Project Grant 2533367
- Federal Grant Award Summary The College of William & Mary received a $500,000 Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering program (CFDA 47.070), awarded August 1, 2026, with completion targeted for July 31, 2028. This award funds the development of next-generation metadata management infrastructure to enable intelligent, artificial intelligence (AI)-ready scientific data discovery at...
- Federal Grant Award Summary The College of William & Mary received a $174,983 Computer and Information Science and Engineering (CISE) Project Grant (CFDA 47.070) from the National Science Foundation's Division of Information and Intelligent Systems, awarded August 1, 2025, with completion targeted for July 31, 2027. This Computer Research Initiation (CRII) award supports the development of novel methodologies for measuring and controlling memorization in text-attributed graphs (TAGs)—data...
- The National Science Foundation (NSF) awarded a $329,183 Project Grant to the College of William & Mary under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, awarded on October 1, 2023, will fund the development of a framework and methodology to enable researchers and software engineers to better interpret the behavior of AI-powered developer tools that leverage neural language models for source code. The project aims to generate global and local...
- Federal Grant Award Summary The College of William & Mary received a $661,478 Project Grant from the National Science Foundation's Division of Research on Learning in Formal and Informal Settings under the STEM Education program (CFDA 47.076), awarded September 1, 2025, with a completion date of August 31, 2028. The award funds the design, development, and evaluation of StoryBridge, a web-based intergenerational digital-storytelling platform that enables older adults and youth to...
- Federal Grant Award Summary The College of William & Mary received a $241,414 Project Grant from the National Science Foundation's Division of Research on Learning in Formal and Informal Settings under the STEM Education program (CFDA 47.076), awarded September 15, 2025, with completion targeted for August 31, 2028. This collaborative research initiative will develop an augmented reality (AR) learning environment integrated with a large language model (LLM)-powered pedagogical agent designed...
- Federal Grant Award Summary The College of William & Mary received a $499,928 CAREER (Collaborative Research: EArly-concept Grants for Exploratory Research) award from the National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) to develop graph learning (GL) algorithms and educational resources for dynamic systems. The project, which runs from July 15, 2026 through June 30, 2031, focuses on creating new GL methods that can explain and forecast...
- Federal Project Grant Award Summary The University of Virginia received a $900,000 Project Grant award from the National Science Foundation (NSF) Office of Integrative Activities under the Integrative Activities program (CFDA 47.083), effective January 1, 2026 through December 31, 2028. The project, titled "CICI: IPAAI: Multi-Layer Data Provenance and Federated Learning for Securing Scientific AI Pipelines," delivers infrastructure and tools to enhance the trustworthiness and...
- This $139,660 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research at the College of William and Mary to develop novel online data mining algorithms that can provide transparent and interpretable machine learning models for real-time applications such as crowd movement prediction, disaster monitoring, and pandemic response. Key objectives include: 1)...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a $180,000 Project Grant to Trustees of Tufts College beginning October 1, 2025, and concluding September 30, 2027, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This collaborative research initiative addresses intellectual property protection challenges arising from the use of generative artificial intelligence (AI) in...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computer and Network Systems awarded the University of Maryland, College Park a Project Grant of $331,428 (CFDA 47.070 – Computer and Information Science and Engineering) commencing October 1, 2025, with a completion date of September 30, 2030. This CAREER award supports research focused on secure code generation with large language models (Code LLMs), addressing critical security vulnerabilities in AI-driven...
The College of William & Mary received a $599,959 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) for the period July 1, 2026 through June 30, 2029. The grant funds research and development of automated and explainable provenance techniques for artificial intelligence (AI)-generated code. The project addresses critical risks associated with AI code generation—including licensing violations, copyright infringement, security vulnerabilities, and code quality issues—by developing novel methods to trace code origins across complex AI pipelines and making AI-generated outputs more transparent and auditable. The deliverables encompass two integrated components: an empirical research component conducting surveys and interviews with developers, AI model users, and compliance practitioners to establish taxonomies of provenance practices, challenges, and stakeholder requirements; and a technical component developing automated methods for tracing and explaining AI code provenance. The project will produce foundational knowledge applicable to responsible AI adoption in software development, deliver explainable techniques for code origin verification, and integrate provenance concepts and practices into computer science curricula. These outputs will equip stakeholders with tools to evaluate AI-generated code and make informed decisions regarding its use and integration while mitigating software licensing, security, and quality risks.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 6/30/26 |