This page details a few of my research interests. More to come--eventually.

Speed-Accuracy Tradeoffs in Decision Making

My current research focuses on how people allocate their time when making decisions. Previous research has shown that when we spend more time making a decision, we tend to be more accurate. However, our time is valuable as well. Thus, there is a speed-accuracy tradeoff which affects how much time we allocate to making a decision. I am currently investigating how people determine how much time to spend making a decision, and whether we behave optimally in these scenarios.


Human Performance Modeling

Often, models in cognitive science attempt to explain a small portion of cognition in great detail. However, most human activities are very complex and require us to integrate many somewhat independent functions, including vision, motor skills, language, memory, decision making, and more. In order to model complex human behavior, it is necessary to have an approximate explanation of many different areas of cognition, and to understand how they interact.

I am interested in modeling human performance in complex tasks. My approach thus far has been to use ACT-R, a unified cognitive architecture, to predict human behavior. The video below shows an ACT-R model created by myself and collaborators Mike Byrne and Volkan Ustun.


In this video, the blue "ghost" plane represents the actual trajectory of a plane taxiing towards the runway. The white plane represents our ACT-R model attempting to follow the same taxi clearance. ACT-R's representation of the world is seen in the bottom right. Critically, the model is using generic strategies which could be applied to novel taxi routes. Such a model may be capable of predicting how changes to policies, procedures, or cockpit design influence a pilot's ability to taxi safely and efficiently. For an overview of how the model operates, see Zemla, Ustun, & Byrne (2011).