Epping, G. P., Caplin, A., Duhaime, E., Holmes, W. R., Martin, D., & Trueblood, J. S. (in press). Harnessing Human Uncertainty to Train More Accurate and Aligned AI Systems. Decision Analysis. https://osf.io/wtnx6

Epping, G. P., Caplin, A., Duhaime, E., Holmes, W. R., Martin, D., & Trueblood, J. S. (2024). Improving human and machine classification through cognitive-inspired data engineering. https://osf.io/euk26

Hasan, E., Duhaime, E. P., & Trueblood, J. S. (2024). Boosting Wisdom of the Crowd for Medical Image Annotation Using Training Performance and Task Features. Cognitive Research: Principles and Implications, 9, 1-21. https://doi.org/10.1186/s41235-024-00558-6

Hasan E., Trueblood, J. S., Eichbaum, Q., Seegmiller, A. C., & Stratton, C. (2021). Improving Medical Image Decision Making by Leveraging Metacognitive Processes and Representational Similarity. In T. Fitch, C. Lamm, H. Leder, & K. Tessmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society. (230-236). Austin, TX: Cognitive Science Society. (link)

— Awarded a Computational Modeling Prize for Applied Cognition from the Cognitive Science Society