Transforming the toolbox

Empowering future mechanical engineers with AI and machine learning

It was on this campus that two professors, Allen Newell and Herb Simon, pioneered the foundations of artificial intelligence (AI) decades ago. Today at Carnegie Mellon, faculty and students within the Department of Mechanical Engineering have embraced AI and machine learning technologies to confront big challenges. These tools are becoming increasingly integrated into the department’s education and research programs.

“AI and machine learning are ubiquitous and exciting technologies. We view them as critical tools for the next generation of mechanical engineers,” said Allen Robinson, head of mechanical engineering. “Our department is pioneering the use of these tools to better understand physical phenomena and to develop better products, from surgical devices to autonomous vehicles.”

“While AI and machine learning are often associated with computer science, their true impact only occurs when they are translated into the physical world,” he added. “This translation is the role of mechanical engineers. We are the physical connection, using these technologies to solve real world problems.”

In the curriculum

Given the growing importance of AI and machine learning, the Department of Mechanical Engineering is teaching both graduate and undergraduate students how these technologies complement and extend the existing physics-based model. A sampling of courses includes:

• Artificial intelligence and machine learning—project course

• Machine learning and artificial intelligence for engineers

• Bayesian machine learning for scientists and engineers

• Deep learning for engineers

• AI and autonomous vehicles

“AI and machine learning are new tools that are not going away, and they will help to inform engineers how to do their jobs better,” said Jonathan Cagan, professor of mechanical engineering. “They will need to understand AI and machine learning, which will be embedded in the methods and techniques they use.”

A pioneer among peers

Solving the world’s biggest challenges requires collaboration among many partners, and preparing the next generation of mechanical engineers happens at many universities. While Carnegie Mellon is already integrating AI and machine learning tools into our curriculum, many of the departments at peer institutions aren’t there yet.

Recognizing this, Robinson teamed up with Evelyn Wang, the mechanical engineering department head at Massachusetts Institute of Technology (MIT), to co-organize and co-moderate a panel on the topic for department heads and chairs at peer institutions.

The panel, titled “Artificial Intelligence in Mechanical Engineering: Opportunities for Education and Research,” was part of the Department Head Forum at the 2019 International Mechanical Engineering Congress & Exposition (IMECE) in Salt Lake City, Utah in November.

Research and beyond

In a world of increasingly complex challenges, the Department of Mechanical Engineering's students and faculty are incorporating machine learning and artificial intelligence technologies as integral tools in nearly every area of mechanical engineering. Here are some examples of areas we are impacting:

• Safe autonomous vehicles
• Novel material discovery
• Robust human health
• Efficient design and manufacturing
• Infrastructure and smart cities 

Learn more about these research areas on meche.engineering.cmu.edu/ml.

Media contact:
Lisa Kulick
lkulick@andrew.cmu.edu