NSF award 2530788 · University of Texas at Dallas

Collaborative Research: CAIG: Multi-Task and Multi-Scale Deep Learning Inversion for Geophysical Imaging and Monitoring

Final report due

30 April 2029

in 925 days · The award ends on 31 December 2028.

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Decide about an extension2 Sep 2028in 685 days
award ending 2028-12-31 · Research.gov
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Extension request16 Nov 2028in 760 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Dec 2028in 795 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due30 Apr 2029in 925 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due30 Apr 2029in 925 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out30 Apr 2029in 925 days
award ending 2028-12-31 · 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 December 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 30 April 2029.

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Award card

Award number: 2530788
Period of support: 1 Jan 2026 – 31 Dec 2028
Amount: $193,567
Awardee: University of Texas at Dallas, Richardson, TX
Program: GEO CI - GEO Cyberinfrastrctre
Directorate: GEO

Abstract

Understanding the Earth’s subsurface is essential for society’s ability to monitor natural hazards, manage environmental risks, and support sustainable energy development. Seismic waves generated by earthquakes and other sources can provide clues about underground structures, but interpreting these waves remains complex and computationally intensive. This project will advance artificial intelligence (AI) methods for…

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