NSF award 2541747 · University of California-Los Angeles

CAREER: Theory and Methods for Nonparametric Estimation with Neural Networks

Final report due

28 October 2031

in 1,836 days · The award ends on 30 June 2031.

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Decide about an extension2 Mar 2031in 1596 days
award ending 2031-06-30 · Research.gov
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Extension request16 May 2031in 1671 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Jun 2031in 1706 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Oct 2031in 1836 days
award ending 2031-06-30 · 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 June 2031.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 October 2031.

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Award card

Award number: 2541747
Period of support: 1 Jul 2026 – 30 Jun 2031
Amount: $450,000
Awardee: University of California-Los Angeles, LOS Angeles, CA
Program: STATISTICS
Directorate: MPS

Abstract

Modern science, industry, and public decision-making increasingly depend on the ability to learn from large, complex data. Neural networks are now widely used to support decisions in areas such as health care, scientific discovery, finance, engineering, and language technologies. These tools can be powerful, but their predictions are often difficult to understand, and it is not always clear when they can be trusted.…

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