Dr. Karen M. Feigh is the Daniel S. Lewis Professor and Associate Chair for Research at Georgia Tech's Daniel Guggenheim School of Aerospace Engineering with a courtesy appointment in the School of Interactive Computing. As the director of the Georgia Tech Cognitive Engineering Center, she leads a research and education program focused on the computational cognitive modeling and design of cognitive work support systems and technologies to improve the performance of socio-technical systems. She is responsible for undergraduate and graduate level instruction in the areas of flight dynamics, human reliability analysis methods, human factors, human-automation interaction, and cognitive engineering. Feigh has over 17 years of relevant research and design experience.  

Dr. Feigh’s research integrates aerospace engineering, cognitive systems engineering, and human factors to improve human–machine collaboration in complex, safety-critical domains such as aviation, spaceflight, and autonomous systems. Her work addresses shared mental models, judgment, and situation awareness in human–AI teams; inferring decision strategies from behavioral data; and modeling trust in human–machine interactions. Recent projects include safe collaboration between autonomous pilots and human crews, the role of shared mental models in human–AI teaming, and methods for inferring belief states in partially observable human–robot teams.

She has served as an Associate Editor for the Journal of Cognitive Engineering and Decision Making and the IEEE Transactions on Human-Machine Systems, helping to shape the research agenda in human–automation interaction. Dr. Feigh has also contributed her expertise to the National Academies of Sciences, Engineering, and Medicine, serving on committees addressing aviation safety, human–autonomy integration, and the future workforce for aerospace systems.

Through her interdisciplinary research, leadership, and mentorship, Dr. Feigh advances the design of resilient socio-technical systems and prepares the next generation of aerospace engineers to address the challenges of increasingly complex human–machine partnerships.