Jerome Busemeyer

Biography

Jerome Robert Busemeyer is a Distinguished Professor at Indiana University Bloomington in the Department of Psychological & Brain Sciences and Cognitive Science Program.

Busemeyer completed his undergraduate degree in Psychology at the University of Cincinnati in 1973, which he followed with both a masters and Ph.D. in Experimental Psychology from the University of South Carolina in 1976 and 1979 respectively. He was a NIMH post-doctoral fellow in the Quantitative program at University of Illinois until 1980. Afterwards, he became a faculty member at Purdue University until 1997, and then he joined the faculty at Indiana University-Bloomington. He was president of the Society for Mathematical Psychology in 1993, and he also served as the Manager of the Cognition and Decision Program at the Air Force Office of Scientific Research in 2005-2007. He was Chief Editor of Journal of Mathematical Psychology from 2005 to 2010, and he is the inaugural Editor of the APA journal Decision.

Education & Training

·       Post-Doctoral Fellow,
Quantitative Methods, University of Illinois, 1980

·       Ph.D., University of South Carolina, 1979

·       M.A., University of South Carolina, 1976

·       B.A., cum laude, University of Cincinnati, 1973

Areas of Study

·       Cognitive Science

·       Dynamic Models

·       Quantitative Methods

Research Topics

·       Dynamic, emotional, and cognitive models of judgment and decision making

·       Neural network models of function learning, interpolation, extrapolation

·       Methodology for comparing and testing complex models of behavior

·       Measurement theory with error contaminated data.

 Honors & Awards

• Honorary Doctorate of the university of Basel in Psychology, 2019
• Distinguished Professor Indiana University, 2017
• Fellow of American Academy of Arts and Sciences, 2017
• Fellow Cognitive Science Society, 2017
• Society of Experimental Psychologists Howard C. Warren medal, 2015
• Fellow of the Society of Experimental Psychologists, 2006

Selected
Publications

Johnson, J. G. & Busemeyer, J. R. (2005) A dynamic, computational model of preference reversal phenomena. Psychological Review, 112(4), 841-861.

Yechiam, E. & Busemeyer, J. R. (2005) Comparisons of basic assumptions embedded in learning models for experienced based decision making. Psychonomic Bulletin and Review, 12 (3), 387-402.

McDaniel, M. A. & Busemeyer, J. R. (2005) The conceptual basis of function learning and extrapolation: Comparison of rule and associative based models. Psychonomic Bulletin and Review, 12 (1), 24-42.

Busemeyer, J. R., Wang, Z., & Townsend, J. T. (2006) Quantum dynamics of human decision making. Journal of Mathematical Psychology, 50, 220-241.

Rieskamp, J., Busemeyer, J. R., & Mellers, B. A. (2006) Extending the bounds of rationality: A review of research on preferential choice. Journal of Economic Literature, 44, 631-636.

Diederich, A. & Busemeyer, J. R. (2006) Modeling the effects of payoffs on response bias in a perceptual discrimination task: Threshold bound, drift rate change, or two stage processing hypothesis. Perception and Psychophysics, 97 (1), 51-72.

Yechiam, E., Busemeyer, J. R., Stout, J. C., & Bechara, A. (2005) Using cognitive models to map relations between neuropsychological disorders and human decision making deficits. Psychological Science, 16 (12), 841-861.

Busemeyer, J. R. & Johnson, J. G. (2006) Micro-process models of decision-making. In R. Sun (Ed.) Cambridge Handbook of Computational Cognitive Modeling. Cambridge University Press.

Busemeyer, J.R., Jessup, R. K., Johnson, J.G., & Townsend, J. T. (2006) Building bridges between neural models and complex human decision making behavior. Neural Networks, 19, 1047-1058.

Busemeyer, J. R., Barkan, R., Mehta, S.; & Chatervedi, A. (2007) Context models and models of preferential choice: Implications for Consumer Behavior. Marketing Theory, 7 (1), 39-58.

Yechiam, E. & Busemeyer, J. R. (2008) Evaluating generalizability and parameter consistency in learning models. Games and Economic Behavior, 63, 370-394.

Busemeyer, J. R. & Pleskac, T. (2009) Theoretical tools for understanding and aiding dynamic decision making. Journal of Mathematical Psychology, 53, 126-138.

Johnson, J.G. & Busemeyer, J. R. (2007) A computational model of the attention processes used to generate decision weights in risky decision making. Under revision for Cognition.

Jessup, R. K., Bishara, A. J., & Busemeyer, J. R. (2008) Feedback produces divergence from prospect theory in predictive choice. Psychological Science, 19 (10), 1015-1022.

Ahn, W. Y., Busemeyer, J. R., Wagenmakers, E. J., Stout, J. C. (2009) Comparison of decision learning models using the generalization criterion method. Cognitive Science, 32, 1376-1402.

Pothos, E. M. & Busemeyer, J. R. (2009) A Quantum Probability Explanation for Violations of "Rational" Decision Theory. Proceedings of the Royal Society B, 276 (1165), 2171-2178.

Busemeyer, J. R. & Diederich, A. Cognitive Modeling. Sage.

Pleskac, T. J. & Busemeyer, J. R. (submitted). Two Stage Dynamic Signal Detection Theory: A Dynamic and Stochastic Theory of Confidence, Choice, and Response Time.