Stanford HAI 资助项目

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All Grants Closed Hoffman-Yee Research Grants The Hoffman-Yee Research Grants are designed to address significant scientific, technical, or societal challenges requiring an interdisciplinary team and a bold approach.

These grants are made possible by a gift from philanthropists Reid Hoffman and Michelle Yee.

The Hoffman-Yee Research Grants are designed to address significant scientific, technical, or societal challenges requiring an interdisciplinary team and a bold approach.

These grants are made possible by a gift from philanthropists Reid Hoffman and Michelle Yee.

Applications closed on May 1, 2026 We welcome proposals for research projects that tackle important challenges and opportunities in this space from either a technical or social science perspective, with findings that can generate policy insights and recommendations.

Applications closed on August 18, 2026 Designed to support new, ambitious, and speculative ideas with the objective of getting initial results

Emerging research that requires advanced computational resources provided by the commercial cloud

Proposals due by Wednesday, September 16, 2026 at 11:59PM PT Aimed at supporting novel or emerging research that requires advanced computational resources provided by Google Cloud

Stanford HAI and the Wu Tsai Neurosciences Institute jointly seek proposals that transform our understanding of the human brain using AI and advance the development of intelligent technology.

Created to explore how generative AI can be applied in novel ways to support learning

The HAI and AIMI Partnership Grant is designed to fund new and ambitious ideas that reimagine artificial intelligence in healthcare, using real clinical data sets, with near term clinical applications.

Call for proposals will open up again in late 2026 Advances in artificial intelligence technology offer unprecedented opportunities to improve health and medicine, from accelerating biomedical research to strengthening care delivery and patient outcomes.

Since its founding, HAI’s grant programs have supported over 415 faculty members from all seven Stanford schools spanning multiple departments, in keeping with the commitment to support interdisciplinary AI research.

faculty funded

60 MM+ in grant funding distributed

research projects

Our Focus Areas AI is a general purpose technology that can be used for good and for ill. Our vision for the future is led by a commitment to human-centered uses of AI and data science and to ensuring that the benefits are broadly shared. In support of these goals, our research falls into three pillars: AI and data science for accelerating discovery, transforming education, and understanding and shaping AI for societal good.

AI can accelerate scholarship in every discipline — and domain-specific scholarship is itself key for advancing AI. We work to catalyze that virtuous cycle.

Better AI makes better scholarship possible. Less obviously, the reverse is also true: the hardest problems in, for example, astronomy, medicine, economics, and the humanities expose the limits of current models and point toward what AI needs to become. HAI is built to close that loop.

Our work here has two dimensions. AI-driven discovery advances every discipline, where domain-specific scholarship can itself become a powerful vector for advancing AI — from decoding the physical universe from data, to understanding how ideas, language, and cultures evolve, to designing environments and therapies for human health. Foundations of AI pursue new architectures, algorithms, and evaluation approaches that go beyond simply adding silicon to scale models, including the search for shared principles underlying natural and artificial intelligence.

As AI reshapes work and society, what should people learn, and how should they learn it? We are building the rigorous evidence base to answer these questions.

Most conversations about AI in education begin and end with how AI transforms schooling. We start from a broader goal: supporting human flourishing in the age of AI. That reframing changes the research agenda.

We ask what knowledge and skills learners of all ages actually need as AI reshapes work, civic life, and the professions. We also focus on how to learn: developing AI-enabled learning systems that genuinely support students, teachers, communities, and institutions.

Answering these questions requires evidence gathered over time. We aim to build longitudinal research infrastructure — with Stanford’s own courses serving as a testbed — to track learner outcomes through their time at Stanford and well beyond graduation. This work extends from K–12 through university and lifelong learning.

AI is scaling at a breakneck pace while public trust in its governance remains unsettled. HAI offers a rigorous, empirically grounded alternative to the extremes dominating public conversation.

To shape AI for positive societal impact, you need to understand both how the systems work and how they transform incentives, institutions, and human lives. That requires technical and humanistic expertise working in dialogue — not going along parallel tracks. That integration is what Stanford HAI was built to provide.

Our research fuses technical AI expertise, design, and humanistic inquiry to study AI systems as they actually behave in the world and to develop new methods and tools to design them for the better. Then we translate that scholarship into clear, trusted guidance that leaders can depend upon to make decisions as AI continues to evolve.

Active and Upcoming Grants Grants are open to Stanford research teams. All proposals must have a Stanford faculty who qualifies as a Principal Investigator per Stanford policy . Before funding is released, all proposals undergo an Ethics and Society Review to assess for any potential negative impact on society.

Proposals due by Wednesday, September 16, 2026 at 11:59PM PT Aimed at supporting novel or emerging research that requires advanced computational resources provided by Google Cloud

Applications closed on August 18, 2026 Designed to support new, ambitious, and speculative ideas with the objective of getting initial results