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 Department of Psychology. 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 US Air Force Summer Faculty Fellowship Program (AFSFFP) Award in 2018. 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. He is a Fellow of the Human Factors and Ergonomics Society (HFES).
Publications
- Brain dynamics of mental workload in a multitasking context: Evidence from dynamic causal modeling
- Huang, J., Pugh, Z. H., Kim, S., & Nam, C. S. (2024), COMPUTERS IN HUMAN BEHAVIOR, 152. https://doi.org/10.1016/j.chb.2023.108043
- 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
- Designing an XAI interface for BCI experts: A contextual design for pragmatic explanation interface based on domain knowledge in a specific context
- Kim, S., Choo, S., Park, D., Park, H., Nam, C. S., Jung, J.-Y., & Lee, S. (2023), INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 174. https://doi.org/10.1016/j.ijhcs.2023.103009
- Effectiveness of multi-task deep learning framework for EEG-based emotion and context recognition
- Choo, S., Park, H., Kim, S., Park, D., Jung, J.-Y., Lee, S., & Nam, C. S. (2023), EXPERT SYSTEMS WITH APPLICATIONS, 227. https://doi.org/10.1016/j.eswa.2023.120348
- Enhancing Culinary Training with Spatial Augmented Reality: A User Study Comparing sAR Kitchen and Video Tutorials
- Ghasemi, Y., Bayro, A., MacDonald, J., Jeong, H., Reynolds, J., & Nam, C. S. (2023), 2023 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS, VRW, pp. 390–392. https://doi.org/10.1109/VRW58643.2023.00085
- 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
- Review of public motor imagery and execution datasets in brain-computer interfaces (vol 17, 1134869, 2023)
- Gwon, D., Won, K., Song, M., Nam, C. S., Jun, S. C., & Ahn, M. (2023, May 17), FRONTIERS IN HUMAN NEUROSCIENCE, Vol. 17. https://doi.org/10.3389/fnhum.2023.1205419
- 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