Human factors in transportation and medical systems; social interactions; intelligent systems; intelligent virtual agents; multimodal interface
Dr. Lee joined George Mason University in the Fall of 2016. Her areas of research interest include social interaction and communication in intelligent systems, human-automation interaction, human factors in transportation and medical systems, and behavior change, with a focus on improving quality of life and health behaviors.
Lately, she is interested in emerging technologies, such as interactions with intelligent virtual agents in online applications and the utilization of the five senses as communication channels in multisensory and multimodal wearable technologies.
Her background is Industrial Engineering (PhD) and Experimental Psychology (MS). With her 15+ years of experience in human factors, Dr. Lee’s most significant contribution is in the development of research methodology, including integration between applied and basic research, innovative experimental design, applying theories and principles from other research domains, and adaptive analytical methods. Prior to joining GMU, Dr. Lee directed the driving simulator research group at the Children’s Hospital of Philadelphia and successfully managed multi-institution research projects.
She is currently on leave (until summer 2024) and works as a government contractor at a company.
Lee, Y.-C., Momen, A., & LaFreniere, J. (2021). Attributions of social interactions: Driving among autonomous vs. conventional vehicles. Technology in Society, 66, 101631.
Lee, Y.-C., Hand, S. H., & Lilly, H. (2020). Are parents ready to use autonomous vehicles to transport children? Concerns and safety features. Journal of Safety Research, 72, 287-297.
Lee, Y.-C., & Mirman, J. H. (2018). Parents’ perspectives on using autonomous vehicles to enhance children’s mobility. Transportation Research Part C: Emerging Technologies, 96: 415-431.
Lee, Y.-C., & LaVoie, N. (2018). Instruction-prompted objective behaviors as proxy for subjective measures in a driving simulator. Transportation Research Part F: Psychology and Behaviour, 55, 58-66.
Lee, Y.-C., & Winston, F. K. (2016). Stress induction techniques in a driving simulator and reactions from newly licensed drivers. Transportation Research Part F, 42, 44-55.
Ontañón, S., Lee, Y.-C., Snodgrass, S., Bonfiglio, D. J., Winston, F. K., McDonald, C. C., & Gonzalez, A. J. (2014). Case-Based prediction of teen driver behavior and skill. Case-Based Reasoning Research and Development, Lecture Notes in Artificial Intelligence, 8765, 375-489.
Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2009). The interaction of cognitive load and attention-directing cues in driving. Human Factors, 51, 271-280.
Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2007). Visual attention in driving: the effects of cognitive load and visual disruption. Human Factors, 49, 721-733.
2019 - 2023: Driver vigilance framework for level 2 and level 3 driving automation systems, National Highway Traffic Safety Administration
2019 - 2021: Microplastics in the Mason watershed: A mass balance approach, GMU Institute for a Sustainable Earth
2018: Turning ambiguous traffic scenarios into autonomous vehicle’s intelligence, GMU OSCAR Summer Impact Grant
2017 - 2018: Interpretable temporal mining for contrastive driving behaviors, GMU Office of Research
2017 - 2018: GEST DC Study: Gestational exposure to traffic pollution in the DC metro area, GMU Office of Research
2015 - 2021: SCH:INT:Collaborative Research: Diagnostic driving: Real time driver condition detection through analysis of driving behavior, National Science Foundation
PhD in Industrial Engineering (Human Factors concentration) at University of Iowa, 2006
Daniela Barragan, Empirical and Theoretical Understanding of Driver Hazard Perception and Response (2020)