Professor Todorov studies perception, judgment, and decision making. As an alternative to standard theory-driven experiments to study perception and judgment, Todorov’s lab pioneered data-driven computational methods. These methods model and visualize the perceptual basis of judgments (e.g., what makes an object beautiful) without prior assumptions, and can be used as a discovery tool. Building on this past work, current research uses generative AI to model individual human preferences. Another line of research is on the incompleteness of human statistical intuitions and the conditions under which these intuitions impair decision making (e.g., dealing with outcomes generated by chance processes).

Learn more about Professor Todorov here.