My fundamental research goal is to develop new mathematical models and computational tools for understanding and reasoning about the content, structure, and dynamics of complex social processes. I study a wide range of social processes, ranging from communications between scientists or political leaders to the activities of corporate or governmental organizations. To this end, I develop techniques for aggregating and representing large quantities of data from sources with disparate emphases, methods for analyzing text and network data, robust models for reasoning under uncertain information, and efficient inference algorithms. My research contributes to machine learning, Bayesian statistics, and, in collaboration with social scientists, to the nascent field of computational social science.
