Description

This opportunity from the National Science Foundation (NSF) funds collaborative, interdisciplinary research on the mathematical and theoretical underpinnings of artificial intelligence (AI) and machine learning (ML). The program seeks to address foundational gaps that limit advances in AI, emphasizing the need for rigorous mathematical frameworks to explain, validate, and design AI systems. Supported projects should foster collaborations among mathematicians, statisticians, computer scientists, engineers, and social/behavioral scientists, with a focus on innovative, principled approaches that advance the theory and reliability of current and next-generation AI.

Research areas of interest include, but are not limited to:

• Fundamental mathematical understanding of AI capabilities and limitations (e.g., foundation models, generative models, deep learning, federated learning)
• Development of mathematically grounded design and analysis principles
• Rigorous validation and characterization of AI algorithms and their predictions
• Approaches enabling provably reliable, general-purpose AI systems
• Promotion of new interdisciplinary collaborations and workforce development

Projects should clearly articulate the mathematical and theoretical advances, the technical challenges addressed, and the collaborative contributions of the team.