Displaying 10 of 193 results for "Michel De Garine-Wichatitsky" clear search
Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.
In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’
To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.
Aniruddha Belsare is a disease ecologist with a background in veterinary medicine, interspecific transmission, pathogen modeling and conservation research. Aniruddha received his Ph.D. in Wildlife Science (Focus: Disease Ecology) from the University of Missouri in 2013 and subsequently completed a postdoctoral fellowship there (University of Missouri, May 2014 – June 2017). He then was a postdoctoral fellow in the Center for Modeling Complex Interactions at the University of Idaho (June 2017 - March 2019) and later a Research Associate with the Boone and Crockett Quantitative Wildlife Center, Michigan State University (March 2019 - Jan 2021). He was a Research Scientist in the Civitello Disease Ecology Lab at Emory University from Jan 2021 to Jan 2023. Currently, Aniruddha is an Assistant Professor of Disease Ecology at the College of Forestry, Wildlife & Environment / College of Veterinary Medicine at Auburn University.
My research interests primarily lie at the interface of ecology and epidemiology, and include host-pathogen systems that are of public health or conservation concern. I use ecologic, epidemiologic and model-based investigations to understand how pathogens spread through, persist in, and impact host populations. Animal disease systems that I am currently working on include canine rabies, leptospirosis, chronic wasting disease, bighorn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), chytridiomycosis, and Lyme disease.
I am a marine environmental scientist by training (U Oldenburg, 2001) with a PhD in atmospheric physics (U Wuppertal, 2005) and a strong modeling focus throughout my career.
I have built models (C, C++) for understanding the regional transitions from hunting-gathering subsistence to agropastoral life styles throughout the world. The fundamental principle of these models is to consider aggregate traits of populations, such as the preference for a subsistence style. I applied these models to the European “Wave of Advance”, to the disintegration of the urban Indus civilisation and to the differential emergence of agropastoralism in the Americas versus Europe, but also globally. An interesting outcome of these models are global and reginoally resolved prehistoric CO2 emissions caused by the land use transitions.
I have built and applied models for understanding the ecological relations and biogeochemical flows through the North Sea ecosystem. Also for this research I apply trait-based models, looking at traits such as vertical positioning or energy allocation. As an outcome, I have, e.g., estimated the biomass of blue mussels in the North Sea and quantified the effect of Offshore Wind Farm biofouling on the sea’s produtivity.
I led the development of the Earth System coupler MOSSCO, leveraging ESMF technologies. I like to rip legacy models apart and reconstruct them with interoperability and reusability by design. I contribute to building the next-generation modular hurricane forecasting system.
As a member of the Open Modeling Foundation (OMF), I am an evangelist of good scientific software practices, and educate and publish about improving underlying assumptions, stating clear purposes, keeping models simple and aquiring tools to further good practices.
Ms. Stringfellow is a PhD candidate whose goal is to identify ways to build and leverage the natural support systems of people who are experiencing problems related to their illicit drug use. Her current interest is in how these support systems operate in small towns with limited formal resources for quitting. To that end, she recently began conducting in-depth qualitative interviews for her dissertation in a semi-rural county in eastern Missouri. These interviews will be used to build an agent-based model, a type of dynamic simulation modeling that can be used to represent heterogeneous actors with multiple goals and perceptions. As a research assistant and dissertation fellow with the Social System Design Lab, she has also been trained in system dynamics, an aggregate-level dynamic simulation modeling method.
Prior to joining the PhD program, she worked as a research associate at the Boston Health Care for the Homeless Program from 2008-2012. BHCHP is an exemplar model of providing patient-centered care for people who have experienced homelessness. There, she gained significant experience in managing research projects, collecting qualitative and quantitative data, and program evaluation. She earned her MSW from the University of Michigan in 2007, with a focus on policy and evaluation in community and social systems, and a BA in sociology in 2005, also at the University of Michigan. Ms. Stringfellow was born and raised in a small town in Michigan.
The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.
My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.
Mazaher Kianpour is a PhD candidate at NTNU. He holds a Bachelor’s degree in Computer Engineering (Software) from the Payame Noor University. He obtained his Master’s degree in Architecture of Computer Systems from Shahid Beheshti University, Tehran, Iran. He started his PhD in Information Security at NTNU in May 2018. His PhD research lies at the intersection of economics and information security with a socio-technical perspective. He has several years of work experience at Tehran University of Medical Sciences, and his professional training includes Computer Networks, Cybersecurity and Risk Management.
My main research interest is modelling of information security, business operations and deterrents in complex ICT ecosystem. I will in particular focus on the complex interaction between various stakeholders and actors in the information security business domain. In order to model and better understand the information security ecosystem, I rely on agent-based simulation and quantitative modelling techniques such as stochastic modelling, discrete event simulations and game theory. Of particular interest is to gain increased understanding on how various security threats and measures influence business operations in the digital ecosystem.
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.
I am Professor in Computational Resilience Economics at the University of Twente (the Netherlands), which I joined in 2010. In September 2017 I also joined University of Technology Sydney (Australia) as Professor of Computational Economic Modeling working with spatial simulation models to study socioeconomic impacts of disasters and emergence of resilience across scales. I was honored to be elected as a Member of the De Jonge Akademie of the Royal Dutch Academy of Sciences (DJA/ KNAW in 2016) and of Social Sciences Council (SWR/KNAW in 2017). From 2009 to 2015 I have been working part-time as an economist at Deltares – the leading Dutch knowledge institute in the field of water management – specializing in economics of climate change, with focus on floods and droughts management.
I am interested in the feedbacks between policies and aggregated outcomes of individual decisions in the context of spatial and environmental policy-making. The issue of social interactions and information diffusion through networks to affect economic behavior is highly relevant here. My research line focuses on exploring how behavioral changes at micro level may lead to critical transitions (tipping points/regime shifts) on macro level in complex adaptive human-environment systems in application to climate change economics. I use agent-based modelling (ABM) combined with social science methods of behavioral data collection on individual decisions and social networks. This research line has been distinguished by the NWO VENI and ERC Starting grants and the Early Career Excellence award of the International Environmental Modeling Society (iEMSs). In 2018 I was invited to serve as the Associate Editor of the Environmental Modelling & Software journal, where I have been a regular Member of the Editorial Board since 2013.
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.
Displaying 10 of 193 results for "Michel De Garine-Wichatitsky" clear search