Dr. Karen Feigh

Associate Professor

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Biography

Karen M. Feigh is the Daniel S. Lewis Professor and Associate Chair for Research in Georgia Tech's Daniel Guggenheim School of Aerospace Engineering, with a courtesy appointment in the School of Interactive Computing. She directs the Georgia Tech Cognitive Engineering Center and leads research programs focused on computational cognitive modeling, cognitive work support systems, and technologies to improve performance in socio-technical systems. Dr. Feigh is responsible for undergraduate and graduate level instruction in areas including flight dynamics, human reliability analysis methods, human factors, human-automation interaction, and cognitive engineering. With 17 years of relevant research design experience, her work integrates aerospace engineering and cognitive systems engineering to enhance human-machine collaboration in complex, safety-critical domains such as aviation, spaceflight, and autonomous systems. Her research addresses topics like shared mental models, judgment, and situation awareness within human-AI teams, highlighting methods to infer decision strategies from behavioral data and modeling trust in human-machine interactions. Dr. Feigh has contributed to several committees for the National Academies of Sciences, Engineering, and Medicine focused on aviation safety and human-autonomy integration, and she is dedicated to mentoring the next generation of aerospace engineers to tackle challenges in complex human-machine partnerships.

Research Interests

Awards

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David S. Lewis Professorship

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Wilbur Orville Wright Graduate Award

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Amelia Earhart Fellowship

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National Science Foundation Graduate Research Fellow

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Marshall Scholar

Requirements for Georgia Institute of Technology

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:19
Reading
Required:19
Writing
Required:19
Speaking
Required:19
Total
Required:100
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:5.5
Speaking
Required:6.5
Overall
Required:7.5
Prerequisites
Undergraduate degree in computer science or related field
Application Checklist
  • Online application
  • Official transcripts
  • Three letters of recommendation
  • Statement of Purpose
Specialization Notes

Department of Computer Science: GRE scores are optional for Fall 2026.