Sanghyun Choo

Advisor: Dr. C.S. Nam

Sanghyun Choo is a Ph.D. student at NC State’s Edward P. Fitts Department of ISE focusing on Human-Systems Engineering.

LinkedIn: https://www.linkedin.com/in/sanghyun-choo-22b66516b

Research Interests

Sanghyun’s research interests include Machine Learning (ML), Deep Learning (DL), eXplainable Artificial Intelligence (XAI), Brain-Computer Interface (BCI), Human-In-The-Loop (HITL), and Neuroergonomics. Thier previous and ongoing research topics include model-agnostic/-specific post hoc methods in XAI for BCI, representation learning for various applications (e.g., signal, image, and text), regularization methods (e.g., data augmentation, multi-task learning, and adaptive batch size) to improve the generalization performance of DL, uncertainty-aware Interactive Reinforcement Learning (IRL; which is one of HITL models), using Monte Carlo dropout to reduce sample complexity, performance improvement of machine learning models (e.g., restricted Boltzmann machine (RBM), Bayesian network), cognitive state recognition using neuroimaging methods with state-of-the-art ML/DL models, brain network analysis to find causal relationships among brain components, etc.

Education

DegreeProgramSchoolYear
Expected Graduation2020 | Spring or Summer
MSIEMaster of Science in Industrial EngineeringKumoh National Institute of Technology2018
BEIEBachelor of Engineering in Industrial EngineeringKumoh National Institute of Technology2016

 

 

Publications

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
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, 2. https://doi.org/10.1093/scan/nsab092
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. (2021), HUMAN FACTORS. https://doi.org/10.1177/0018720820987443
Brain-to-Brain Neural Synchrony During Social Interactions: A Systematic Review on Hyperscanning Studies
Nam, C. S., Choo, S., Huang, J., & Park, J. (2020). [Review of , ]. APPLIED SCIENCES-BASEL, 10(19), 6669. https://doi.org/10.3390/app10196669
Designing of smart chair for monitoring of sitting posture using convolutional neural networks
Kim, W., Jin, B., Choo, S., Nam, C. S., & Yun, M. H. (2019), DATA TECHNOLOGIES AND APPLICATIONS, 53(2), 142–155. https://doi.org/10.1108/DTA-03-2018-0021
Learning Framework of Multimodal Gaussian-Bernoulli RBM Handling Real-value Input Data
Choo, S., & Lee, H. (2018), Neurocomputing, 275(1), 1813–1822. https://doi.org/10.1016/j.neucom.2017.10.018

View all publications via NC State Libraries

Sanghyun Choo