Ryan M. HopeCarnegie Mellon University | CMU · Department of Psychology
Ryan M. Hope
Doctor of Philosophy
About
13
Publications
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129
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Introduction
Additional affiliations
May 2016 - May 2019
May 2016 - present
Education
January 2010 - May 2016
September 2007 - May 2009
September 2002 - May 2007
Publications
Publications (13)
A growing body of research on oculomotor control suggests that humans have much less control over their eye movements than typically assumed. Eye trackers have revealed that the eyes are in constant motion, even when fixating, and that these fixational eye movements are possibly functional. The growing consensus is that saccades are initiated autom...
Plenary Presentation at the 12 th Biannual Meeting of the German Cognitive Science Society – 2014-10oct-02 Gray, et al. (RPI) Elements of Extreme Expertise: Searching for Differences in Microstrategies Deployed by Experts and Novices.
Process models of cognition, written in architectures such as ACT-R and EPIC, should be able to interact with the same software with which human subjects interact. By eliminating the need to simulate the experiment, this approach would simplify the modeler's effort, while ensuring that all steps required of the human are also required by the model....
EEG data has been used to discriminate levels of mental workload when classifiers are created for each subject, but the reliability of classifiers trained on multiple subjects has yet to be investigated. Artificial neural network and naive Bayesian classifiers were trained with data from single and multiple subjects and their ability to discriminat...
Most of the current EEG-based workload classifiers are subject-specific; that is, a new classifier is built and trained for each human subject. In this paper we introduce a cross-subject workload classifier based on a hierarchical Bayes model. The cross-subject classifier is trained and tested with data from a group of subjects. In our work, it was...
EEG data has been used to discriminate levels of mental workload when classifiers are created for each subject, but the reliability of classifiers trained on multiple subjects has yet to be investigated. Artificial neural network and naive Bayesian classifiers were trained with data from single and multiple subjects and their ability to discriminat...
This research investigated an observer’s ability to track and maintain multiple uniquely iden- tified objects in a dynamic environment similar to ATC. The experimental task consisted of tracking a set of moving objects for twenty seconds. The objects were 6-character strings; three letters followed by three numbers. After tracking the objects for t...