Hang Xiong Member since: Tuesday, February 14, 2012 Full Member


Research fellow at the Agricultural Economics and Policy Group at ETH Zurich.

Malik Koné Member since: Thursday, January 21, 2016

Master in mathematics and didactics

Agent Based Modeling (ABM), Agent Based Social System (ABSS), Multi-Agent Systems (MAS), Bayesian learning, Social networks Analysis (SNA), Socio ecological Dynamics.

Xiaotian Wang Member since: Friday, March 28, 2014

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.

Eo SeungWon Member since: Thursday, August 03, 2017 Full Member Reviewer

B.A. Urban Studies, UC Berkeley., MSc. Geographic Information Science, Seoul National University.

GIS enthusiast and ABM practitioner

Urban Mobility
Machine Learning
Social Network Analysis
Crime Simulation

MV Eitzel Solera Member since: Sunday, May 21, 2017 Full Member Reviewer

I am a data scientist employing a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I am also working to apply Science and Technology Studies to my modeling processes in order to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling, both teaching mapping and modeling skills as well as analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis. Recent projects include: 1) studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis).

Hassan Bashiri Member since: Tuesday, April 28, 2015 Full Member


As an Assistant Professor I am a scientific member at the Department of Computer Science in Hamedan University of Technology.
I have completed my Ph.D. in Futures Studies as an interdisciplinary field. My background comes from computer science.

Complex Systems, Social Modeling and Simulation
Enginnering the Futures

Tom Brughmans Member since: Wednesday, September 24, 2014 Full Member Reviewer

PhD in Archaeology, University of Southampton (completion 13-10-2014), MSc Archaeological Computing (Spatial Technologies), University of Southampton, MA Archaeology, University of Leuven, BA Archaeology of Syro-Palestine, University of Leuven

My research aims to explore the potential of network science for the archaeological discipline. In my review work I confront the use of network-based methods in the archaeological discipline with their use in other disciplines, especially sociology and physics. In my archaeological work I aim to develop and apply network science techniques that show particular potential for archaeology. This is done through a number of archaeological case-studies: archaeological citation networks, visibility networks in Iron Age and Roman southern Spain, and tableware distribution in the Roman Eastern Mediterranean.

Giorgio Gosti Member since: Tuesday, January 13, 2015

Magistral Degree, Physics, University of Rome, “La Sapienza”, Italy, Dottorato, Computer Science and Mathemaatics, University of Perugia, Italy, PhD, Institute for Mathematical Behavioral Sciences, Social Science, University of California, Irvine

My research focuses pn the intersection between game theory, social networks, and multi-agent simulations. The objectives of this scientific endeavor are to inform policy makers, generate new technological applications, and bring new insight into human and non-human social behavior. My research focus is on the transformation of cultural conventions, such as signaling and lexical forms, and on many cell models models of stem cell derived clonal colony.

Because the models I analyze are formally defined using game theory and network theory, I am able to approach them with different methods that range from stochastic process analysis to multi-agent simulations.

Matthew Oldham Member since: Friday, June 17, 2016

Bachelor of Economics (tons), MAIS - Computational Social Science

I am a Ph.D. candidate in Computational Social Science (CSS) program at George Mason (GMU). I hold a MAIS from GMU and a Bachelor of Economics from the University of Tasmania. My research interests are the application of ABMs, network analysis, and machine learning to financial markets. My email address and website is [email protected] and

I am interested in using agent-based model to understand the behavior of financial markets

Cristina Chueca Del Cerro Member since: Friday, May 15, 2020

I’m a PhD researcher at the University of Glasgow working on modelling national identity polarisation on social media platforms using ABMs.

agent-based models, social networks, python, R, NetLogo

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