NSF award 2621883 · University of Illinois at Chicago

Collaborative Research: CDS&E: Adaptive Uncertainty-Driven AI for Drug Discovery: A Conformal Prediction-Simulation Loop Approach

Final report due

28 November 2029

in 1,137 days · The award ends on 31 July 2029.

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Decide about an extension2 Apr 2029in 897 days
award ending 2029-07-31 · Research.gov
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Extension request16 Jun 2029in 972 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2029in 1007 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2029in 1137 days
award ending 2029-07-31 · 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 July 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2029.

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Award card

Award number: 2621883
Period of support: 1 Aug 2026 – 31 Jul 2029
Amount: $304,067
Awardee: University of Illinois at Chicago, Chicago, IL
Program: Chem Thry, Mdls & Cmptnl Mthds
Directorate: MPS

Abstract

Yihang Wang of Case Western Reserve University, and collaborator Lu Cheng of the University of Illinois Chicago, are supported to develop artificial-intelligence (AI) methods that quantify their own uncertainty and refine themselves through molecular simulation for more reliable computational drug discovery. The discovery of new medicines depends on accurately predicting how candidate molecules bind to the proteins…

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