Project Grant 2429837

Award Date 10/1/24
Completion Date 9/30/27
Dollars Obligated $150K
Awarding Federal Agency
National Science Foundation
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
University, MS 38677, USA
Similar Awards
This $350,000 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant awarded to the Rochester Institute of Technology (RIT) aims to develop a user-centered platform for detecting and mitigating the impact of AI-generated deepfakes. The project seeks to protect the integrity of digital content and maintain public trust as advances in generative AI have made it easier to create and manipulate digital media. RIT, leveraging its expertise in...
This Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) provides $225,000 to Michigan State University (MSU) to develop a user-centered platform for protecting the integrity of digital content and maintaining public trust. The project aims to address the risks posed by the rapid advancement of generative AI, which has made it easier to create and manipulate digital content, by integrating multiple...
This $400,000 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program aims to advance digital forensics capabilities for analyzing artificial intelligence (AI) systems. The key products and services to be delivered under this 2-year project include: Developing and deploying forensic tools to reconstruct HDF5 machine learning model files, with evaluation of their precision in data recovery using benchmark performance...
This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program totaling $491,955 will fund research to develop a self-learning and self-evolving system for detecting altered and deceptive images and videos. The goal is to design an intelligent detector capable of assessing digital visual content integrity and automatically identifying falsified images or videos in real time to prevent their spread. The award to Vanderbilt University from...
This $749,623 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of a prototype community infrastructure called CISAAD (Community Infrastructure for Advancing Audio Deepfake Detection). The project aims to address challenges around limited data availability and human augmented data for audio deepfake analysis by creating open datasets, enabling both single and multi-speaker...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award to Georgetown University totals $826,361 over a 3-year period from October 1, 2024 to September 30, 2027. The project, titled "COLLABORATIVE RESEARCH: REDDDOT PHASE 2: ENABLING PARTICIPATORY PRIVACY PROTECTIONS FOR AI TRAINING DATA", aims to develop novel methods and best practices for navigating the tradeoffs between data privacy protection and model usefulness for...
This $300,000 Project Grant awarded by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) will fund a 2-year research initiative titled "REDDDOT PHASE 1: PLANNING GRANT - BRIDGING PAST AND FUTURE: FOSTERING COMMUNITY-RESEARCHER SYNERGY THROUGH PLANNING." The project aims to design, develop, and responsibly deploy artificial intelligence (AI) technologies by engaging with community members as experts to incorporate...
This $100,000 Project Grant award is funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award supports a research project at the University of Oklahoma's Office of Research Administration that aims to expand on earlier work by the research team to identify, measure, and address multiple ways that artificial intelligence (AI) could be inadvertently misused within environmental and Earth sciences...
This $435,594 federal Project Grant award was provided by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program. The funding supports a collaborative research project titled "REDDDOT PHASE 2: ENABLING PARTICIPATORY PRIVACY PROTECTIONS FOR AI TRAINING DATA" at Columbia University. The project aims to develop novel approaches for public interest technology (PIT) organizations to deploy data safeguards, including techniques like...
This $125,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) aims to develop and improve automated techniques for identifying fraudulent online accounts and narratives. The key products and services to be delivered under this 2-year grant include: Developing robust AI methods to detect narratives associated with previously identified inauthentic online accounts, leveraging advances in large...

This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is for $150,000 over a 3-year period from October 1, 2024 to September 30, 2027. The project, titled "COLLABORATIVE RESEARCH: REDDDOT PHASE 2: A USER-CENTERED PLATFORM FOR DIGITAL CONTENT INTEGRITY," aims to develop an integrated digital content forensics platform to protect the integrity of digital content and maintain public trust in the face of emerging AI-enabled deepfake technologies. The University of Mississippi is the sole awardee and will not be issuing any subawards. The platform will streamline the process of detecting AI-generated content by integrating multiple tools into a single user-friendly interface. The project employs a user-centered design approach, involving qualitative user research and studies to understand user needs and workflows. It will also create novel game-based training scenarios and ethical frameworks to assist users in effectively leveraging the platform. The goal is to empower diverse user communities to maintain the integrity of online digital content.

Generated 4/8/25, 2:55 AM