Dr. Michael N. Jones

Assistant Professor of Psychology

Contact Information

Office: PY 357
Office Phone: 812-856-1490
Lab: Hillcrest 300
Lab Phone:n/a
E-mail:

Web site: Computational Language and Cognition Lab

Educational Background

Ph.D. Psychology (Queen’s University) January, 2005
M.A. Psychology (Queen’s University) August, 2001
B.A. (Hon) Psychology (Nipissing University) April, 1999

Areas of Study

Cognitive Science

Research Topics

Computational models of memory and language
Dynamics of knowledge and language acquisition
Categorization and concept learning
Attention in reading and visual navigation
Artificial intelligence; specifically swarm intelligence

Research Summary:

My research focuses on language learning, comprehension, and knowledge representation in humans and machines. I employ a combination of computational and experimental techniques to examine large-scale statistical structure of certain environments (such as language corpora) with the goal of understanding how this structure could be learned and represented with the mathematical capabilities of human learning and memory. This line of my research has applications in machine learning and intelligent systems. The overall premise of my work is that complex behavior often naturally emerges as a product of many simple processors working together at a large scale in response to statistical redundancies in a complex environment.

Under the same unified theme of large-scale statistical learning, I study human associative and recognition memory, categorization, decision making, and the role of attention in reading and perception. I am particularly interested in the temporal dynamics of learning in all these domains, and how to model the time course of knowledge acquisition. My secondary interests involve the application of these models to practical problems in text mining, intelligent search algorithms, and automated comprehension and scoring algorithms.

Representative Publications

Riordan, B., & Jones, M. N. (2009). Redundancy in linguistic and perceptual experience: Comparing distributional and feature-based models of semantic representation. Topics in Cognitive Science.

Hare, M., Jones, M. N., Thomson, C., Kelly, S., & McRae, K. (2009). Activating event knowledge. Cognition.

Recchia, G. L., & Jones, M. N. (2009). More data trumps smarter algorithms: Training computational models of semantics on very large corpora. Behavior Research Methods.

Jones, M. N., & Mewhort, D. J. K. (2007) Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114, 1-37.

Jones, M. N., Kintsch, W., & Mewhort, D. J. K. (2006) High-dimensional semantic space accounts of priming. Journal of Memory and Language, 55, 534-552.

Mozer, M., Jones, M. N., & Shettel, M. (2006) Context effects in category learning: An investigation of four probabilistic models. Proceedings of NIPS.

Jones, M. N., & Mewhort, D. J. K. (2004) Case-sensitive letter and bigram frequency counts from large-scale English corpora. Behavior Research Methods, Instruments, and Computers, 36, 388-396.

Jones, M. N., & Mewhort, D. J. K. (2004) Tracking attention with the focus-window technique: The information filter must be calibrated. Behavior Research Methods, Instruments, and Computers, 36, 270-276.