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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 courses and workshops on complexity-based modeling of socio-ecological systems, for training of researchers, practitioners, 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
I have a strong background in building and incorporating agent-based simulations for learning. Throughout my graduate career, I have worked at the Center for Connected Learning and Computer Based Modeling (CCL), developing modeling and simulation tools for learning. In particular, we develop NetLogo, the gold standard agent-based modeling environment for learners around the world. In my dissertation work, I marry biology and computer science to teach the emergent principles of ant colonies foraging for food and expanding. The work builds on more than a decade of experience in ABM. I now work at the Center for the Science and the Schools as an Assistant Professor. We delivered a curriculum to teach about COVID-19, where I incorporated ABMs into the curriculum.
You can keep up with my work at my webpage: https://kitcmartin.com
Studying the negative externalities of networks, and the ways in which those negatives feedback and support the continuities.
I studied Molecular Biology and Genetics at Istanbul Technical University. During my undergraduate studies I became interested in the field of Ecology and Evolution and did internships on animal behaviour in Switzerland and Ireland. I then went on to pursue a 2-year research Master’s in Evolutionary Biology (MEME) funded by the European Union. I worked on projects using computer simulations to investigate evolution of social complexity and human cooperation. I also did behavioural economics experiments on how children learn social norms by copying others. After my Master’s, I pursued my dream of doing fieldwork and investigating human societies. I did my PhD at UCL, researching cultural evolution and behavioural adaptations in Pygmy hunter-gatherers in the Congo. During my PhD, I was part of an inter-disciplinary Hunter-Gatherer Resilience team funded by the Leverhulme Trust. I obtained a postdoctoral research fellowship from British Academy after my PhD. I am currently working as a British Academy research fellow and lecturer in Evolutionary Anthropology and Evolutionary Medicine at UCL.
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.
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.
PhD in Physics
One year postdoctoral position at the Institute of Physics at the University of Puebla, Mexico
Two year postdoctoral position at the Institute of Physics, University of Mexico, Mexico.
Working since 2007 as a professor and researcher at the University of Mexico City, Mexico.
Complex systems
Yiyu Wang is a PhD student in Center for Spatial Analysis and Policy (CSAP), at University of Leeds. Currently her research interests are the forward-looking simulation model of pedestrian evacuating behaviours especially in emergency situations incorporating Bayesian game theory within multi-agent systems, and their interactions with other social factors.
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.
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.
Raquel Guimaraes is a Postdoctoral Research Scholar at IIASA with support from the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES). She is hosted by the Advanced Systems Analysis (ASA), Risk and Vulnerability (RISK), and World Population (POP) programs. Dr. Guimaraes is currently on sabbatical leave from her appointment as an Adjunct Professor in the Economics Department at the Federal University of Paraná (Brazil), where she carries out research on, as well as teaching, economic demography, development microeconomics and applied microeconometrics.
In her research at IIASA, Dr. Guimaraes aims to contribute to the extant literature and to policy-making by offering a case study from Brazil, examining whether and how individual exposure to floods did or not induce affected migration in a setting with intense urbanization, the city of Governador Valadares, in the State of Minas Gerais. To elucidate the role of vulnerability at the household-level in mediating the relationship between mobility and floods, she will rely on causal models and simulation analysis. Her study is aligned with and will have support from, the Brazilian Network for Research on Global Climate Change (Rede Clima), which is an important pillar in support of R&D activities of the Brazilian National Climate Change Plan.
Dr. Guimaraes graduated from the Federal University of Minas Gerais, Brazil, in 2007 with degrees in economics. She completed an MA degree in International Comparative Education at Stanford University (2011) and earned a doctorate in demography from the Federal University of Minas Gerais in 2014.
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