Christopher McComb is a faculty member in Carnegie Mellon University’s Department of Mechanical Engineering. Previously, he was an assistant professor in the School of Engineering Design, Technology, and Professional Programs at Penn State. He also served as director of Penn State’s Center for Research in Design and Innovation and led its Technology and Human Research in Engineering Design Group.

He received dual B.S. degrees in civil and mechanical engineering from California State University-Fresno. He later attended Carnegie Mellon University as a National Science Foundation Graduate Research Fellow, where he obtained his M.S. and Ph.D. in mechanical engineering.

His research interests include human social systems in design and engineering; machine learning for engineering design; human-AI collaboration and teaming; and STEM education, with funding from NSF, DARPA, and private corporations.


Ph.D., Mechanical Engineering, Carnegie Mellon University

M.S., Mechanical Engineering, Carnegie Mellon University

B.S., Civil Engineering and Mechanical Engineering, California State University-Fresno

Media mentions

CMU Engineering

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.


McComb selected as the recipient of ASME award

MechE’s Chris McComb was selected by ASME to receive the DTM (Design Theory and Methodology) Young Investigator Award.

Mechanical Engineering

Designing for a brighter future

New MechE faculty member and alumnus Christopher McComb wants to develop successful human-machine teams, create a student-centered learning environment, and give designers computational superpowers.

Construction Industry Institutue

McComb selected to lead new research team

MechE’s Chris McComb has been selected as the principal investigator for a new research team led by the Construction Industry Institute (CII). The team will find opportunities for ML, AI, and data analytics in advanced work packaging.