I have been working in the software implementation of different kinds of complex networks inspired in real-life populations. My software may be classified on several categories: complex networks, Aedes aegypti development, dengue epidemics, cultural behavior of populations. I am also researching in education of Deaf people in Colombia.

My research interest is to learn more about spatial and temporal interactions and relationships driving changes in our world. Spatial analysis and modelling and geographic information systems (GIS) can provide insights into complex problems such as climate change, landscape ecology and forestry by explicitly representing phenomena in their geographic context. My research focuses on the multidisciplinary nature of geographical information science (GIScience) to investigate the relationships between ecological processes and resulting spatial patterns.

Modeling and simulation of complex systems, particularly, interbank networks; economic models and critical phenomena modeling

network science; social networks; sociology; complex systems; ecological psychology; cognitive science; perception and action

General Question:
Without Central Control is self organization possible?

Specific Case:

Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?

Muaz is a Senior Member of the IEEE and has more than 15 years of professional, teaching and research experience. Muaz has been working on Communication Systems and Networks since 1995. His BS project in 1995 was on the development of a Cordless Local Area Network. In 1996, his postgraduate project was on Wireless Connectivity of devices to Computers. In addition to his expertise as an Communications engineer, his areas of research interest are in the development of agent-based and complex network-based models of Complex Adaptive Systems. He has worked on diverse case studies ranging from Complex Communication Networks, Biological Networks, Social Networks, Ecological system modeling, Research and Scientometric modeling and simulation etc. He has also worked on designing and developing embedded systems, distributed computing, multiagent and service-oriented architectures.

Computational Modeling of knowledge diffusion in organizational contexts.

Research Interests: Agent-based modeling, migrant integration, residential segregation

Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.

I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.

While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.