Research interests: Computational cognition, Bayesian cognitive modeling, adaptive design optimization, Gaussian process optimization, autonomous behavioral research system, model selection and evaluation, minimum description length, neural networks.

Awards, Honors and Recognition

2001 – 2002: President, Society for Mathematical Psychology
1995: New Investigator Award, Society for Mathematical Psychology
Fellow, American Association for the Advancement of Science
Fellow, Association for Psychological Science
Fellow, Psychonomic Society

Selected Publications

Kim, W., Pitt, M. A., Lu, Z.-L., & Myung, J. I. (2017). Planning beyond the next trial in adaptive experiments: A dynamic programming approach. Cognitive Science, 41, 2234-2252.

Aranovich, G. J., Cavagnaro, D. R., Pitt, M. A., Myung, J. I., & Mathews, C. A. (2017). A model-based analysis of decision making under risk in obsessive-compulsive and hoarding disorders. Journal of Psychiatric Research, 90, 126-132.

Cavagnaro, D. R., Aranovich, G. J., McClure, S. M., Pitt, M. A., & Myung, J. I. (2016). On the functional form of temporal discounting: An optimized adaptive test. Journal of Risk and Uncertainty, 52, 233-254.

Hou, F., Lesmes, L., Kim, W., Gu, H., Pitt, M. A., Myung, J. I., & Lu, Z.-L. (2016). Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes. Journal of Vision, 16(6):18, 1-19.

Gu, H., Kim, W., Hou, F., Lesmes, L., Pitt, M. A., Lu, Z.-L., & Myung, J. I. (2016). A hierarchical Bayesian approach to adaptive vision testing: A case study with the contrast sensitivity function. Journal of Vision, 16(6):15, 1-17.

Kim, W., Pitt, M. A., Lu, Z.-L., Steyvers, M., & Myung, J. I. (2014). A hierarchical adaptive approach to optimal experimental design. Neural Computation, 26, 2463-2492.

Montenegro, M., Myung, J. I., & Pitt, M. A. (2014). Analytic expressoins for the REM model of recognition memory. Journal of Mathematical Psychology, 60, 23-28.

Myung, J. I., Cavagnaro, D. R., & Pitt, M. A. (2013). A tutorial on adaptive design optimization. Journal of Mathematical Psychology, 57, 53-67.

Cavagnaro, D. R., Pitt, M. A., Gonzalez, R., & Myung, J. I. (2013). Discriminating among probability weighting functions using adaptive design optimization. Journal of Risk and Uncertainty, 47(3), 255-289.

Cavagnaro, D. R., Gonzalez, R., Myung, J. I., & Pitt, M. A. (2013). Optimal decision stimuli for risky choice experiments: An adaptive approach. Management Science, 59(2), 358-375.

Kim, W., Pitt, M. A., & Myung, J. I. (2013). How do PDP models learn quasiregularity? Psychological Review, 120 (4), 903-916.

Cavagnaro, D. R., Pitt, M. A. & Myung, J. I. (2011). Model disccrimination through adaptive experimentation. Psychonomic Bulletin & Review, 18(1), 204-210.