Tarnita Lab @ Princeton

Understanding and managing complex adaptive systems—characterized by emergent patterns at scales larger than those of the interacting parts—has crystallized as one of the most pressing problems of our time, from biology to sociology, from medicine to financial markets. Faced with a range of challenges throughout evolutionary history that have led to a diversity of hierarchical, modular, and robust solutions, biological systems are ideal for the study of complex adaptive systems, and solutions inferred from biology have successfully been applied to system design and management in other fields. It is therefore imperative not only to study individual biological systems, but also to compare the organizing principles and emergent properties across a diversity of systems and scales.

Our lab studies the organization and emergent properties of complex adaptive systems at multiple scales, from single cells to entire ecosystems. Central to our approach is the development of general theoretical frameworks.

Simultaneously, we use empirical data to identify and catalog patterns in nature and, within the general frameworks, we develop models whose predictions we attempt to empirically test using experiments, molecular and genomic analyses, and field manipulations.