Golan received his BA and MS from the Hebrew University of Jerusalem and his PhD degree from UC Berkeley (economics with concentrations in statistical physics and mathematical economics). He is the Director of the Info-Metrics Institute and a Professor of Economics at American University. He is also a Senior Associate at Pembroke College, Oxford. His main research interest is information, primarily the study of how to reason and optimize under conditions of incomplete information and the interdisciplinary study of info-metrics, which is the science and practice of information processing, modeling, inference, and problem solving with insufficient information. He focuses on developing information-theoretic inferential methods for solving problems, for modeling, and for understanding complex systems across many disciplines;
Golan’s current major project is a primer on the Foundations of Info-Metrics: Modeling, Inference and Imperfect Information. In this book he takes an interdisciplinary approach that lays out the foundations of info-metrics across the disciplines together with applications in the social, natural, medical, engineering and complexity sciences. This primer presents a framework for inference with finite, noisy and incomplete information. It shows that this framework is universal across disciplines though the problems and the specifics are different. It shows where, and how, these different features that are special to particular disciplines do come in. See http://info-metrics.org for a preview of the book.