NSF award 2529883 · Pennsylvania State Univ University Park

SHF: Small: Practical Privacy-preserving AI Offloading with Hybridizing Multi-party Computing and Strongly-secure Hardware

Final report due

28 February 2029

in 864 days · The award ends on 31 October 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 extension3 Jul 2028in 624 days
award ending 2028-10-31 · Research.gov
This one is ours, not NSF’s.
Extension request16 Sep 2028in 699 days
award ending 2028-10-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Oct 2028in 734 days
award ending 2028-10-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Feb 2029in 864 days
award ending 2028-10-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Feb 2029in 864 days
award ending 2028-10-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Feb 2029in 864 days
award ending 2028-10-31 · 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 31 October 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 February 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: 2529883
Period of support: 1 Nov 2025 – 31 Oct 2028
Amount: $600,000
Awardee: Pennsylvania State Univ University Park, University Park, PA
Program: Software & Hardware Foundation
Directorate: CSE

Abstract

When users interact with modern artificial intelligence (AI) services, they often transmit their data to the service provider. For example, individuals seeking to enhance their resumes using tools like ChatGPT must upload their resumes to the service. Those using AI-powered health monitoring devices send their biomedical signals to the provider's AI model. These interactions pose significant privacy risks, as the…

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.