Jonathan Cagan is the Interim Department Head and George Tallman and Florence Barrett Ladd Professor of Mechanical Engineering. His career spans collaborative and innovative work in education, research, and industry.
Researching engineering design automation and methods, Cagan merges AI, machine learning, and optimization methods with cognitive science problem solving. One focal area is the cognitive basis and computational modeling of designer processes to improve the effectiveness of human designers, with a focus on hybrid human/AI teams. Another area includes computational methods for the design and diagnosis of biomechanical systems. An additional focus is in user-centered design and integrated product development practice. He exemplifies the college’s culture of advanced collaboration, having worked with engineers, psychologists, neuro-scientists, marketers, designers, computer scientists, and architects in his work.
At Carnegie Mellon, Cagan co-founded and co-directed the Integrated Innovation Institute and served as interim dean, and, prior, associate dean for graduate and faculty affairs and chief academic officer, of the College of Engineering. Cagan was recently honored with the Robert A. Doherty Award for Sustained Contributions to Excellence in Education. Active in professional societies and editorial boards, Cagan is a Fellow in the American Society of Mechanical Engineers and was awarded with the ASME Design Theory and Methodology, Design Automation, and Ruth and Joel Spira Outstanding Design Educator Awards. He has authored several books, more than 300 publications, and is an inventor on multiple patents.
Design and Innovation
1990 Ph.D., Mechanical Engineering, University of California, Berkeley
1985 MS, Mechanical Engineering, University of Rochester
1983 BS, Mechanical Engineering, University of Rochester
Design Conference 2022
Cagan delivers keynote on AI-human hybrid teaming
MechE Interim Head Jonathan Cagan delivered a keynote speech at the Design Conference on AI-human hybrid teaming.
AI research featured in podcast
Featured on the podcast The Next Byte, new research by shows that AI may soon be taking over managerial positions and doing a better job at them.
Automating engineering’s ideal manager
A recent paper by a collaboration of CMU mechanical engineering and psychology researchers explored the use of artificial intelligence as a process manager for human design teams.
2021 Engineering faculty award winners selected
Congratulations to the 2021 CMU Engineering Faculty Awards winners.
Bringing students into the next industrial revolution
Students taking a new course combine rapidly expanding technologies to create innovative solutions for real societal problems.
Florida News Times
Cagan and Taylor’s research on DNA origami featured
MechE’s Jonathan Cagan and Rebecca Taylor’s research on DNA origami was featured in Florida News Times.
Using DNA for tiny tech
Tito Babatunde and her advisors Rebecca Taylor and Jon Cagan are combining their expertise to optimize designs for DNA origami nanostructures.
Predictive placentas: Using AI to protect mothers’ future pregnancies
In partnership with UPMC, Carnegie Mellon researchers developed a machine learning approach for examining placenta samples to determine if mothers are at risk for complications in future pregnancies.
CMU Mechanical Engineering
Cagan receives ASME award
MechE’s Jonathan Cagan has been named the 2020 recipient of the American Society of Mechanical Engineers’ Ruth and Joel Spira Outstanding Design Educator Award.
Cagan earns ASME award
The American Society of Mechanical Engineers recognizes Jonathan Cagan with the Ruth and Joel Spira Outstanding Design Educator Award.
Transforming the toolbox
The true impact of AI and machine learning occurs when these technologies are translated into the physical world. This is the role of mechanical engineers—and we’re leading the way.
Cagan research on training AI in design featured
ZME Science featured a new study by MechE’s Jon Cagan and Ph.D. candidate Ayush Raina that shows how artificial intelligence (AI) can be trained to learn complex design problems.