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I obtained my undergraduate degree in Mathematics at Worcester College, Oxford University. I then worked for 9 years for the UK government before returning to university to study for a MSc and PhD at UCL. On leaving UCL I started working in the insurance industry, where I develop models of cyber catastrophe events.
Key research interests are how to build models of complex human behaviour.
My PhD research project was focussed on building a model of the process by which people develop the propensity to commit acts of crime or terrorism, from which came a computer simulation of the radicalisation process.
My current research interest is on creating models of cyber threats.
Flaminio Squazzoni is Full Professor of Sociology at the Department of Social and Political Sciences of the University of Milan and director of BEHAVE. He teaches “Sociology” to undergraduate students, “Behavioural Sociology” to master students and “Behavioural Game Theory” to PhD students. Untill November 2018, he has been Associate Professor of Economic Sociology at the Department of Economics and Management of the University of Brescia, where he led the GECS-Research Group on Experimental and Computational Sociology.
He is editor of JASSS-Journal of Artificial Societies and Social Simulation, co-editor of Sociologica -International Journal for Sociological Debate and member of the editorial boards of Research Integrity and Peer Review and Sistemi Intelligenti. He is advisory editor of the Wiley Series in Computational and Quantitative Social Science and the Springer Series in Computational Social Science and member of the advisory board of ING’s ThinkForward Initiative. He is former President of the European Social Simulation Association (Sept 2012/Sept 2016, since 2010 member of the Management Committee) and former Director of the NASP ESLS PhD Programme in Economic Sociology and Labour Studies (2015-2016).
His fields of research are behavioural sociology, economic sociology and sociology of science, with a particular interest on the effect of social norms and institutions on cooperation in decentralised, large-scale social systems. His research has a methodological focus, which lies in the intersection of experimental (lab) and computational (agent-based modelling) research.
Postdoctoral researcher at Institute of Economics, Polish Academy of Sciences and in Macroprudential Research Division at National Bank of Poland. She graduated in Mathematics (Jagiellonian University, Poland) and in Economics (University of Alcala, Spain). In 2017 she obtained Fulbright Advanced Research Award. In the United States, she carried out research on systemic risk and complex systems. Her doctoral dissertation was about the measurement and modeling of systemic risk using simulation methods and complex systems approach (the results to be published by Palgrave Macmillan US). Previously, she gained experience on agent-based modeling while working with Juan Luis Santos on the European Commission FP 7 MOSIPS project (http://www.mosips.eu/).
Mathematics, complex systems, financial modeling, agent-based modeling, econometrics, macroprudential policies, systemic risk, cental banking
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.
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
Cristina Montañola Sales is an assistant professor at Institut Químic de Sarrià in Ramon Llull University, where she teaches subjects in ICT and statistics. She holds a PhD in Statistics and Operations Research and specializes in the investigation of novel quantitative methods for studying human behavior, such as agent-based models and spatio-temporal analysis. Her interdisciplinary research combines mathematics with social sciences, biomedicine and High-Performance Computing. She has studied various contexts, such as the dynamics of mobility of Gambian emigrants, demographic forecasting in South Korea, and ecological resilience of hunter-gatherers in India. Her research on tuberculosis transmissions and COVID-19 has advanced knowledge in epidemics, demographic dynamics and computational statistics. She has published articles and participated in international projects on simulation, parallel computing and global health.
validation, computer performace, epidemics, demography
I am an agent-based simulation modeler and social scientist living near Cambridge, UK.
In recent years, I have developed supply chain models for Durham University (Department of Anthropology), epidemiological models for the Covid-19 pandemic, and agent-based land-use models with Geography PhD students at Cambridge University.
Previously, I spent three years at Ludwig-Maximillians University, Munich, working on Human-Environment Relations and Sustainability, and over two and a half years at Surrey University, working on Innovation with Nigel Gilbert in the Centre for Research in Social Simulation (CRESS). The project at Surrey resulted in a book in 2014, “Simulating Innovation: Computer-based Tools for Rethinking Innovation”. My PhD topic, modeling human agents who energise or de-energise each other in social interactions, drew upon the work of sociologist Randall Collins. My multi-disciplinary background includes degrees in Operational Research (MSc) and Philosophy (BA/MA).
I got hooked on agent-based modeling and complexity science some time around 2000, via the work of Brian Arthur, Stuart Kauffman, Robert Axelrod and Duncan Watts (no relation!).
As an agent-based modeler, I specialize in NetLogo. For data analysis, I use Excel/VBA, and R, and occasionally Python 3, and Octave / MatLab.
My recent interests include:
* conflict and the emergence of dominant groups (in collaboration with S. M. Amadae, University of Helsinki);
* simulating innovation / novelty, context-dependency, and the Frame Problem.
When not working on simulations, I’m probably talking Philosophy with one of the research seminars based in Cambridge. I have a particular interests when these meet my agent-based modeling interests, including:
* Social Epistemology / Collective Intelligence;
* Phenomenology / Frame Problem / Context / Post-Heideggerian A.I.;
* History of Cybernetics & Society.
If you’re based near Cambridge and have an idea for a modeling project, then, for the cost of a coffee / beer, I’m always willing to offer advice.
I am a modeler scientist at CIRAD. As member of the Green Research Unit, I contribute to promote the Companion Modeling approach (http://www.commod.org). Through the development of CORMAS, a Framework for Agent-Based Models (http://cormas.cirad.fr), I have been focusing on the development and the use of multi-agent simulations for renewable resource management issues. I have been based several years in Brazil, at the University of Brasilia and at the PUC-Rio University, until 2014. I developed models related to environmental management, such as breeding adaptation to drought in the Uruguay or as breeding and deforestation in the Amazon. I am currently based in Costa Rica, firstly at the University of Costa Rica working on adaptation of agriculture and livestock to Climate Changes, and now at CATIE, working on coffe rust.
Participatory modeling, including collective design of model and interactive simulation
Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.
Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
Displaying 10 of 123 results Simulation clear