Research Theme: Applied Cognitive Modeling

Summary: The focus of my research is applied cognitive modeling. I am particularly interested in using cognitive models to help bridge the gap between artificial intelligence and human cognition.

I use computational cognitive modeling (generative models of human behavior) to model human performance in complex domains. I have a background modeling visual imagery, HCI, motor control, decision making, Explainable Artificial Intelligence, and Human-Machine Teaming. Models are predictive of human performance and used to understand the underlying cognitive processes responsible for behavior. I have a strong interest in human-centric computing including: human-centric AI and human-machine teaming.

In recent work I developed computational cognitive models for Explainable Artificial Intelligence. The model provided common ground between a reinforcement learner trained in a domain task and human performers of the same tasks. We developed a novel algorithm, “Cognitive Salience” to compute how the features of the environment are affecting both the AI and human performers.

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