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Software Engineering for Machine Learning

Grace Lewis and Ipek Ozkaya discuss their research into software engineering for machine learning (ML) with host Jonathan Spring.

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

Headshot of Grace Lewis.

Grace Lewis

Grace Lewis is a Principal Researcher and the lead for the Tactical and AI-Enabled Systems (TAS) Initiative at the Carnegie Mellon Software Engineering Institute (SEI). She is a Principal Investigator for two projects in the growing field of software engineering for machine-learning (ML) systems: “Characterizing and Detecting Mismatch in ML-Enabled …

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Headshot of Ipek Ozkaya.

Ipek Ozkaya

Ipek Ozkaya is a principal researcher and the 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 …

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