Understanding, Tracing, and Forecasting Change across Time, Space, and Cultures
Professor Eduardo Lopez
Computational and Data Sciences Department, George Mason University
Eduardo Lopez is an Assistant Professor of Computational Social Sciences at George Mason University, in the Department of Computational and Data Sciences. He is a specialist in complex network theory, scaling theory, canonical ensembles, percolation theory, graphs and graph algorithms, stochastic processes, and large scale data handling, among others. Prof. Lopez applies those techniques to systems that can be approached in an interdisciplinary way with the tools of network science, stochastic processes, and big data. In this broad context, he has a particular interest in flow processes on networks. Another highly related interest is the search for quantitative laws in social, economic, and technological systems. Prof. Lopez also holds Visiting Research Fellowships in Complexity Science at the CABDyN Complexity Centre and at Green Templeton College, both at the University of Oxford. He is published widely in network science and has advanced the state of the art in analytic and computational techniques for network analysis.