Overview

My research explores how people differ in cognitive traits such as attention, working memory, and numerical cognition. Human behaviors in psychological tasks typically show general trends at a population level yet differ greatly at an individual level. Exploring individual differences provides additional information about psychological constructs that underlie human behaviors.

I build and evaluate Bayesian cognitive models to provide parameters that would capture relevant properties of complex data, facilitating the analysis of individual differences. I also use machine-learning models based on Gaussian processes and deep neural network to identify individual differences in data-driven manners, and to address theoretical questions in novel ways.

Publications

Lee, S. H., Song, M. S., Oh, M. H., & Ahn, W. Y. (2024) Bridging the gap between self-report and behavioral laboratory measures: A real-time driving task with inverse reinforcement learning. Psychological Science, online first publication (link to the paper)

Lee, S. H., & Pitt, M. A. (2024). Implementation of an online spacing flanker task and evaluation of its test-retest reliability using measures of inhibitory control and the distribution of spatial attention. Behavior Research Methods, 1-12

Kwon, M, Lee, S. H., Ahn, W. Y. (2023). Adaptive design optimization as a promising tool for reliable and efficient computational fingerprinting. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8(8), 798-804.

Lee, S. H., Kim, D., Opfer, J., Pitt, M. A., & Myung, J. I. (2022). A number-line task with a Bayesian active learning algorithm provides insights into the development of non-symbolic number estimation. Psychonomic Bulletin & Review, 29(3), 1-14.

Lee, S. H., & Pitt, M. A. (2022). Individual differences in selective attention reveal the non-monotonicity of visual spatial attention and its association with working memory capacity. Journal of Experimental Psychology: General, 151(4), 749-762.

Lee, S. H., Pitt, M. A., & Myung, J. I. (2018). Computational modeling of cognitive control in a flanker task. Proceedings of the 40th Annual Meeting of the Cognitive Science Society, pp. 671-676.

Kim, S., Lee, S. H., & Cho, Y.S. (2015). Control processes through the suppression of the automatic response activation triggered by task-irrelevant information in the Simon-type tasks. Acta Psychologica, 162, 51-61.

Lee, S. H., Kim, S. P., & Cho, Y. S. (2015). Self-concept in fairness and rule establishment during a competitive game: a computational approach. Frontiers in Psychology, 6, 1321.