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Mathematical Foundations of Artificial Intelligence

U.S. National Science Foundation

24-569

NSF

General Information

$8,500,000

Est. Program Funding:

October 10, 2024

Closing Date:

N/a

Expected No. of Awards

$1,500,000

Award Ceiling

Opportunity Number:
24-569

Owning Agency:
NSF

Opportunity Category:
Discretionary (D)

Synopsis

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 thefactors determining the capabilities and limitations of current and emerging generations 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; encouragement of new collaborations in this interdisciplinary research community and between institutions. 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.
Response Date	Oct 09, 2026 12:00:00 AM EDT
Posting Date	May 02, 2024 12:00:00 AM EDT
Archive Date	Nov 08, 2026 12:00:00 AM EST
Award Ceiling	1,500,000
Award Floor	500,000
Cost Sharing	No

Eligibility

Eligible Applicants

Others (see text field entitled "Additional Information on Eligibility" for clarification)

Additional Info on Eligibility:

*Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities. - Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. *Who May Serve as PI: <div class="OutlineElement Ltr SCXW177155816 BCX0"> As of the date the proposal is submitted, any PI, co-PI, or senior/key personnel must hold either: <ul> <li>a tenured or tenure-track position, or</li> <li>a primary, full-time, paid appointment in a research or teaching position</li> </ul> at a US-based campus of an organization eligible to submit to this solicitation (see above), with exceptions granted for family or medical leave, as determined by the submitting organization. Individuals with primary appointments at for-profit non-academic organizations or at overseas branch campuses of U.S. institutions of higher education are not eligible.</div>

Additional Information

Agency Name	U.S. National Science Foundation
Link to Additional Information:	NSF Publication 24-569
Grantor Contact Information:	If you have difficulty accessing the full announcement electronically, please contact: GrantSolutions Help Desk Phone: 703-292-4203

CFDA Program(s)

47.041: Engineering
47.049: Mathematical and Physical Sciences
47.070: Computer and Information Science and Engineering
47.075: Social, Behavioral, and Economic Sciences

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