Stanford scholars are working across disciplines to understand the rapidly changing implications of AI for society – and leveraging the technology to drive transformative breakthroughs in the lab.
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Faculty affiliated with the Stanford Institute for Human-Centered Artificial Intelligence
Stanford HAI grants for AI research since 2019
GPUs in “Marlowe,” a $30 million supercomputer introduced on campus to facilitate AI-based research across fields
Computer science Professor John McCarthy, a “founding father” of AI, established the Stanford Artificial Intelligence Laboratory on campus in 1963. It was one of the first in the world to pursue the development of AI systems.
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Stanford supports its AI researchers with university-scale computing power, seed and moonshot grants, fellowship programs for early-career scholars, and a growing network of cross-disciplinary centers and labs devoted to the field.
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Computer scientist Karen Liu is advancing embodied intelligence, a form of AI that lets robots and animated characters gather information and take actions to change the state of their world.
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Stanford radiologist and data scientist Curtis Langlotz develops AI-powered systems that help medical experts and patients improve care across a variety of diseases and ailments.
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Bioengineer Emma Lundberg is leveraging AI to map the human proteome in space and time, while reframing the way scientists think about genetic disease.
Established in 2019, Stanford HAI is an interdisciplinary institute that advances AI research, education, policy, and practice in the service of humanity. Through scholarship, fellowships, convenings, and direct engagement with policymakers and civil society leaders, HAI helps shape how AI is developed and governed – from California to Washington, D.C., to the international stage.
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Policymakers, business leaders, and the public turn to Stanford HAI’s AI Index for rigorous, objective insights into the technology’s progress, economic influence, and societal impact.
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Computer scientists Ludwig Schmidt and Diyi Yang study the foundations of AI, ensuring these tools are designed with people in mind.
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Data scientist James Zou discusses new findings that reveal fundamental gaps in how language models understand human perspective.
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“Human-centered AI is about bringing interdisciplinary and multi-stakeholder perspectives to the table – engineers, social scientists, ethicists, communities – so we can build systems that are trustworthy and supportive of human flourishing.”
Fei-Fei Li
Founding director of Stanford HAI and special advisor on AI to President Jonathan Levin | Image courtesy of QEPrize/Jason Alden
AI can be a vital accelerant in advancing solutions to some of humanity’s greatest challenges – guided by human curiosity, human needs, and human well-being.
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AI is accelerating drug discovery, improving detection and diagnosis of disease, enhancing the patient and provider experience, and democratizing access to leading expertise. Breakthroughs in Stanford labs have led to dozens of startup companies.
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Trained on a dataset that includes all known living species – and a few extinct ones – Evo 2 can predict the form and function of proteins in the DNA of all domains of life.
“Academic institutions are where most of the progress will be made in medical AI.”
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In a small pilot study, a Stanford Medicine-developed tool showed promise by decreasing physician burnout while maintaining safety.
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Researchers have developed a deep learning model that transforms overwhelming brain data into clear trajectories, opening new possibilities for understanding thought, emotion, and neurological disease.
Developed at Stanford Medicine, Nuclei.io is designed to improve workflow and diagnosis in cancer and other diseases.
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Researchers are using AI to build better climate models, track forest carbon, look into the geological past, and improve mineral exploration for the renewable energy transition.
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Researchers are using satellite imagery and machine learning to map human well-being in thousands of municipalities.
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Stanford scientists in Senegal hunting for schistosomiasis – a parasitic disease infecting 250 million people worldwide – used AI to transform local field work into satellite-powered risk analysis.
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Ripples of air known as atmospheric gravity waves can influence the polar vortex, severe winter weather, and long-term climate patterns. Using AI and machine learning, researchers have developed a way to realistically represent their effects in global climate models.
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Researchers are exploring a role for AI in professional education, studying workplace transformation, and rooting out illegal discrimination in real estate covenants.
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During two recent panels, scholars, industry leaders, and former policymakers explored government’s role in preparing workers and maintaining public trust during AI’s workplace transformation.
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Led by a former machine learning scientist and engineer, a new class aims to nurture future leaders who are conversant in the vocabulary of artificial intelligence.
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Through training, tool-testing, and in-house innovation, the Robert Crown Law Library is a model for how law schools can respond to legal AI.