John Feeney specializes in the design and development of enhanced decision support systems and the application of machine learning and artificial intelligence technologies. His primary interests are in cognitive aspects of human performance, decision making, and automated feedback. John applies his expertise to human performance assessment systems over a wide range of domains including industrial health and safety, healthcare, cyber operations, intelligence analysis, and unmanned systems. His work includes formal knowledge representations, multi-modal assessment, analytics, and Live, Virtual, and Constructive (LVC) training applications.
John holds a PhD in Applied Experimental Psychology from The Catholic University of America, a MS in Software Engineering from National University, and a BA in Computer Science from the State University of New York at Oswego. He is a member of the American Psychology Association and The Society of Industrial Security Professionals (NCMS).
Feeney, J., Kiehl, Z., Durkee, K., Hiriyanna, A. Utilizing Physiological and Behavioral Signals to Estimate Human Functional State. In S. K. B. Perry & G. F. Goodwin (Co-chairs), Beyond Unobtrusive Methodologies: The Intrusive Component of ‘Big Data’ Research. Symposium Presented at the 32nd Annual Conference for the Society for Industrial and Organizational Psychology, Orlando FL. (April, 2017).
Pappada SM, Papadimos TJ, Lipps J, Feeney JJ, Durkee KT, Galster SM, Winfield S, Pfeil S, Castellon-Larios K, Bhandary SB, Stoicea N, Moffat-Bruce SM. Establishing an instrumented environment for simulation-based training of healthcare providers: an initial proof of concept. International Journal of Academic Medicine, June 2016.
Durkee, K., Pappada, S., Ortiz, A., Feeney, J., & Galster, S. (2015). System Decision Framework for Augmenting Human Performance Using Real-Time Workload Classifiers. Proceedings of the 5th Annual IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, Orlando, FL.
For more information about Dr. Feeney’s publications, please contact email@example.com.