We research the networks that are around us and in us, because understanding these networks can help us build technologies that augment our decision making in a variety of domains. In this way, we help decision makers integrate information through training and visualization. This work combines perspectives from information systems, cognitive psychology, social network analysis, and various computational sciences.

We focus on bringing needed techniques to several areas:

Understanding the dynamics of social networks. The ubiquity of networked technologies and the increase in location-aware mobile devices now make possible new forms of research that reveals the emergence of ideas.  These ideas are generated and shared within communities, and leave electronic traces as they spread between people situated across time and space. Within this area of research, we are looking at data from websites such as Digg and Twitter. We are also looking at the ways communication within and between social networks can be used to predict political, cultural, and economic phenomena. In order to help decision makers identify trends in social network information streams, we are exploring new ways of visualizing data.

Improving the design of information systems. Systems are difficult to design, and little is understood about how to encourage the creative leaps that lead to simple but powerful designs. Specifically, we are looking at how diagrams, gesture, and language interact in the design process.

Understanding the mechanisms of cognition. We study mental processes by conducting human subjects experiments and developing computational models that explain the observed behaviors. We apply our understanding of human learning and thought to predicting both individual and group behavior. These predictions, in turn, can be used to improve training and education.