Andrew M. Olney presently serves as Professor in both the Institute for Intelligent Systems and Department of Psychology at the University of Memphis. Dr. Olney received a B.A. in Linguistics with Cognitive Science from University College London in 1998, an M.S. in Evolutionary and Adaptive Systems from the University of Sussex in 2001, and a Ph.D. in Computer Science from the University of Memphis in 2006. He is the former editor of the Journal of Educational Data Mining (2017-2022) and former Director/Associate Director of the Institute for Intelligent Systems at the University of Memphis (2006-2017), where he oversaw tenure track faculty, staff, and approximately 40 faculty affiliates. Dr. Olney has over 100 publications in the fields of artificial intelligence, education, and psychology, with a particular focus on using natural language processing to assess and enhance learning from text and learning through conversation. He has been an investigator on $18M in federal grants ($6M as PI) in these fields. His primary research interests are in natural language interfaces. Specific interests include language and knowledge acquisition (both human and AI) with applications in learning and performance support systems.
Classes at the undergraduate and graduate level involving cognitive science and computational modeling. Also graduate student mentorship in grant-sponsored research.
Publications and projects focussing on task-oriented natural langugage interfaces with specific focus on conversational intelligent tutoring systems, computational representations of meaning, and dyadic interaction and engagement.
Associate Editor of the Journal of Educational Data Mining and International Journal of Artificial Intelligence in Education, Coordinator for the Cognitive Science Graduate Certificate, and Coordinator for the Undergraduate Minor in Cognitive Science. Also community outreach and service to the field.
Traditional CV in PDF format
Serving on senior program committee for 18th International Conference on Educational Data Mining, 2025.
