The study explores the risks and tradeoffs when adapting enterprise-IT security and zero trust principles to weapon systems.

In this webcast, Eileen Wrubel and Brigid O’Hearn discuss the launch of the Software Acquisition Go Bag. Our SEI team has helped hundreds of DoD programs deliver software-enabled capability through ...

At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice. We have been ...

The individuals listed below have earned an SEI certificate and requested that the SEI include their information on this list. You can earn an SEI certificate by completing a set curriculum in a ...

Shevchenko, N., 2020: An Introduction to Model-Based Systems Engineering (MBSE). Carnegie Mellon University, Software Engineering Institute's Insights (blog ...

Heim, E., and Frank, C., 2025: Out of Distribution Detection: Knowing When AI Doesn't Know. Carnegie Mellon University, Software Engineering Institute's Insights ...

Leaders in defense and national security want to obtain the leap-ahead capabilities AI offers. At the same time, it is difficult to get AI right. As many as 85% of current AI deployments fail—failures ...

ER 2024 was held in Pittsburgh, Pennsylvania, United States, hosted by Carnegie Mellon University’s Software Engineering Institute on October 28-31, 2024. ER 2024 was the main international forum for ...

The Software Engineering Institute (SEI) at Carnegie Mellon University is a Federally Funded Research and Development Center (FFRDC)—a nonprofit, public–private partnership that conducts research for ...

Konrad, M., Testa, N., Gates, L., Nolan, C., Shepard, D., Cohen, J., Mellinger, A., Miller, S., and Ludwick, M., 2024: Measuring AI Accuracy with the AI Robustness ...

This free event, hosted by Carnegie Mellon University’s Software Engineering Institute, gives you the opportunity to elevate how you integrate security into your DevOps practices and transform your ...

Scherlis, B., 2024: Weaknesses and Vulnerabilities in Modern AI: AI Risk, Cyber Risk, and Planning for Test and Evaluation. Carnegie Mellon University, Software ...