Paul Van Liedekerke Member since: Thursday, May 31, 2018

Interested in numerical models and new conceptual ideas, applications from industry to medicine.

I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.

I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.

The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).

Gayanga Herath Member since: Wednesday, March 14, 2018 Full Member

Master's degree in Information Technology, Management & Organisational Change at Lancaster University, Bachelor of Engineering (BEng) (Hons) in Computer Networks And Security at Staffordshire University, PhD in Organizational Cognition at University of Southern Denmark (Present)

An ambitious and driven individual with knowledge and project experience in computer networks and security (BEng (Hons)), along with a masters degree at a top 10 UK university in the domain of IT, management and organizational change with a distinction, and is currently working as a Ph.D. Research fellow in Denmark.

Current Ph.D. Project - Work Improvisation, looking into more flexible and plastic management through cognition.

Organizational Cognition
Organizational behaviour
Organizational change
Recruitment & Selection
Distribted Cognition

Elpida Tzafestas Member since: Sunday, December 14, 2014

Electrical and Computer Engineering Degree, DEA (MSc) in Artificial Intelligence, PhD in Artificial Intelligence

Electrical and Computer Engineer (NTU, Athens), M.Sc. and Ph.D. on Artificial Intelligence (Univ. Paris VI, France). Formerly senior researcher in the Institute of Communication and Computer Systems (NTU, Athens). I have taught a variety of courses on intelligent, complex and biological systems and cognitive science. I have participated in numerous national and european R&D projects and I have authored about a hundred articles in journals, books and conference proceedings, at least half of them as a single author. I am frequent reviewer for journals, conferences and research grants. My research interests lie on the intersection of biological, complex and cognitive systems and applications.

Area: Complex Biological, Social and Sociotechnical Systems
Specific focus: Origins of intelligent behavior

Garry Sotnik Member since: Friday, April 06, 2018 Full Member Reviewer

GARRY SOTNIK is a Lecturer with the Sustainability Science and Practice Program in the School of Earth, Energy and Environmental Sciences. He is a systems scientist with research focused on identifying robust strategies in contexts defined by deep uncertainty and global climate change. Garry develops and implements agent-based computer simulation models that explore co-evolutionary interactions among human cognition and behavior, on the one end, and biophysical conditions, on the other. He has experience designing and teaching courses on agent-based modeling and on different approaches to modeling coupled human and natural systems. Garry holds a Ph.D. in Systems Science from Portland State University and an M.A. in Economics and a B.S. in Management from Boston University.

agent-based modeling, cognition

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

Moira Zellner Member since: Friday, December 06, 2013 Full Member

PhD, Urban and Regional Planning, University of Michigan, Ann Arbor

Moira Zellner’s academic background lies at the intersection of Urban and Regional Planning, Environmental Science, and Complexity. She has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological and behavioral factors influence the emergence and impacts of a range of complex socio-ecological systems problems, where interaction effects make responsibilities, burdens, and future pathways unclear. Her research also examines how participatory complex systems modeling with stakeholders and decision-makers can support collaborative policy exploration, social learning, and system-wide transformation. Moira has taught a variety of workshops on complexity-based modeling of socio-ecological systems, for training of both scientists and decision-makers in the US and abroad. She has served the academic community spanning across the social and natural sciences, as reviewer of journals and grants and as a member of various scientific organizations. She is dedicated to serving the public through her engaged research and activism.

Applications of agent-based modeling to urban and environmental planning
Participatory modeling

Talal Alsulaiman Member since: Friday, February 27, 2015

Bachelor of Science in Systems Engineering, Master of Science in Industrial Engineering, Master of Science in Financial Engineering

In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.

Tuong Manh Vu Member since: Wednesday, May 16, 2018

I received my BSc, MSc, and PhD from the University of Nottingham. My PhD focuses on the Agent-Based Modelling and Simulation (ABMS) of Public Goods Game (PGG) in Economics. In my thesis, a development framework was developed using software-engineering methods to provide a structured approach to the development process of agent-based social simulations. Also as a case study, the framework was used to design and implement a simulation of PGG in the continuous-time setting which is rarely considered in Economics.

In 2017, I joined international, inter-disciplinary project CASCADE (Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies) to further pursue my research interest in strategic modelling and simulation of human-centred complex systems. CASCADE, funded by the US National Institutes of Health (NIH), aims to develop agent-based models and systems-based models of the UK and US populations for the sequential and linked purposes of testing theories of alcohol use behaviors, predicting population alcohol use patterns, predicting population-level alcohol outcomes and evaluating the impacts of policy interventions on alcohol use patterns and harmful outcomes.

Simone Righi Member since: Friday, June 08, 2018

I received a Ph.D. in Economics at the University of Namur (Belgium) in June 2012 with a thesis titled “Essays in Information Aggregation and Political Economics”.
After two years at the Research Center for Educational and Network Studies (Recens) of the Hungarian Academy of Sciences, I joined the Department of Economics “Marco Biagi” of the University of Modena and Reggio Emilia in January 2015 and then the Department of Agricultural and Food Sciences of the University of Bologna.
I am currently a Lecturer in Financial Computing at the Department Computer Science (Financial Computing and Analytics group) - University College London. Moreover I am an affiliated researcher of the DYNAMETS - Dynamic Systems Analysis for Economic Theory and Society research group and an affiliate member of the Namur Center for Complex Systems (Naxys).

My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.

Bashar Ourabi Member since: Sunday, March 12, 2017 Full Member Reviewer

Bsc Industrial Engineering, Masters of Public Administration/ Development Economics

Bashar Ourabi is a principle consultant at arabianconsult of Syria where he has been chairman since 2003. He holds Bsc. Eng., A Grad. Certificate in Project engineering from the University of Central Florida; and a MS. in Public Administration from the Doha Graduate Institute in Qatar.

Bashar completed his graduate studies at Doha Institute for Graduate Studies and his undergraduate studies at the Unversity of Central Florida. His research interests lie in the area of systems modelling, ranging from theory to design to implementation. He has collaborated actively with researchers in several other disciplines of computer science, system design, and bigData Artificial Intellegence, particularly BigData Expert System and Automated decision Making.

He has served on many international posts overlooking public infrastructure design and operations, varying from public transport, urban design and operations management. These posts spanned over the the US and the Middle East including Florida, UAE and Qatar.

Bashar has served on many conferences and workshop program committees and has succesfully delivered many corporate training programs..

Artificial Intellegence
Web Based Decision Making and Expert Systems
Fuzzy Logic
AgentBased Modelling
Discret Event Simulation
Corporate Support Systems

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