Statistical mechanics offers an elegant description of physical systems whose macroscopic properties arise, at least in part, from mathematical laws governing large ensembles. The picture that emerges is profound: the collective behaviors of many complex systems do not depend on microscopic intricacies but instead on statistical properties shared by a large number of systems. Research in the Wood group focuses on the development and application of similar approaches for the study of living systems, where biologically-relevant dynamics—for example, the evolution of drug-resistance in a population of cancer cells—emerge from interactions and competition between a large number of individual components. Using both theoretical and experimental tools, we study a wide range of biological systems, with particular emphasis on systems dominated by heterogeneities, non-equilibrium dynamics, strong interactions with the environment, or rare events. Our goal is to develop a quantitative physical understanding that can be used to predict, and in some cases, control these biological systems. We are also interested in exploring when, and why, statistical or dynamical properties lead to universal behaviors common to entire classes of living systems. Our research is highly multi-disciplinary and combines theoretical tools from physics, engineering, applied math, and computer science with experimental approaches from molecular biology, genetics, microbiology, and cancer biology.