Joe Austerweil

Assistant Professor
328 Psychlogy
(608) 262-9932

Website: Austerweil Labratory

Research Interests: 

My research program investigates how people make decisions, reason, learn, and encode knowledge. To do so, I formulate computational models of how people learn and use their representations using recent advances in computer science and statistics. Then, I test these predictions empirically using online and laboratory experiments.

Representative Publications:

Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2015). Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122(3), 558-569. 

Austerweil, J. L. & Griffiths, T. L. (2013). Constructing flexible feature representations using nonparametric Bayesian inference. Psychological Review, 120 (4), 817-851.

Austerweil, J. L. & Griffiths, T. L. (2011). A rational model of the effects of distributional information on feature learning. Cognitive Psychology, 63, 173-209.

Austerweil, J. L. & Griffiths, T. L. (2011). Seeking confirmation is rational for deterministic hypotheses. Cognitive Science, 35, 499-526.