Skip to the ledger

GrantClerk

NSF award 2511507 · Rochester Institute of Tech

A Foundational Model for Extragalactic Spectroscopy: Combining Transformer-Based Deep Learning and Citizen Science

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

  • Extension request16 Aug 2028in 668 days

    award ending 2028-09-30 · Research.gov

  • No-cost extension notice20 Sep 2028in 703 days

    award ending 2028-09-30 · Research.gov

  • Final report due28 Jan 2029in 833 days

    award ending 2028-09-30 · Research.gov

  • Project outcomes report due28 Jan 2029in 833 days

    award ending 2028-09-30 · Research.gov

  • Award is closed out28 Jan 2029in 833 days

    award ending 2028-09-30 · Research.gov

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

  1. NSF lists this award's end date as 30 September 2028.
  2. NSF rules say the final report is due no later than 120 days after that.
  3. 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
2511507
Period of support
1 Oct 2025 – 30 Sep 2028
Amount
$394,869
Awardee
Rochester Institute of Tech, Rochester, NY
Program
OFFICE OF MULTIDISCIPLINARY AC, EXTRAGALACTIC ASTRON & COSMOLO
Directorate
MPS

Abstract

Spectroscopic observations of galaxies contain critical information about their physical properties, and modern large spectroscopic surveys of galaxies are producing a plethora of data. Given the size of these datasets, traditional data analysis methods are prohibitively time consuming. The Principal Investigator (PI) will develop an artificial intelligence (AI) model called Spectroscopy Pre-trained Transformer…

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.