The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of South Carolina. The grant, with a period of performance from October 1, 2024 to September 30, 2027, focuses on enhancing security and mitigating harm in AI-generated vision language models. Key technical objectives include: 1) Developing a prompting framework for detecting harmful content provenance in AI-generated vision...
This $600,000 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The project aims to advance the fundamental research on detecting AI-generated fake images by focusing on understanding the generalization capabilities of fake image detectors. Specifically, the project will investigate two main thrusts: (1) understanding the characteristics that make AI-generated images fake, including the role of...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $309,407 to Virginia Polytechnic Institute & State University (Virginia Tech) to develop a framework for ensuring the safety and trustworthy deployment of generative artificial intelligence (AI) foundation models, particularly large language models. The project will pursue three key tasks: 1) Conduct in-depth analysis to identify root...
This $400,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The project aims to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models, in order to increase the accountable and safe use of these advanced AI systems and mitigate potential harms. The key research thrusts involve: 1) new...
This Project Grant award from the National Science Foundation (NSF) under CFDA 47.070 - Computer and Information Science and Engineering is for $395,927 over the period of Sep 1, 2024 to Aug 31, 2027. The award aims to develop theoretical and algorithmic foundations for building a safe and robust human-AI ecosystem, where machine learning (ML) and artificial intelligence (AI) techniques are used in applications involving humans, such as recommendation systems, lending, and healthcare. The key...
This $400,000 project grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models. The key objectives are to: 1) create new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2) explore model...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to New York University (NYU) to investigate the risks of AI-generated code in the software supply chain. The 3-year project, which began on June 1, 2024, aims to: (i) develop techniques to distinguish human-written code from AI-generated code, (ii) measure the prevalence and security implications of AI-generated code in open-source software, and (iii)...
This $100,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the planning and development of a proposal to study the risks and benefits of generative AI-based systems for security and privacy. The University of Kansas Center for Research Inc., a non-profit subsidiary of the University of Kansas, will lead this planning effort. The goal is to create a fully realized proposal that addresses...
This $660,000 Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports the development of advanced multi-stream deep learning architectures and efficient implementations for cybersecurity and data analytics applications. The project aims to: (1) create a suite of high-performance multi-stream foundation models for tasks like object detection, text-based image segmentation, and audio-video...
This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $826,361 to Georgetown University to conduct research that develops novel approaches to support Public Interest Technology (PIT) organizations in deploying data safeguards to build ethical and responsible AI systems. The project will: (1) use ethnographic methods to identify socio-technical challenges at PIT organizations, (2) create and evaluate participatory...