## MIT Course Empowers Engineers with AI and Machine Learning tools
A popular course at MIT’s Department of Mechanical Engineering (MechE) is equipping students with the skills to integrate Artificial Intelligence (AI) and Machine Learning (ML) into the engineering design process. first offered in 2021, the course has drawn a diverse student body from across MIT – including Mechanical, Civil & Environmental, Aeronautical & Astronautical Engineering, the Sloan School of Management, Nuclear Science & Engineering, and Computer science - as well as students from Harvard and other institutions.
The course focuses on applying advanced ML and optimization strategies to real-world mechanical design challenges, ranging from bike frame design to city grid planning. Students participate in competitive challenges, refining existing code to achieve optimal solutions, tracked via live leaderboards.”Ther’s a lot of reason for mechanical engineers to think about machine learning and AI to essentially expedite the design process,” explains Lyle Regenwetter,a teaching assistant and PhD candidate in the Design Computation and Digital Engineering Lab (DeCoDE),were research centers on developing new ML and optimization methods for complex engineering design.Students engage with research papers and hands-on exercises focused on applying ML to areas like robotics, aircraft, structures, and metamaterials. The culminating project involves collaborative team work, applying AI techniques to a complex design problem of their choosing.
Professor Jamal Ahmed notes the high quality of student projects, often leading to research publications and awards. He cites the recent paper, “GenCAD-Self-Repairing,” wich received the American Society of Mechanical Engineers Systems Engineering, Details and Knowledge Management 2025 Best Paper Award.
Students have tackled a wide range of projects. Malia Smith, a MechE graduate student, successfully predicted ground force for runners using “markered motion captured data.” Em Lauber, a system design and management student, developed a framework for designing customized “cat trees” based on individual cat household needs.Ilan Moyer, also a MechE graduate student, created software for a novel 3D printer architecture.
Moyer summarizes the impact of the course, stating, “This class has opened the curtains” on the often-abstracted world of machine learning, providing a practical understanding of its submission in engineering.
