Individual preferences fluctuate over time and differ among people. Few models of utility and decision making attempt to capture this fundamental fact explicitly. Prof. Regenwetter's primary goal is to model, measure, and predict preference and choice behavior when it is allowed to vary. Random utility models are designed as a modeling language to capture and quantify the ubiquitous variability in choice and preference behavior. Prof. Regenwetter's primary interests can be categorized as falling within three paradigms: probabilistic measurement, social choice, and preference evolution over time. Probabilistic measurement theory reformulates axiomatic measurement structures (e.g., in decision theory) in a probabilistic framework and thereby makes them empirically (and statistically) testable. Social choice theory is the theory of aggregating individual preferences or choices into a social ordering or choice. Dr. Regenwetter's interest in social choice is behavioral. Using random utility models as measurement tools, he evaluates and compares competing social choice functions on empirical data of various kinds. Dr. Regenwetter studies preference change over time via stochastic process models in which random utilities are indexed by continuous time.