Trisha N. Patel, Ph.D.

Cognitive Scientist

My research investigates how the nature of the visual system impacts learning and decision making. I seek methods to improve training programs, sustained attention, and AI-assisted decision making.


Data Simulation: Sample Size Estimation Using N Trials

Data Simulation: The Impact of Target Rate on Signal Detection

Travel Log

Research Interests


Attention is important for everyday tasks, but it can be difficult to focus for prolonged periods of time. The goal of this research is to understand how attention changes overtime and how well humans can sync themselves to these fluctuations. How can we increase the ability to maintain attention to benefit memory and perception?

The metacognition of attention: Using self-scheduled breaks to improve performance. (in prep)

Prioritization in visual attention does not work the way you think it does (2021)

Monitoring the ebb and flow of attention: Does controlling the onset of stimuli during encoding enhance memory? (2019)

AI-Assisted Decision Making

Artificial intelligence has become a popular tool to assist humans in everyday tasks. The integration between humans and AI is not clearly understood. To benefit from AI, users must adopt a healthy dynamic between their decisions and that of the machines. Over reliance or under reliance on AI advice is a common problem that obscures the benefit of AI. This research focuses on when and how human decision making can benefit from AI assistance.

Explaining Algorithm Aversion with Metacognitive Bandits (2021)


Memory interacts with a variety of cognitive processes, ranging from problem-solving to visual perception. I am interested in furthering the understanding of fundamental memory processes and cognition.

Exploring the contributions of spatial and non-spatial working memory to priming of pop-out (2017)

Forgetting as a consequence and enabler of creative thinking. (2014)