My group's research focuses on the development of novel methods for analyzing and modeling complex systems of all kinds and for extracting scientifically valuable insights from complex data. We are particularly interested in notions of collective dynamics, the emergence of patterns in random processes, population dynamics, and statistical forecasting. These efforts are fundamentally non-discplinary, sitting at the intersection of Computer Science, Physics, and Statistics, and with broad applications across the sciences.
The quantitative study of networks has emerged as a fundamental tool for the study of complex systems, in part for its ability to provide a rigorous foundation to the study of biological and social complexity. Our work here focuses on developing novel methods and models of large-scale structure (regularities like modules, communities, and hierarchies) that can be fitted directly to empirical network data, that account for auxiliary information including vertex and edge annotations and temporal dynamics, and that make precise predictions about missing information, anomalies, or future evolution.
Computational Social Science
The computer revolution is generating a revolution in the social sciences, via both the collection of massive data sets on social behavior and newfound ability to test complex theories with empirical data. These changes are allowing us to examine old questions with new data and models and to pose fundamentally new questions about large-scale patterns in social phenomena. My group's work here focuses on the 'science of science', and in particular the drivers of different kinds of inequalities in the academic workforce and how they shape who makes what scientific discoveries. I also study global patterns in terrorism and the dynamics of warfare and competition, as well as the way networks provide a way to bridge the micro-dynamics of individuals and the macro-patterns of populations.
Computational Systems Biology
Fundamental questions in biology increasingly demand answers that consider the interactions of different components or subsystems and the impact of macroevolutionary forces on the large-scale and long-term dynamics of the biosphere. This work spans all scales, including work with oncologists, paleontologists, epidemiologists, geneticists, and microbial ecologists. Currently, my group's work aims to understand the complex dynamics of ovarian cancer and the statistical patterns of genomic structural variants. In the past, my group has developed predictive theories of the macroevolution of species body sizes, microbial ecologies, and malaria.