I am a social/behavioral scientist who researches how people make decisions. People are sometimes perfectly rational, acting optimally and hence consistently with widely used mathematical models of decision making. Other times, not so much… The state of the art is determining the limits of rationality as a descriptive theory (e.g., Homo economicus), and moreover what we can do to help people make better decisions. Part of this puzzle is understanding people's preferences, which we can measure and quantify. Another part of this research program is understanding how people think about uncertainty and risk, which we can also measure and quantify.

As a starting point I often use formal models that conceptualize people as perfectly rational decision agents (i.e., they optimize expectations and understand probabilities perfectly) and contrast these idealized decision makers with real people's behavior from experiments. This comparison helps us build psychologically realistic models of people who are
boundedly rational and heterogeneous in their preferences, beliefs, and reactivity to new information. Decision theory is a data driven interdisciplinary undertaking, bringing together methods from experimental economics, cognitive psychology, finance, statistics, and mathematical modeling. The overarching goal is to better understand how humans make decisions in noisy and complex environments and further how they adapt to changing contexts.

I currently work in the finance industry as the Head of Decision Sciences at Morningstar Investment Management in Chicago. Previously I was the Chair of Decision Theory and Behavioral Game Theory at the
ETH Zürich, and a visiting professor in the economics department of the University of Zürich. Before that I was a research scientist and the Associate Director of the Center for Decision Sciences at Columbia University in New York. Here is my full curriculum vitae with all the details.