My primary research interests lie in decision theory and probabilistic modeling for artificial intelligence, machine learning and management science. My current interests include topics such as event models, graphical models, value of information, preference models and data-driven decision analysis. My applied work has spanned several domains, including sales, energy, business services, transportation, consumer products and public policy. I am interested in promoting the importance of probabilistic and decision-theoretic thinking to a broader audience. I occasionally dabble in the field of computational creativity. I am currently leading a research endeavor around causal learning, knowledge discovery, and reasoning with graphical event models (GEMs).