Rate My Professor Chang Nam

Chang S. Nam is a Professor of Industrial and Systems Engineering in the Edward P. Fitts Department at North Carolina State University. He holds associated faculty appointments in the UNC/NC State Joint Department of Biomedical Engineering and the Department of Psychology. Nam earned a Bachelor’s degree in Industrial Engineering from Hanyang University in Seoul, South Korea, followed by a Master’s degree in Industrial Engineering from the University at Buffalo, and a Ph.D. in Industrial and Systems Engineering from Virginia Tech in 2006. He directs the Brain-Computer Interface Lab, where he teaches and conducts basic and applied research in human factors and ergonomics engineering. His research specializations encompass human-computer interaction with a focus on brain-computer interfaces, neuroergonomics, neuroengineering, rehabilitation engineering, and neurally inspired human-systems engineering, including efforts to enable communication for vegetative patients through brain simulations and advanced interfaces.

Nam has been recognized with the NSF CAREER Award in 2010, the Outstanding Researcher Award and Best Teacher Award for 2010-2011, and the US Air Force Summer Faculty Fellowship Program Award in 2018. He is a Fellow of the Human Factors and Ergonomics Society and serves as Editor-in-Chief of the journal Brain-Computer Interfaces, as well as a main editor of the “Brain-Computer Interfaces Handbook: Technological and Theoretical Advances” published by CRC Press. Key publications include “A scoping review on emerging technologies and automation of musculoskeletal ergonomic assessments” with H. Iyer et al. (2025, Ergonomics); “Brain dynamics of mental workload in a multitasking context: Evidence from dynamic causal modeling” with J. Huang et al. (2023, Computers in Human Behavior); “Effectiveness of multi-task deep learning framework for EEG-based emotion and context recognition” with S. Choo et al. (2023, Expert Systems with Applications); “Review of public motor imagery and execution datasets in brain-computer interfaces” with D. Gwon et al. (2023, Frontiers in Human Neuroscience); and “Culture and gender modulate dlPFC integration in the emotional brain: evidence from dynamic causal modeling” with Z. H. Pugh et al. (2022, Cognitive Neurodynamics). His contributions advance the integration of neuroscience into engineering practices, enhancing human-centered technologies.