Michael D Lee

Picture of Michael D Lee
Professor, Cognitive Sciences
School of Social Sciences
Ph.D., University of Adelaide, 1997, Psychology
Grad Dip Education, University of Adelaide, 1993
B.A., University of Adelaide, 1992, Psychology
B.S., University of Adelaide, 1990, Mathematical Science
Fax: (949) 824-2307
Email: mdlee@uci.edu
University of California, Irvine
SBSG 2568
Mail Code: 5100
Irvine, CA 92697
Research Interests
computational models of cognition, Bayesian statistics, cognitive data science
Academic Distinctions
William K. Estes Early Career Award, Society for Mathematical Psychology, 2003.
Honorable mention, David Marr Prize, Cognitive Science Society, 2004.
University of Leuven fellowship, 2009.
President, Society for Mathematical Psychology, 2010.
Best Applied Cognitive Modeling Paper Prize, Cognitive Science Society, 2011.
Best paper award, Journal of Mathematical Psychology, 2017.
Previous: Action Editor, Cognitive Science; Action Editor, Journal of Mathematical Psychology; Editorial Board, Psychological Review; Editorial Board, Psychonomic Bulletin & Review; Editorial Board, Journal of Problem Solving

Current: Action Editor, Judgment and Decision Making; Editorial Board, Behavior Research Methods; Editorial Board, Decision
Research Abstract
My research involves the development, evaluation, and application of models of cognition including representation, memory, learning, and decision making, with a special focus on individual differences and collective cognition.

Much of my research uses naturally occurring behavioral data, and tries to pursue a solution-oriented approach to empirical science, in which the research questions are generated from real-world problems.

My methods involve probabilistic generative modeling, and Bayesian methods of computational analysis.
Lee, M.D., & Wagenmakers, E.-J. (2013). Bayesian cognitive modeling: A practical course. Cambridge University Press.
Lee, M.D. (2018). Bayesian methods in cognitive modeling. In J. Wixted & E.-J. Wagenmakers (Eds.) The Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, Volume 5: Methodology (Fourth Edition). John Wiley & Sons.
Lee, M.D., & Vanpaemel, W. (2018). Determining informative priors for cognitive models. Psychonomic Bulletin & Review, 25, 114-127.
Lee, M.D. (2011). How cognitive modeling can benefit from hierarchical Bayesian models. Journal of Mathematical Psychology, 55, 1-7.
Lee, M.D. (2008). Three case studies in the Bayesian analysis of cognitive models. Psychonomic Bulletin & Review, 15, 1-15.
Selker, R., Lee, M.D., & Iyer, R. (2017). Thurstonian cognitive models for aggregating top-n lists. Decision, 4, 87-101.
Danileiko, I. & Lee, M.D. (2017). A model-based approach to the wisdom of the crowd in category learning. Cognitive Science, 42, 861-883.
Lee, M.D., & Sarnecka, B.W. (2011). Number knower-levels in young children: Insights from a Bayesian model. Cognition, 120, 391-402.
2006-2009: Modeling Exploration and Exploitation in Structured Environments, Air Force Office of Scientific Research (with M. Steyvers)
2009-2010: Bayesian methods for the detection, diagnosis and treatment of Alzheimer's Disease, Alzheimer's Association (with R. Shankle)
2011-2013, Sequential Sampling Models of Adaptive Human Decision-Making, Air Force Office of Scientific Research
2012-2014: Categorizing models of categorization. National Science Foundation (with M. Kalish and J. Dunn).
2017-2019: Models of strategic decision making in dynamic environments. US Air Force Research Laboratory’s Cognitive Models and Agents Branch.via the Oak Ridge Institute for Science and Education (ORISE) Faculty Research Program.
2018-2019: Memory models and Bayesian methods for understanding memory impairment. Medical Care Corporation.
Professional Societies
Society for Mathematical Psychology
Cognitive Science Society
Other Experience
Senior Research Scientist
Australian Defence Science and Technology Organisation 1997—2001
Associate Professor
Department of Psychology, University of Adelaide 2001—2006
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