
Artificial intelligence is evolving rapidly, driven by a relatively small group of individuals whose ideas, research, products, and companies influence the direction of the industry.
This directory serves as a practical reference guide for anyone seeking to understand the people behind today’s most important AI breakthroughs, businesses, platforms, and conversations.
Whether you’re researching industry leaders, discovering influential voices, following emerging startups, or simply learning who’s shaping the future of AI, this directory provides a structured place to begin.
Who’s Who in AI
There are currently 2 names in this directory beginning with the letter H.
Hartmut Neven
Founder and Lead, Google Quantum AI; VP of Engineering, Google
Hartmut Neven studied physics and economics across Brazil, Germany, France, and Israel, earning his PhD in 1996 with a focus on autonomous robots and self-driving cars. He coined the terms "Quantum Machine Learning" and "Quantum AI," and in 2007 implemented the first machine learning and image recognition algorithms on a quantum computer. His computer vision company Neven Vision — which launched face login, face filters, and visual search for mobile phones — was acquired by Google in 2006.
He founded Google's Quantum AI lab in 2012, which has since produced some of the most advanced scientific achievements in quantum computing to date — including the first physical instantiations of time crystals, non-Abelian anyons, and traversable wormholes using a quantum processor.
His most recent landmark: the Willow quantum chip, announced in late 2024, which Neven says solved the 30-year challenge of quantum error correction — enabling more qubits while exponentially reducing error rates. In April 2026, Neven expanded Google's quantum program to include neutral atom systems alongside superconducting qubits, targeting commercially relevant quantum computing by end of decade.
A law bears his name. Neven's Law posits that quantum systems improve at a double-exponential rate — and his long-range prediction is unambiguous: "Long before AI turns 100, all advanced AIs will use quantum computing resources. We won't discriminate between AI and quantum anymore — there will be only one discipline, called quantum AI."
Submitted by: Admin Hartmut Neven studied physics and economics across Brazil, Germany, France, and Israel, earning his PhD in 1996 with a focus on autonomous robots and self-driving cars. He coined the terms "Quantum Machine Learning" and "Quantum AI," and in 2007 implemented the first machine learning and image recognition algorithms on a quantum computer. His computer vision company Neven Vision — which launched face login, face filters, and visual search for mobile phones — was acquired by Google in 2006.
He founded Google's Quantum AI lab in 2012, which has since produced some of the most advanced scientific achievements in quantum computing to date — including the first physical instantiations of time crystals, non-Abelian anyons, and traversable wormholes using a quantum processor.
His most recent landmark: the Willow quantum chip, announced in late 2024, which Neven says solved the 30-year challenge of quantum error correction — enabling more qubits while exponentially reducing error rates. In April 2026, Neven expanded Google's quantum program to include neutral atom systems alongside superconducting qubits, targeting commercially relevant quantum computing by end of decade.
A law bears his name. Neven's Law posits that quantum systems improve at a double-exponential rate — and his long-range prediction is unambiguous: "Long before AI turns 100, all advanced AIs will use quantum computing resources. We won't discriminate between AI and quantum anymore — there will be only one discipline, called quantum AI."
Heidy Khlaaf
Chief AI Scientist, AI Now Institute
Heidy Khlaaf worked in traditional safety engineering for nuclear power plants and autonomous vehicles before joining OpenAI, where she developed a methodology to evaluate the safety of Codex — the predecessor to ChatGPT — by analyzing and assessing risk categories and mitigation strategies. That methodology has since been adopted by AI labs worldwide. She later served as Engineering Director of the AI Assurance team at Trail of Bits, where she led cyber evaluations as part of the launch of the UK AI Safety Institute and unveiled the LeftoverLocals vulnerability. She holds a Computer Science doctorate in Formal Verification from University College London.
Her current focus is the area where AI safety is most consequential and least examined: warfare. At the AI Now Institute, Khlaaf specifically assesses the safety of AI within autonomous weapons systems — and every one she has studied has fallen below the risk thresholds set for conventional weapons. "The existing safety guardrails for generative AI are deeply lacking," she says. "It's highly doubtful that if they cannot guard systems against benign cases, they'd be able to do so for complex military and surveillance operations."
Her framing of the military AI race is deliberately contrarian: "Why is AI adoption the measure to win the race when these systems are faulty and likely to harm your national security?"
MIT Technology Review named her to its 35 Innovators Under 35.
Submitted by: Admin Heidy Khlaaf worked in traditional safety engineering for nuclear power plants and autonomous vehicles before joining OpenAI, where she developed a methodology to evaluate the safety of Codex — the predecessor to ChatGPT — by analyzing and assessing risk categories and mitigation strategies. That methodology has since been adopted by AI labs worldwide. She later served as Engineering Director of the AI Assurance team at Trail of Bits, where she led cyber evaluations as part of the launch of the UK AI Safety Institute and unveiled the LeftoverLocals vulnerability. She holds a Computer Science doctorate in Formal Verification from University College London.
Her current focus is the area where AI safety is most consequential and least examined: warfare. At the AI Now Institute, Khlaaf specifically assesses the safety of AI within autonomous weapons systems — and every one she has studied has fallen below the risk thresholds set for conventional weapons. "The existing safety guardrails for generative AI are deeply lacking," she says. "It's highly doubtful that if they cannot guard systems against benign cases, they'd be able to do so for complex military and surveillance operations."
Her framing of the military AI race is deliberately contrarian: "Why is AI adoption the measure to win the race when these systems are faulty and likely to harm your national security?"
MIT Technology Review named her to its 35 Innovators Under 35.
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