Grace Lewis
Software Engineering Institute
Grace Lewis is a Principal Researcher at the Carnegie Mellon Software Engineering Institute (SEI), where she conducts applied research on how software engineering principles, practices, and tools need to evolve in the face of emerging technologies. She is the principal investigator for the Establishing the Practice of Integrated Test and Evaluation for ML Capabilities project, in addition to other projects that are advancing the state of the practice of software engineering for AI-enabled systems.
Grace is also the lead for the Enabling Edge Intelligence (E2I) applied research and development team at the SEI that is creating and transitioning innovative solutions, principles, and best practices for
- agentic AI for edge intelligence
- software engineering to support edge missions
- resource management for edge systems
- adaptive systems for mission resilience
She is also the 2026 President of the IEEE Computer Society. Grace holds a B.Sc. in Software Systems Engineering and a Post-Graduate Specialization in Business Administration from Icesi University in Cali, Colombia; a Master in Software Engineering from Carnegie Mellon University; and a Ph.D. in Computer Science from Vrije Universiteit Amsterdam.
A Quality Model for Machine Learning Components Quick Reference Guide
• Educational Material
By Grace Lewis , Rachel Brower-Sinning , Robert Edman , Alex Derr , Ipek Ozkaya , Sebastián Echeverría
A Quality Model for Machine Learning Components
• Blog Post
By Grace Lewis , Rachel Brower-Sinning , Robert Edman , Alex Derr , Ipek Ozkaya , Sebastián Echeverría
A Quality Model for Machine Learning Components Quick Reference Guide
• Educational Material
By Grace Lewis , Rachel Brower-Sinning , Robert Edman , Alex Derr , Ipek Ozkaya , Sebastián Echeverría
Engineering of Edge Software Systems: A Report from the November 2022 SEI Workshop on Software Systems at the Edge
• SEI Report
Pervasive Mobile Computing
• SEI Report
By William Anderson , Jeff Boleng , Ben W. Bradshaw , James Edmondson , Grace Lewis , Edwin J. Morris , Marc Novakouski , James Root
Cyber-Foraging for Improving Survivability of Mobile Systems
• SEI Report
By Sebastián Echeverría , Grace Lewis , James Root , Ben W. Bradshaw
A Quality Model for Machine Learning Components
• Blog Post
By Grace Lewis , Rachel Brower-Sinning , Robert Edman , Alex Derr , Ipek Ozkaya , Sebastián Echeverría
Enhancing Machine Learning Assurance with Portend
• Blog Post
By Jeffrey Hansen , Sebastián Echeverría , Lena Pons , Gabriel Moreno , Grace Lewis , Lihan Zhan
Introducing MLTE: A Systems Approach to Machine Learning Test and Evaluation
• Blog Post
By Alex Derr , Sebastián Echeverría , Katherine R. Maffey (AI Integration Center, U.S. Army) , Grace Lewis
Tackling Collaboration Challenges in the Development of ML-Enabled Systems
• Blog Post
By Grace Lewis
Internet-of-Things (IoT) Security at the Edge
• Blog Post
Software Engineering for Machine Learning
• Podcast
By Grace Lewis , Ipek Ozkaya
Software Engineering for Machine Learning
• Webcast
By Grace Lewis , Ipek Ozkaya