Chang S. (CS) Nam
Professor
- Phone: 919.515.8140
- Email: csnam@ncsu.edu
- Office: 4171 Fitts-Woolard Hall
Chang S. Nam is a Professor of Industrial and Systems Engineering at North Carolina State University. He is also an associated faculty in the UNC/NCSU Joint Department of Biomedical Engineering as well as the Department of Psychology. He is a fellow of the Human Factors and Ergonomics Society. Currently, Dr. Nam serves as the Editor-in-Chief of the journal Brain-Computer Interfaces. He has received the NSF CAREER Award (2010), Outstanding Researcher Award (2010-2011), and Best Teacher Award (2010-2011). He is a recipient of the 2018 US Air Force Summer Faculty Fellowship Program (AFSFFP) Award and the 2019 Leland S. Kollmorgen Spirit of Innovation Award from the HFES Augmented Cognition TG. Dr. Nam teaches and conducts basic and applied research in human factors and ergonomics engineering to advance the science of Human-Computer Interaction (HCI) with a broad perspective on the application of systems and information engineering to human-centered technologies, including brain-computer interfaces and rehabilitation engineering. His research has been supported by the National Science Foundation (NSF), Air Force Research Laboratory (AFRL), Air Force Office of Scientific Research (AFOSR), and the Laboratory for Analytic Sciences (LAS), UNC/NCSU Rehabilitation Engineering Center (REC). He is the main editor (with Drs. Nijholt and Lotte) of “Brain-Computer Interfaces Handbook: Technological and Theoretical Advances,” published by CRC Press. Currently, Nam serves as the Editor-in-Chief of the journal Brain-Computer Interfaces. For more details, refer to Brain-Computer Interface (BCI) Lab.
Research Interests
CS Nam’s research interests include Brain-computer interface and neurorehabilitation, haptic-user interaction, neuroergonomics, and adaptive and intelligent human-computer interaction.
Education
| Degree | Program | School | Year |
|---|---|---|---|
| Ph.D. | Doctor of Philosophy in Industrial Engineering | Virginia Tech | 2003 |
| MSIE | Master of Science in Industrial Engineering | State University of New York at Buffalo | 2000 |
Honors and Awards
- 2021 | Fellow, Human Factors and Ergonomics Society
- 2019 | Leland S. Kollmorgen Spirit of Innovation Award, HFES Augmented Cognition TG
- 2018 | Award for Outstanding Book in STEM, Taylor and Francis Group
- 2018 | U.S. Air Force Research Lab Summer Faculty Fellowship Program (AFSFFP) Awardee
- 2010 | CAREER Award, National Science Foundation
- 2010 | Outstanding Researcher Award, University of Arkansas
- 2010 | Best Teacher Award, University of Arkansas
Discover more about CS Nam
- Faculty Profile: Chang “CS” Nam
- Research Highlight: Brain-Computer Interface Lab
- Professor Receives Grant to Help Most Vulnerable People
- Brainstorming
- Ergonomics Teams Goes INDY
Publications
- Can vibrotactile stimulation and tDCS help inefficient BCI users?
- Won, K., Kim, H., Gwon, D., Ahn, M., Nam, C. S., & Jun, S. C. (2023), JOURNAL OF NEUROENGINEERING AND REHABILITATION, 20(1). https://doi.org/10.1186/s12984-023-01181-0
- Review of public motor imagery and execution datasets in brain-computer interfaces
- Gwon, D., Won, K., Song, M., Nam, C. S., Jun, S. C., & Ahn, M. (2023). [Review of , ]. FRONTIERS IN HUMAN NEUROSCIENCE, 17. https://doi.org/10.3389/fnhum.2023.1134869
- Culture and gender modulate dlPFC integration in the emotional brain: evidence from dynamic causal modeling
- Pugh, Z. H., Huang, J., Leshin, J., Lindquist, K. A., & Nam, C. S. (2022, May 25), COGNITIVE NEURODYNAMICS, Vol. 5. https://doi.org/10.1007/s11571-022-09805-2
- Detecting Human Trust Calibration in Automation: A Convolutional Neural Network Approach
- Choo, S., & Nam, C. (2022, January 19), IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, Vol. 1. https://doi.org/10.1109/THMS.2021.3137015
- Editorial: Neuroergonomics in Human-Robot Interaction
- Barresi, G., Nam, C. S., Esfahani, E. T., & Balconi, M. (2022, September 6), FRONTIERS IN NEUROROBOTICS, Vol. 16. https://doi.org/10.3389/fnbot.2022.1006103
- Emotion depends on context, culture and their interaction: evidence from effective connectivity
- Pugh, Z. H., Choo, S., Leshin, J. C., Lindquist, K. A., & Nam, C. S. (2022), SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE, 17(2), 206–217. https://doi.org/10.1093/scan/nsab092
- Estimating effective connectivity in Alzheimer's disease progression: A dynamic causal modeling study
- Huang, J., Jung, J.-Y., & Nam, C. S. (2022), FRONTIERS IN HUMAN NEUROSCIENCE, 16. https://doi.org/10.3389/fnhum.2022.1060936
- Evaluating Effective Connectivity of Trust in Human-Automation Interaction: A Dynamic Causal Modeling (DCM) Study
- Huang, J., Choo, S., Pugh, Z. H., & Nam, C. S. (2022), HUMAN FACTORS, 64(6), 1051–1069. https://doi.org/10.1177/0018720820987443
- Numerical and experimental evaluation of low-intensity transcranial focused ultrasound wave propagation using human skulls for brain neuromodulation
- Chen, M., Peng, C., Wu, H., Huang, C.-C., Kim, T., Traylor, Z., … Jiang, X. (2022, November 24), MEDICAL PHYSICS, Vol. 11. https://doi.org/10.1002/mp.16090
- A Functional BCI Model by the P2731 working group: Physiology
- Hossaini, A., Valeriani, D., Nam, C. S., Ferrante, R., & Mahmud, M. (2021, September 5), BRAIN-COMPUTER INTERFACES, Vol. 9. https://doi.org/10.1080/2326263X.2021.1968665
