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I am interested in the dynamics of cultural transmission, especially in diffusion of religious innovations (concepts and practices) across a population. In my dissertation, I am targeting this issue while studying and modelling the development of Christian meal practices in the first four centuries CE across the Roman Mediterranean.
My research examines the most effective and efficient policies for renewable energy development using an approach that integrates input-output analysis, life cycle analysis, econometric, and agent-based modelling to estimate the impacts of the policies to economic, emission, extracted materials, renewable energy capacity and social acceptance.
I am interested in questions of method, and in the application of computational social models to a wide variety of national security questions (such as counterterrorism and counterinsurgency) as well as decision-making around complex natural resources such as water. My methods interest center on the use of qualitative social theory to inform the structure of computational social models, and the ways in which such models handle qualitative data. This raises questions around the nature of data and the ways in which computational social models convey information to decision-makers.
Development and usage of demographic microsimulation tools and applications, in particular combining statistical modeling and social theory
PhD student in economics
BIGSSS-Departs PhD Fellow
Bremen International Graduate School of Social Sciences / Jacobs University (Germany)
PhD project: Residential Segregation and Intergenerational Immigrant Integration: A Schelling-Esser Model
Italian PhD fellow, fond of social complexity and agent-based modeling, applied to residential segregation and integration processes
Research Interests: Agent-based modeling, migrant integration, residential segregation
Social Simulation using MABS. At present, research to expand SocLab in order to model emotions and morality.
Others: Organisations, Soft Systems, Planning methodologies.
Gerd Wagner is Professor of Internet Technology at Brandenburg University of Technology, Cottbus, Germany. After studying Mathematics, Philosophy and Informatics in Heidelberg, San Francisco and Berlin, he (1) investigated the semantics of negation in knowledge representation formalisms, (2) developed concepts and techniques for agent-oriented modeling and simulation, (3) participated in the development of a foundational ontology for conceptual modeling, the Unified Foundational Ontology (UFO), and (4) created a new Discrete Event Simulation paradigm, Object Event Modeling and Simulation (OEM&S), and a new process modeling language, the Discrete Event Process Modeling Notation (DPMN). Much of his recent work on OEM&S and DPMN is available from sim4edu.com.
Modeling and simulation of agents and other discrete systems.
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
Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In Fall 2023, he is a Visiting Research Scholar at SUNY Binghamton in NY.
agent-based simulations
social network analysis
complex systems
big data analysis
statistical learning
computational social science
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