Software Engineering for Machine Learning
November 2021 • Podcast
Grace Lewis and Ipek Ozkaya discuss their research into software engineering for machine learning (ML) with host Jonathan Spring.
““Machine-learning systems are built by three different types of teams. You have data scientists or machine-learning engineers that are building machine-learning models. Then that model is passed to a software engineering team for integration into a larger system, and then the system is passed to an operations team in charge of operating and monitoring the system as a whole. Because these teams operate independently, they tend to make assumptions about what the other teams are doing, leading to mismatch. Mismatch occurs because of an incorrect assumption made in isolation by one of these teams.””
Software Engineering Institute
Mismatches between the perspectives and practices of the roles involved in the development and fielding of ML systems—data scientists, software engineers, and operations personnel—can affect the ability of systems to achieve their intended missions. In this SEI Podcast, Grace Lewis, a principal researcher and lead for the Tactical and AI-Enabled Systems Initiative, and Ipek Ozkaya, technical director of Engineering Intelligent Software Systems, discuss their research into characterizing, codifying, and mitigating such mismatches.
About the Speaker
Grace Lewis is principal researcher and lead of the Tactical and AI-enabled Systems (TAS) initiative at the Software Engineering Institute at Carnegie Mellon University. Lewis is the principal investigator ...
Grace Lewis is principal researcher and lead of the Tactical and AI-enabled Systems (TAS) initiative at the Software Engineering Institute at Carnegie Mellon University. Lewis is the principal investigator for the “Predicting Inference Degradation in Production ML Systems” and “Characterizing and Detecting Mismatch in ML-Enabled Systems” research projects. Lewis’ current areas of expertise and interest include software engineering for AI/ML systems, edge computing, software architecture (in particular the development of software architecture practices for systems that integrate emerging technologies), and software engineering in society. Lewis received a PhD in Computer Science from Vrije Universiteit Amsterdam, a Master in Software Engineering from Carnegie Mellon University, and B.Sc. in Software Systens Engineering from Icesi University. She is also very active in the IEEE Computer Society, currently serving as VP for Technical and Conference Activities (T&C) and a member of the Board of Governors.
Ipek Ozkaya is technical director of the Engineering Intelligent Software Systems group at the SEI. Ozkaya’s primary interests include developing techniques for improving software development efficiency ...
Ipek Ozkaya is technical director of the Engineering Intelligent Software Systems group at the SEI. Ozkaya’s primary interests include developing techniques for improving software development efficiency and system evolution with an emphasis on software architecture practices, software economics, and agile development. Ozkaya’s most recent research focuses on building the theoretical and empirical foundations of managing technical debt in large-scale, complex software-intensive systems and software engineering of AI-enabled systems. Ozkaya is editor in chief of IEEE Software magazine and is the coauthor of a practitioner book, Managing Technical Debt, Reducing Friction in Software Development. Ozkaya holds doctoral and master’s degrees in computational design from Carnegie Mellon University.