His teaching and course-development work encompasses software engineering, computer science, computer networks, embedded and digital systems, computer graphics, systems engineering, and graduate engineering capstone courses. His current scholarly and applied interests include responsible generative AI use in engineering education, AI literacy and source verification, workforce readiness, scalable online STEM learning, and AI-assisted course development and quality assurance.
Before joining Embry-Riddle, Dr. Doyle held academic leadership positions and engineering roles with organizations including Texas Instruments, Raytheon, Lockheed Martin, Rockwell Collins, and AAI. He is the author of Applied Probability and Statistics for Engineers: An Interactive Learning Approach and is a member of ASEE and IEEE.
Ph.D. - Doctor of Philosophy in Electrical Engineering, Southern Methodist University
M.S. - Master of Science in Electrical Engineering, University of Oklahoma Norman Campus
B.S. - Bachelor of Science in Electrical Engineering: Computer Engineering (Certified Cooperative Education), Oklahoma State University-Main Campus