Fred Livingston

Associate Teaching Professor

Fred Livingston joined the ISE Department in 2023 as an associate teaching professor. When not in the office or co-working space, you can find him competing in challenges such as Badwater Ultra, IRONMAN, and Spartan.

Research Interests

Livingston’s research and teaching are centered on enhancing cyber-physical systems for smart manufacturing, focusing on AI-assisted low-volume manufacturing post-processing. These systems harness generative AI and machine learning to enable real-time process actions for responsive manipulation. They integrate seamlessly with the Industrial Internet of Things (IIoT) by employing open architectures, facilitating dynamic and flexible manufacturing processes. Furthermore, we leverage real-time perception, process modeling, and the advantages of digitalization to optimize processes and enhance scalability.

Education

DegreeProgramSchoolYear
Ph.D.Doctor of Philosophy in Electrical and Computer EngineeringNC State University2014
MSECEMaster of Science in Electrical and Computer EngineeringNC State University2006
BSECEBachelor of Science in Electrical and Computer EngineeringNC State University2003

Awards and Honors

  • 2007 | Outstanding Paper Award, Emerald LiteratiNetwork
  • 2006 | Fellow, Microsystems and Engineering Sciences Applications Institute
  • 2004 | Fellow, Microsystems and Engineering Sciences Applications Institute

Discover More About Fred Livingston

Publications

Anticipating Household Rescue Demand in Hurricanes Using Socio-Demographic Data and Machine Learning
Leavitt, P., Livingston, F., McConnell, B., Rachunok, B., Leavitt, P., Livingston, F., … Rachunok, B. (2025, January 1), SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5799543
Model-Free Optimal Control of PV-DC Microgrid Integration Using Value Iteration Algorithm
Alshareef, A., Aljumah, O., Alshammari, S., & Livingston, F. (2025, June 11), 2025 7TH GLOBAL POWER, ENERGY AND COMMUNICATION CONFERENCE, GPECOM, pp. 679–684. https://doi.org/10.1109/GPECOM65896.2025.11061890
A Design and Modeling Software Tool for Prototyping for Ultrasonic Transceivers
Livingston, F., & Grant, E. (2022), 2022 IEEE Sensors, 2022-October. https://doi.org/10.1109/sensors52175.2022.9967042
Rapid Development of Secure Robotic Platforms
Aldridge, H., & Livingston, F. (2022), Future Force Capabilities Conference and Exhibition. Presented at the Future Force Capabilities Conference and Exhibition, Austin, Texas.
Secure Rapid Prototyping for Unmanned Systems
Aldridge, H., & Livingston, F. (2021), NDIA Ground Vehicle Systems Engineering and Technology Symposium. Presented at the NDIA Ground Vehicle Systems Engineering and Technology Symposium, Novi, Michigan.
Binary encoding of sensors in textile structures
Grant, E., Livingston, F. J., Craver, M. D., Hegarty-Craver, M. S., Reid, L. G., & others. (2019, December). , .
Characterizing conductive yarns for pressure sensors applications
Grant, E., Livingston, F., Craver, M., Hegarty-Craver, M., & McMaster, S. (2015, November 1), 2015 IEEE SENSORS - Proceedings, pp. 108–111. https://doi.org/10.1109/ICSENS.2015.7370189
Characterizing conductive yarns for pressure sensors applications
Grant, E., Livingston, F., Craver, M., Hegarty-Craver, M., & McMaster, S. (2015), 2015 ieee sensors, 108–111.
Technology for Improving the Quality of Life for Patients Suffering from Vascular Insufficiency
Livingston, F. J. (2014). , (Doctor of Philosophy). North Carolina State University, Raleigh, NC.
Comparison of Learning on the Design of a KANSEI Robot Testbed for Understanding Human-Machine Interaction
Livingston, F., Grant, E., & Lee, G. (2010), International Conference on KANSEI Engineering and Emotion Research.

View all publications via NC State Libraries

Fred Livingston