Yu (Rain) Huang

I am interested in applying generalized random utility models and stochastic transitivity models to capture and quantify the ubiquitous variability in choice and preference behavior, both in human and animal contexts, spanning various domains. I employ tools from computational geometry and Bayesian statistics to empirically and statistically test hypotheses predicted by a specific theory (e.g., in individual decision making and in social choice theory). Additionally, I play an active role in the enhancement of current algorithms designed for Bayesian inference when dealing with inequality constraints in high-dimensional spaces.