Ryan Dew’s research explores how machine learning and Bayesian statistical methodologies can solve real-world marketing problems, and enhance the capacity of marketing managers to make data-driven decisions. Methodologically, he uses techniques from machine learning, Bayesian nonparametrics, and Bayesian econometrics.
Ryan Dew
Assistant Professor of Marketing
Govil Family Faculty Scholar
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