Department of Cognitive Sciences
University of California, Irvine
mark.steyvers@uci.edu
Key Research Areas
- Learning & Memory
- Cognitive Skill Acquisition
- Metacognition
- Hybrid human-machine algorithm systems
- Wisdom of crowds
- Bayesian computational modeling
- Machine learning
- Joint models for behavior and neuroimaging data
[Note to prospective graduate students — I will be looking for new students with interests in computational and empirical research to start in Fall 2020]
Representative Publications
Steyvers, M. and Benjamin, A.S. (2018). The joint contribution of participation and performance to learning functions: Exploring the effects of age in large-scale data sets. Behavior Research Methods. [pdf][code]
Bennett, S.T., Benjamin, A.S., Mistry, P.K., and Steyvers, M. (2018). Making a wiser crowd: Benefits of individual metacognitive control on crowd performance. Computational Brain and Behavior, 1, 90-99. [pdf][data]
Tauber, S., Navarro, D.J., Perfors, A., & Steyvers, M. (2017). Bayesian models of cognition revisited: Setting optimality aside and letting data drive psychological theory. Psychological Review, 124(4), 410-441. [pdf]
Hemmer, P. & Steyvers, M. (2009). A Bayesian Account of Reconstructive Memory. Topics in Cognitive Science, 1, 189-202. [pdf]
Turner, B. M., Forstmann, B. U., and Steyvers, M. (2019). Joint models of neural and behavioral data. Springer: New York. [book site]
Lee, M.D., Steyvers, M., de Young, M., & Miller. B.J. (2012). Inferring expertise in knowledge and prediction ranking tasks. Topics in Cognitive Science, 4, 151-163. [pdf]
Griffiths, T.L., Steyvers, M., & Tenenbaum, J.B.T. (2007). Topics in Semantic Representation. Psychological Review, 114(2), 211-244. [pdf]
Professional Bio
Mark Steyvers is a Professor of Cognitive Science at UC Irvine and is affiliated with the Computer Science department as well as the Center for Machine Learning and Intelligent Systems. His publications span work in cognitive science as well as machine learning and has been funded by NSF, NIH, IARPA, NAVY, and AFOSR. He received his PhD from Indiana University and was a Postdoctoral Fellow at Stanford University. He is currently serving as Associate Editor of Computational Brain and Behavior and Consulting Editor for Psychological Review and has previously served as the President of the Society of Mathematical Psychology, Associate Editor for Psychonomic Bulletin & Review and the Journal of Mathematical Psychology. In addition, he has served as a consultant for a variety of companies such as eBay, Yahoo, Netflix, Merriam Webster, Rubicon and Gimbal on machine learning problems. For his empirical research and computational modeling work, Dr. Steyvers received the New Investigator Award from the American Psychological Association as well as the Society of Experimental Psychologists.