How do we build mathematical models of complex social phenomena in the face of sparse data, methodological constraints, and multiple but incongruent scales of description? To address this question, we have developed approaches inspired by statistical physics to introduce a fresh perspective on conflict, political decision making, and information processing in firms. Our models not only illuminate the underlying social dynamics but also provide a bridge between diverse disciplines. Through the aforementioned examples, we will demonstrate how these models challenge conventional paradigms and foster interdisciplinary dialogue essential for understanding the evolution of complex societies. 

Eddie studies the role of information in the small and large living patterns around us. Examples range from the biology of neural tissue to the ecology of forests, the dynamics of armed conflict, and the processes of innovation and obsolescence in society. He is fascinated by how we paint those patterns on the shared canvas of mathematics and what the resulting similarities between the mathematical representations reveal about them. Do similarities reflect analogous function, universal dynamics, or are they (simply) artifacts of our representation? His work aims to answer these overarching questions that come together from the standpoint of information.