Software Engineering Institute (SEI) Webcast Series

SEI Members of Technical Staff
  • 5.0 (1)
  • Technology
  • Monthly

Each webinar features an SEI researcher discussing their research on software and cybersecurity problems of considerable complexity. The webinar series is a way for the SEI to accomplish its core purpose of improving the state-of-the-art in software engineering and cybersecurity and transitioning this work to the community. The SEI is a federally funded research and development center sponsored by the U.S. Department of Defense and operated by Carnegie Mellon University. The SEI Webinar Series is produced by SEI Communications Outreach.

  1. 6h ago ·  Video

    Beyond the AI Pilot: Is Your Agency Ready to Scale AI?

    Like their industry counterparts, government organizations, military services, and federal agencies are launching artificial intelligence (AI) pilots, testing generative AI, and exploring new ways to advance mission delivery. Yet moving from isolated experiments to enterprise-wide adoption requires far more than promising technology. It demands strong governance, trusted data, a prepared workforce, an adaptable infrastructure, effective risk management, clear measures of value, and aligned resource management. Drawing on deep policy and defense expertise from the U.S. Government Accountability Office (GAO) alongside technical leaders from the Carnegie Mellon University (CMU) Software Engineering Institute (SEI), the panel will examine what it takes for services and federal agencies to progress from experimentation to the sustainable implementation of AI. Attendees will learn how to manage the security and trust risks that accompany the deployment of AI platforms using structured, enterprise-level governance. The discussion will explore how government organizations can assess their current level of readiness, identify gaps that may limit adoption, and align AI investments with mission outcomes, oversight expectations, and public trust. The panelists will explore actionable strategies to overcome legacy challenges, safely scale emerging technologies, and manage security, trust, and operational risk across critical public and defense sector mission environments. Participants will gain practical insights into the capabilities that distinguish mature AI adoption, the challenges government organizations are encountering, and the steps leaders can take now to build a foundation for intentional scale. Attendees will learn how to move beyond AI-washing by replacing vague, "AI everywhere" mindsets with clearly defined strategies drive AI enterprise gains with end-to-end workflows assess infrastructure costs and resource allocation to prioritize AI investment

    Beyond the AI Pilot: Is Your Agency Ready to Scale AI?

  2. Sep 24 ·  Video

    World Building: How 3D Gaussian Splatting is Transforming Digital Twins

    Software Engineering Institute (SEI) Webcast Series

    World Building: How 3D Gaussian Splatting is Transforming Digital Twins

  3. Sep 10 ·  Video

    The Key to Software Acquisition Pathway Success—the User Agreement

    Collaboration among the Program Management Office, the Product Team, and Users is paramount to the success of software acquisition. In this webcast, software acquisition experts at Software Engineering Institute (SEI) discuss the User Agreement (UA), a key document for programs on the Software Acquisition Pathway (SWP), which is the cornerstone of that collaboration.  Even if you are not using the SWP, if you are using Agile development methods, it's a good idea to consider developing and adopting a UA to get commitment from Users to participate throughout the software development lifecycle. Attendees will learn      Who should be involved in user agreement development?      What types of information should be included in the user agreement?       How to develop a user agreement that specifies the level of user representation needed during the software development lifecycle.

    The Key to Software Acquisition Pathway Success—the User Agreement

  4. Aug 27 ·  Video

    Intro to the SEI CERT Coding Standard for Fortran

    Fortran is one of the oldest high-level programming languages still in active use and remains a cornerstone of scientific, engineering, and high-performance computing (HPC) software in critical applications areas, such as climate and weather prediction, aerospace, nuclear energy, computational physics, and national security. Fortran provides several features that are particularly well-suited for scientific and high-performance computing, including intrinsic multidimensional array operations, native array slicing and whole-array syntax, built-in support for numerical computation, explicit parallel programming constructs, and language-level facilities for efficient vectorization and mathematical optimization. Recently, the Fortran community has shown growing interest in secure software development practices, vulnerability prevention, and secure coding standards. The SEI CERT Coding Standard for Fortran leverages expertise in secure coding practices and provides well-documented and enforceable coding guidelines to audit Fortran software. Attendees will learn how to       identify common security risks in Fortran      navigate the SEI CERT Coding Standard for Fortran        leverage Fortran safety features for secure coding         improve software quality through secure coding practices

    Intro to the SEI CERT Coding Standard for Fortran

  5. Jun 10 ·  Video

    Rethinking and Maturing AI Adoption

    Many organizations are discovering, as they accelerate adoption of artificial intelligence (AI), that business and operational success with AI depends on far more than deploying AI models or experimenting with generative AI tools. Successful AI adoption occurs at the intersection of software engineering practices, the realities of system and enterprise architecture modernization, governance, cybersecurity, workforce readiness, workflow reengineering, operational integration, and enterprise strategy. Organizations must manage technological challenges that have intensified with AI adoption, including growing dependencies, vendor lock-in, and the imperative to innovate and scale quickly. Leaders must also adapt to new emerging realities, from the operational and financial demands of supporting multiple frontier models to the novel security and governance risks introduced by agentic AI approaches. Traditional approaches to technology transformation are no longer sufficient to thrive in this environment. To address these emerging complexities and drive success, Carnegie Mellon University's Software Engineering Institute (SEI) collaborated with Accenture to develop the AI Adoption Maturity Model—an evidence-backed, field-tested instrument that provides a structured, yet agile, pathway for scaling AI capabilities across enterprises to ensure value and return on investment (ROI). This approach is designed for today's realities, including fast-paced technological change, limited time and resources, and the need for lightweight, actionable methods rather than burdensome documentation.  In this webcast, experts from the SEI and Accenture share technical insights and lessons learned from maturing AI adoption in complex environments. They will demonstrate how a nimble assessment instrument such as the road-tested AI Adoption Maturity Model fills critical gaps faced by organizations adopting AI.  What Will Attendees Learn? • How AI maturity extends beyond isolated experimentation to encompass scalable, repeatable, measurable, and governed organizational capabilities. • How common pitfalls and strengths that we observed in early adopter organizations during AI Adoption Maturity Assessments can influence AI adoption. • How certain approaches to integrating existing risk management routines and security processes can support AI adoption. • How an agile, lightweight maturity assessment approach can enable organizations to rapidly prioritize activities, align efforts, and make targeted progress.

    Rethinking and Maturing AI Adoption

  6. May 22 ·  Video

    AI-Native Software Engineering: Enduring Principles, New Pace

    AI is rapidly changing how software is produced but not the need to engineer software to meet business and mission goals. AI is enabling developers to move from idea to implementation at incredible speeds. However, this fast pace has implications that teams must manage. Product quality does not come for free, and there is some tendency for AI to accelerate the accumulation of technical debt. In addition, what works well on small code bases doesn't always work as well on large code bases. So, what's a good software engineer to do? Software engineering principles and practices are essential in guiding software engineers to use AI to achieve production-ready outcomes. In this webcast, experienced software engineers discuss their observations and lessons from applying AI-native software engineering and studying its use across multiple projects. What Will Attendees Learn? • Distinguish between "vibe coding" and software engineering • Understand how software engineering principles improve the use of AI and where these principles need to be adapted to be used with AI • Recognize the different criteria that can be used to assess the benefits of AI-native software engineering (e.g., productivity and software quality) and their potential tradeoffs

    AI-Native Software Engineering: Enduring Principles, New Pace

  7. May 19 ·  Video

    Software Acquisition Go Bag: Pack Light, Measure Right

    Metrics are about more than just compliance. They ground you in fact, enable informed decision making, and help your team understand performance while providing insight into program health. By understanding the why, what, and how behind metrics, your team can move from "just collecting data" to using metrics that enable better decision making, improve program outcomes, and deliver mission value. Get ready to hear all about our new Tactical Guide called Pack Light, Measure Right and Supplement called Decoding SWP Metrics. What Will Attendees Learn? • How to select a minimal but sufficient set of measures to get the insight you need • How to implement measurement approaches that are compatible with iterative delivery • The hidden value in the metrics that you're already collecting if you are on the Software Acquisition Pathway

  8. Apr 29 ·  Video

    When Performance Isn't Enough: Ensuring the Safety and Security of AI Systems

    Artificial intelligence (AI) systems offer tremendous potential, but compared to traditional software, they introduce novel safety and security risks. System theory provides a powerful lens for understanding these risks and developing effective mitigations. In this webcast, we'll introduce System Theoretic Process Analysis (STPA), a system-theory-based approach to safety analysis. We'll explain how STPA helps organizations build stronger assurances about the safety and security of complex systems, including those that incorporate AI. What Will Attendees Learn? • How complex systems fail due to design flaws and unsafe interactions—not just component failures • How these types of accidents can occur in AI-enabled systems • How to apply a system-theoretic perspective, including System Theoretic Process Analysis (STPA), to analyzing AI systems • Practical insights into improving the design, testing, and operational use of AI systems to strengthen safety and security

    When Performance Isn't Enough: Ensuring the Safety and Security of AI Systems
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About

Each webinar features an SEI researcher discussing their research on software and cybersecurity problems of considerable complexity. The webinar series is a way for the SEI to accomplish its core purpose of improving the state-of-the-art in software engineering and cybersecurity and transitioning this work to the community. The SEI is a federally funded research and development center sponsored by the U.S. Department of Defense and operated by Carnegie Mellon University. The SEI Webinar Series is produced by SEI Communications Outreach.

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