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

I’m a PhD researcher at the University of Glasgow working on modelling political polarisation on social media platforms suing agent-based models

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

María Del Castillo Member since: Tuesday, February 18, 2014


Archaeological Simulation of Social Interactions, mainly between hunter gatherers societies.

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

Annie Waldherr Member since: Monday, February 10, 2014


Annie Waldherr is a postdoctoral researcher at the Free University of Berlin, Institute for Media and Communication Studies. In 2012, she received her PhD for her dissertation on the dynamics of media attention. Her research interests include modeling public spheres, political online communication as well as science and technology discourses.

Peer-Olaf Siebers Member since: Friday, February 15, 2019 Full Member

I am an Assistant Professor at the School of Computer Science, University of Nottingham, UK.

My main research interest is the application of computer simulation to study human-centric complex adaptive systems. I am a strong advocate of Object Oriented Agent-Based Social Simulation. This is a novel and highly interdisciplinary research field, involving disciplines like Social Science, Economics, Psychology, Operations Research, Geography, and Computer Science. My current research focusses on Urban Sustainability and I am a co-investigator in several related projects and a member of the university’s “Sustainable and Resilient Cities” Research Priority Area management team.

Morteza Mahmoudzadeh Member since: Sunday, May 10, 2015 Full Member Reviewer


Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.

Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory

Muaz Niazi Member since: Sunday, June 07, 2009 Full Member Reviewer

BE (Hons), MS CS, PhD

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.

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.

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.

Gary Polhill Member since: Wednesday, September 05, 2012 Full Member

BA (Hons) Computing and Artificial Intelligence (Sussex), Ph. D. Guaranteeing Generalisation in Neural Networks (St. Andrews)

Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.

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