NSF award 2601665 · William Marsh Rice University

Collaborative Research: MFAI: Mathematical Foundations of Structure-Aware Adaptive Machine Learning Algorithms

Final report due

28 February 2027

in 133 days · The award ends on 31 October 2026.

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No-cost extension notice21 Oct 2026in 3 days
award ending 2026-10-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Feb 2027in 133 days
award ending 2026-10-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Feb 2027in 133 days
award ending 2026-10-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Feb 2027in 133 days
award ending 2026-10-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 October 2026.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 February 2027.

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Award card

Award number: 2601665
Period of support: 1 Oct 2026 – 31 Oct 2026
Amount: $500,000
Awardee: William Marsh Rice University, Houston, TX
Program: Special Projects - CCF, MSPA-INTERDISCIPLINARY
Directorate: MPS

Abstract

Recent years have witnessed rapid progress in computational algorithms for large-scale machine learning, but many advances remain segmented and disconnected. This project develops a unified mathematical framework for modern machine learning algorithms with emphasis on scalability, adaptivity, and structure-aware optimization and generalization. This framework will deepen understanding of the limitations of current…

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