NSF award 2502259 · Columbia University

Collaborative Research: MFAI: Emergence of features in modern machine learning

Final report due

28 January 2029

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

GrantClerk is a private service. We are not NSF or any government agency.

Dates this award owes

NSF emails you about this too.

Decide about an extension2 Jun 2028in 593 days
award ending 2028-09-30 · Research.gov
This one is ours, not NSF’s.
Extension request16 Aug 2028in 668 days
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”

Annual report dates come from the budget period on your award notice. That date is not public, so it is not shown here.

How we got this date

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.

Read the rule on Research.gov

Get a note before each report date

Add this award to your desk. We email you before each date and keep the dates in one place.

Renews each year until you cancel. Cancel any time from your account.

Already a member? Sign in

Award card

Award number: 2502259
Period of support: 1 Oct 2025 – 30 Sep 2028
Amount: $475,000
Awardee: Columbia University, NEW York, NY
Program: EPCL: Energy, Power, Control,, MSPA-INTERDISCIPLINARY, Special Projects - CCF
Directorate: MPS

Abstract

The goal of this research project is to build mathematical foundations for reasoning about the behavior of modern machine learning systems. Foundations are needed to direct future developments in Artificial Intelligence (AI) research, and also to diagnose and remedy problems that arise in existing AI systems. This project specifically focuses on how AI models represent data. For example, many language models are…

Is this right?

We copy this from the public NSF award record. Your award notice and NSF always win. If a date looks wrong, check Research.gov.