NSF award 2515927 · Washington University

Collaborative Research: Online Statistical Inference for Modern Machine Learning

Final report due

28 January 2029

in 833 days · The award ends on 30 September 2028.

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award ending 2028-09-30 · Research.gov
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award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2028in 703 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2029in 833 days
award ending 2028-09-30 · 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 30 September 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2029.

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Award card

Award number: 2515927
Period of support: 1 Oct 2025 – 30 Sep 2028
Amount: $99,322
Awardee: Washington University, Saint Louis, MO
Program: STATISTICS
Directorate: MPS

Abstract

This research aims to develop statistical tools to improve the reliability of artificial intelligence (AI) that is widely used in real-world systems such as automated decision-making, financial forecasting, and neuroscience research. Modern AI often relies on efficient machine learning algorithms to process large-scale, sequentially arriving datasets. While these algorithms are powerful, understanding their behavior…

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