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Mathematical Foundations of Artificial Intelligence is sponsored by National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). This grant supports interdisciplinary research on mathematical and theoretical foundations for sustainable, trustworthy, and socially responsible AI.
It addresses foundational gaps in AI through collaborations between mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists. The goal is to establish innovative and principled design and analysis approaches for AI technology, yielding explainable and interpretable models for sustainable, socially responsible, and trustworthy AI.
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Mathematical Foundations of Artificial Intelligence (MFAI) | NSF - U.S. National Science Foundation Mathematical Foundations of Artificial Intelligence (MFAI) Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .
All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects. Supports research collaborations between mathematicians, statisticians, computer scientists, engineers and social behavior scientists to establish innovative and principled design and analysis approaches for AI technology.
Supports research collaborations between mathematicians, statisticians, computer scientists, engineers and social behavior scientists to establish innovative and principled design and analysis approaches for AI technology.
Machine Learning and Artificial Intelligence (AI) are enabling extraordinary scientific breakthroughs in fields ranging from protein folding, natural language processing, drug synthesis, and recommender systems to the discovery of novel engineering materials and products.
These achievements lie at the confluence of mathematics, statistics, engineering and computer science, yet a clear explanation of the remarkable power and also the limitations of such AI systems has eluded scientists from all disciplines. Critical foundational gaps remain that, if not properly addressed, will soon limit advances in machine learning, curbing progress in artificial intelligence.
It appears increasingly unlikely that these critical gaps can be surmounted with increased computational power and experimentation alone. Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet the future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology.
The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE) will jointly sponsor research collaborations consisting of mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists focused on the mathematical and theoretical foundations of AI.
Research activities should focus on the most challenging mathematical and theoretical questions aimed at understanding the capabilities, limitations, and emerging properties of AI methods as well as the development of novel, and mathematically grounded, design and analysis principles for the current and next generation of AI approaches.
Specific research goals include: establishing a fundamental mathematical understanding of the factors determining the capabilities and limitations of current and emerging generation s of AI systems, including, but not limited to, foundation models, generative models, deep learning, statistical learning, federated learning, and other evolving paradigms; the development of mathematically grounded design and analysis principles for the current and next generations of AI systems; rigorous approaches for characterizing and validating machine learning algorithms and their predictions; research enabling provably reliable, translational, general-purpose AI systems and algorithms; e ncouragement of new collaborations in this interdisciplinary research community and between institution s.
The overall goal is to establish innovative and principled design and analysis approaches for AI technology using creative yet theoretically grounded mathematical and statistical frameworks, yielding explainable and interpretable models that can enable sustainable, socially responsible, and trustworthy AI.
October 3, 2024 - Mathematical Foundations of Artificial Intelligence Office… September 19, 2024 - Mathematical Foundations of Artificial Intelligence Office… June 12, 2024 - Mathematical Foundations of Artificial Intelligence Webinar Awards made through this program Browse projects funded by this program Map of recent awards made through this program Directorate for Mathematical and Physical Sciences (MPS) Division of Mathematical Sciences (MPS/DMS) Directorate for Computer and Information Science and Engineering (CISE) Division of Computing and Communication Foundations (CISE/CCF) Division of Information and Intelligent Systems (CISE/IIS) Directorate for Engineering (ENG) Division of Civil, Mechanical and Manufacturing Innovation (ENG/CMMI) Division of Electrical, Communications and Cyber Systems (ENG/ECCS) Directorate for Social, Behavioral and Economic Sciences (SBE) Division of Social and Economic Sciences (SBE/SES)
According to the current listing, eligibility includes: Research collaborations consisting of mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists are eligible. Universities are typically eligible to apply for NSF grants. Confirm the full requirements in the official notice before applying.
The current listing shows $1,500,000. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Mathematical Foundations of Artificial Intelligence are due October 9, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Mathematical Foundations of Artificial Intelligence is funded by National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Applications go through the funder's official portal — the Apply Now link on this page goes there directly.
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Mathematics Foundations of Artificial Intelligence (MFAI) is sponsored by National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). Mathematics Foundations of Artificial Intelligence (MFAI) is sponsored by National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic …
Mathematical Foundations of Artificial Intelligence (MFAI) is sponsored by National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). This program supports research collaborations focused on the mathematical and theoretical foundations of AI and machine learning, particularly in areas like recommender systems. The goal is to establish a fundamental mathematical understanding of the capabilities and limitations of current and emerging AI systems, and to develop mathematically grounded design and analysis principles.
Mathematical Foundations of Artificial Intelligence is sponsored by U.S. National Science Foundation (NSF) Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE). This program sponsors research collaborations focused on the mathematical and theoretical foundations of AI. It addresses challenging mathematical and theoretical questions to understand AI's capabilities, limitations, and emerging properties.
Economics of AI Fellowship is sponsored by Stripe. The fellowship supports foundational academic research in the economics of AI, an area currently understudied despite rapid technical progress in artificial intelligence. Fellows receive a baseline grant, opportunities to attend conferences with leading economists and technologists, and potential access to unique data via Stripe and its customers.
The UKRI Policy Fellowships 2025, funded by the Economic and Social Research Council, offer 18-month placements for academics to co-design research with UK government and What Works Network host organizations. Awards range from £180,000 to £280,000 and support three fellowship tracks: core policy fellows, Natural Hazards and Resilience policy fellows, and What Works Innovation fellows. Applicants must hold a PhD or equivalent research experience, be based at a UKRI-eligible UK organization, and possess relevant subject matter or methodological expertise. Government-hosted positions target early to mid-career academics, while What Works fellowships welcome all career stages. Fellows work directly with policymakers to bridge academic research and policy development on pressing national and global challenges. The application deadline is July 15, 2025.
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