Xiaoyi Yuan Member since: Monday, January 30, 2017

PhD in Computational Social Science

Manuel Castañón-Puga Member since: Wednesday, October 16, 2019 Full Member

Ph.D. Computer Science, Universidad Autónoma de Baja California, México., MSC Computer Science, Tecnológico Nacional de México, México., ENG Industrial, Tecnológico Nacional de México, México.

I´m a full Professor at Chemistry and Engineering School at the Universidad Autónoma de Baja California in Mexico. I teach computer sciences and software engineering in graduate and undergraduate academic programs.

  • Computational science
  • Computational social science
  • Social-inspired ICT
  • Social computation
  • Agents technology
  • Computational intelligence and hybrid-intelligent agents
  • Complexity and complex systems
  • Multi-agent systems
  • Computational modeling
  • Context-oriented programming
  • Knowledge Management
  • Software engineering

Noha Nagi Member since: Tuesday, October 28, 2014

Bachelor in statistics, Preparing MSC in social science computing

Tom Briggs Member since: Tuesday, December 13, 2016 Full Member Reviewer

MPS, Industrial/Organizational Psychology, BA, Psychology

PhD Student, Computational Social Science
Department of Computational and Data Sciences
George Mason University
Fairfax, VA, USA

I use ABM to study organizations, leadership, employee behavior and performance, and the social/psychological theories addressing workplace behavior and outcomes.

I have also used ABM to explore mass violence, active shooters, and mass shootings, including the spread of mass violence and its antecedents.

Francisco Grimaldo Member since: Sunday, November 03, 2013

PhD. in Computer Science

My main research interests are agent-based modeling, simulation of social complexity, computational social choice, distributed systems and applied artificial intelligence.

David Earnest Member since: Saturday, March 13, 2010 Full Member Reviewer

Ph.D. in political science (2004), M.A. in security policy studies (1994)

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.

Farzaneh Davari Member since: Tuesday, October 09, 2018 Full Member

Farzaneh Davari is a social science researcher who has worked in many diverse fields, including agriculture, conflict, health, and human rights, just to name a few. Currently, she is a Ph.D. candidate in Computational Social Science, focusing on social-ecological complex systems and applying computational science and Agent-Based Modeling to understand resilience procedure through self-organizing and learning. Meanwhile, she is a designer and instructor of the online graduate level course of Decision-making in Complex Environments in Virginia Tech.

Social-ecological complex system, resilience-building, conflictual environment

Andrew Crooks Member since: Monday, February 09, 2009 Full Member

Andrew Crooks is an Associate Professor with a joint appointment between the Computational Social Science Program within the Department of Computational and Data Sciences and the Department of Geography and GeoInformation Science, which are part of the College of Science at George Mason University. His areas of expertise specifically relate to integrating agent-based modeling (ABM) and geographic information systems (GIS) to explore human behavior. Moreover, his research focuses on exploring and understanding the natural and socio-economic environments specifically urban areas using GIS, spatial analysis, social network analysis (SNA), Web 2.0 technologies and ABM methodologies.

GIS, Agent-based modeling, social network analysis

Matteo Morini Member since: Friday, February 22, 2019 Full Member

PhD, Computer Science, ENS Lyon, MS, Economics, University of Turin
This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.