Software Engineering Institute (SEI) Podcast Series

Latest Episodes:

Grace Lewis Outlines Vision for IEEE Computer Society Presidency Mar 11, 2025

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Grace Lewis, a principal researcher at the Carnegie Mellon University Software Engineering Institute (SEI) and lead of the SEI's Tactical and AI-Enabled Systems Initiative, was elected the 2026 president of the IEEE Computer Society (CS), the largest community of computer scientists and engineers, with more than 370,000 members around the world. In this SEI podcast, Lewis sits down with Ipek Ozkaya, technical director of Engineering Intelligent Software Systems, to discuss her vision and plans for the IEEE CS presidency.

Improving Machine Learning Test and Evaluation with MLTE Mar 03, 2025

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Machine learning (ML) models commonly experience issues when integrated into production systems. In this podcast, researchers from the Carnegie Mellon University Software Engineering Institute and the U.S. Army AI Integration Center (AI2C) discuss Machine Learning Test and Evaluation (MLTE), a new tool that provides a process and infrastructure for ML test and evaluation. MLTE can aid organizations across the DoD in more effectively negotiating, documenting, and evaluating model and system qualities.

DOD Software Modernization: SEI Impact and Innovation Feb 25, 2025

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As software size, complexity, and interconnectedness has grown, software modernization within the Department of Defense (DoD) has become more important than ever. In this discussion moderated by Matthew Butkovic, technical director of risk and resilience in the SEI CERT Division, SEI director Paul Nielsen outlines the SEI's work with the DoD on software modernization, including controlling the attack surface, incorporating industry practices such as DevSecOps, and the interplay between software, cybersecurity, and AI.

Securing Docker Containers: Techniques, Challenges, and Tools Dec 16, 2024

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Containerization allows developers to run individual software applications in an isolated, controlled, repeatable way. With the increasing prevalence of cloud computing environments, containers are providing more and more of their underlying architecture. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Sasank Venkata Vishnubhatla and Maxwell Trdina, both engineers in the SEI CERT Division, sit down with Tim Chick, technical manager of the Applied Systems Group, to explore issues surrounding containerization, including recent vulnerabilities.

An Introduction to Software Cost Estimation Dec 04, 2024

Show notes

Software cost estimation is an important first step when beginning a project. It addresses important questions regarding budget, staffing, scheduling, and determining if the current environment will support the project. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Anandi Hira, a data scientist on the SEI's Software Engineering Measurement and Analysis team sits down with Bill Nichols, principal engineer and SEI data science team lead, to discuss software cost estimation including various metrics, best practices, and common challenges when developing or building a model.

Cybersecurity Metrics: Protecting Data and Understanding Threats Oct 11, 2024

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One of the biggest challenges in collecting cybersecurity metrics is scoping down objectives and determining what kinds of data to gather. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Bill Nichols, who leads the SEI's Software Engineering Measurements and Analysis Group, discusses the importance of cybersecurity measurement, what kinds of measurements are used in cybersecurity, and what those metrics can tell us about cyber systems.

3 Key Elements for Designing Secure Systems Oct 02, 2024

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To make secure software by design a reality, engineers must intentionally build security throughout the software development lifecycle. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Timothy A. Chick, technical manager of the Applied Systems Group in the SEI's CERT Division, discusses building, designing, and operating secure systems.

Using Role-Playing Scenarios to Identify Bias in LLMs Sep 16, 2024

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Harmful biases in large language models (LLMs) make AI less trustworthy and secure. Auditing for biases can help identify potential solutions and develop better guardrails to make AI safer. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Katie Robinson and Violet Turri, researchers in the SEI's AI Division, discuss their recent work using role-playing game scenarios to identify biases in LLMs.

Best Practices and Lessons Learned in Standing Up an AISIRT Sep 09, 2024

Show notes

In the wake of widespread adoption of artificial intelligence (AI) in critical infrastructure, education, government, and national security entities, adversaries are working to disrupt these systems and attack AI-enabled assets. With nearly four decades in vulnerability management, the Carnegie Mellon University Software Engineering Institute (SEI) recognized a need to create an entity that would identify, research, and identify mitigation strategies for AI vulnerabilities to protect national assets against traditional cybersecurity, adversarial machine learning, and joint cyber-AI attacks. In this SEI podcast, Lauren McIlvenny, director of threat analysis in the SEI's CERT Division, discusses best practices and lessons learned in standing up an AI Security Incident Response Team (AISIRT).

3 API Security Risks (and How to Protect Against Them) Aug 22, 2024

Show notes

The exposed and public nature of application programming interfaces (APIs) come with risks including the increased network attack surface. Zero trust principles are helpful for mitigating these risks and making APIs more secure. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), McKinley Sconiers-Hasan, a solutions engineer in the SEI CERT Division, discusses three API risks and how to address them through the lens of zero trust.

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