Project Grant 2622986
- The National Science Foundation Division of Graduate Education awarded Virginia Commonwealth University $250,000 on September 1, 2026, under the STEM Education program (CFDA 47.076) to develop curriculum and instructional materials preparing undergraduate computing students to use artificial intelligence coding tools securely and responsibly. The project will deliver a threat modeling framework for AI-assisted coding workflows and at least eight hands-on laboratory modules built around realistic...
- The National Science Foundation Division of Undergraduate Education awarded George Mason University $166,666 on September 1, 2026, under the STEM Education program (CFDA 47.076) to develop a modular, hands-on curriculum and low-barrier web-based learning platform for cybersecurity competence in agentic artificial intelligence systems. The curriculum addresses security risks introduced by autonomous AI systems deployed across government agencies, critical infrastructure, and private industry by...
- Arizona State University received a $300,000 project grant award from the National Science Foundation on May 1, 2021 to develop artificial intelligence tools and resources for cybersecurity education. The funding supports the EAGER: SATC-EDU project to create a machine learning-enabled security knowledge graph for integrating AI into cybersecurity curriculum from April 30, 2023. The grant falls under the National Science Foundation's STEM Education program (CFDA 47.076), which aims to strengthen...
- The National Science Foundation Division of Graduate Education awarded Clemson University $250,000 on September 1, 2026, for collaborative research under the STEM Education program (CFDA 47.076) to develop an AI agent-centered cybersecurity education framework. The project, running through August 31, 2029, will create curriculum modules, hands-on laboratories, and project-based learning activities that train students to understand both the benefits and security challenges of artificial...
- The National Science Foundation Division of Graduate Education awarded $500,000 to the University of Southern California on September 1, 2026, to develop instructional resources and graduate-level curriculum for agentic cybersecurity engineering under the STEM Education program (CFDA 47.076). The project, titled "Agentic Cybersecurity Engineering for Artificial Intelligence" (ACE), addresses the shortage of cybersecurity professionals qualified to design, deploy, and secure AI agents...
- The National Science Foundation Division of Graduate Education awarded Auburn University $299,978 on July 1, 2026, under the STEM Education program (CFDA 47.076) to develop and evaluate a modular curriculum framework for cybersecurity and artificial intelligence education. Auburn will design, prototype, and evaluate instructional materials addressing AI-native cyber threat environments and agentic AI concepts within cybersecurity instruction. The project scope includes developing reusable...
- The National Science Foundation Division of Graduate Education awarded the University of Central Florida Board of Trustees $500,000 on August 1, 2026, to develop and deploy an adaptive intelligent tutoring system that trains cybersecurity professionals to recognize and resist artificial intelligence-enabled threats through metacognitive calibration training under the STEM Education program (CFDA 47.076). The project develops a three-agent architecture with an adversary agent that generates...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant of $299,486 awarded to George Mason University (Mason) aims to develop a curriculum that helps future cybersecurity professionals adopt an ethical and responsible mindset when working with AI-enabled technologies. The project will create a series of four case studies highlighting social and ethical risks associated with AI systems used for security-related applications, such as...
- The National Science Foundation Division of Graduate Education awarded George Mason University $500,000 on September 1, 2026, under the STEM Education program (CFDA 47.076) to modernize cybersecurity education and develop student-centered learning experiences focused on deploying, optimizing, and securing foundation models on internet-of-things and edge computing platforms in the embodied AI era. The recipient will develop cutting-edge curricula and learning materials addressing cybersecurity...
- The National Science Foundation Division of Graduate Education awarded a $146,000 project grant to Clemson University to support the development of a learning platform and education curriculum for artificial intelligence-driven socially-relevant cybersecurity. The two-year award, made under the STEM Education program (CFDA 47.076), will fund Clemson University's collaborative research project titled "EAGER: SATC-EDU: Learning Platform and Education Curriculum for Artificial...
The National Science Foundation Division of Graduate Education awarded $500,000 to the University of Virginia on August 1, 2026, under the STEM Education program (CFDA 47.076) to develop and deliver instructional materials and assessment methods for adversarial causal reasoning in cybersecurity and artificial intelligence. The project creates course materials, a hands-on practice system, instructor support resources, and measurement tools to teach cybersecurity professionals how to evaluate the reliability of AI-generated recommendations for cyberattack detection and response. The curriculum centers on a foundational skill: tracing the logical steps behind an AI tool's answer and judging whether each step can be trusted, enabling defenders to recognize when attackers have fed false information to or manipulated AI systems. The project also aims to strengthen educational pathways into cybersecurity and AI careers in government and critical infrastructure sectors. Work will be performed in Charlottesville, Virginia, over a three-year period ending July 31, 2029. The project addresses whether adversarial causal reasoning can be taught through structured instruction, reliably measured, and optimized through instructional design choices. Materials and tools developed will be freely shared to support the national interest in protecting critical infrastructure and government systems against advanced attacks.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $500.0k | 8/1/26 |