Department of
Psychological and Brain Sciences

Bio

Eeshan Hasan is a PhD student in the Computational Decision Making Lab under the leadership of Jennifer Trueblood. Having been formally trained in mathematics, he is broadly interested in modeling cognitive systems using computational techniques. Specifically, he is interested in modeling decision making about complex-real world objects like medical images and food using representations obtained from artificial neural networks. He is also curious about how attention can act as an informational processing bottleneck during decision making. He is also interested in the Wisdom of the Crowds where decisions can be aggregated from individuals to form more accurate decisions for medical decision making problems.

Computational Decision Making Lab
Area: Psychology + Cognitive Science
Advisor: Jennifer Trueblood
Interests: Modeling decision making about complex-real world objects, how attention can act as an informational processing bottleneck during decision making, the Wisdom of the Crowds

 

Publications

Hasan, E., Eichbaum, Q., Seegmiller, A. C., Stratton, C., & Trueblood, J. S. (2022). Improving Medical Image Decision‐Making by Leveraging Metacognitive Processes and Representational Similarity. Topics in Cognitive Science, 14(2), 400-413.

Hasan, E., & Trueblood, J. (2022). Representational Smoothing to Improve Medical Image Decision Making. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 44, No. 44).

Hasan, E., Eichbaum, Q., Seegmiller, A. C., Stratton, C., & Trueblood, J. (2021). Harnessing the wisdom of the confident crowd in medical image decision-making.