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Working on decision modeling in emergency healthcare. We are trying to design and develop service machine for emergency medical services.As a part of that, we are developing agent based models for emergency medical services
Malte Vogl is a senior research fellow at the Max Planck Institute of Geoanthropology with a PhD in Physics. Until recently, he worked as a research fellow and PI at the Max Planck Institute for the History of Science, in projects ranging from Digital Humanities work on the ancient perception of time and space in the cluster of excellency TOPOI, building and evalutation of research data infrastructures in context of the DARIAH project, large scale analysis of archival data for the history of the MPG project GMPG to the most recent, BMBF-funded work on method development for modelling knowledge evolution as a multilayered temporal network in the ModelSEN project.
History of Science, Evolution of Knowledge, Collective decision making
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.
Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.
I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.
While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.
I am a geographer interested in exploring tourism system dynamics and assessing tourism’s role in environmental sustainability using agent-based modelling (ABM). My current work focus is on human complex systems interactions with the environment and on the application of tools (such as scenario analysis, network analysis and ABM) to explore topics systems adaptation, vulnerability and resilience to global change. I am also interested in looking into my PhD future research directions which pointed the potential of Big Data, social media and Volunteer Geographical Information to increase destination awareness.
I have extensive experience in GIS, quantitative and qualitative methods of research. My master thesis assessed the potential for automatic feature extraction from QuickBird imagery for municipal management purposes. During my PhD I have published and submitted several scientific papers in ISI indexed journals. I have a good research network in Portugal and I integrate an international research network on the topic “ABM meets tourism”. I am a collaborator in a recently awarded USA NCRCRD grant project “Using Agent Based Modelling to Understand and Enhance Rural Tourism Industry Collaboration” and applied for NSF funding with the project “Understanding and Enhancing the Resilience of Recreation and Tourism Dependent Communities in the Gulf”.
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis, using mixed and integrative methods.
Recent projects include: 1) Studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) Indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
Paul Hart BSc (Liverpool), BA (Open University), PhD (Liverpool), MAE, FLS, FMBA. From 1973-1976 I worked on the Continuous Plankton Recorder (CPR) survey at the Oceanographic Laboratory, Edinburgh. From 1973 – 1976 I was employed by Nordreco AB (a Nestlé R & D company) in Sweden as a fishery biologist where he advised the Findus group on fish raw material supplies and assessed the future potential of aquaculture. In 1976 I moved to the University of Leicester as a lecturer in aquatic biology. My research focused on the foraging behaviour of fish with a side interest in marine commercial fisheries. I retired as Professor and Head of the Department of Biology and am now an Emeritus Professor. I was a Trustee of the Sir Alister Hardy Foundation for Ocean Science, which ran the Continuous Plankton Recorder Survey until it was merged with the Marine Biological Association: I then became a Trustee of the MBA. From 2010 – 2016 I was a member of the Science Advisory Board of Marine Scotland. I am co-author of Fisheries Ecology (1982) and co-editor of the two-volume Handbook of Fish Biology and Fisheries (2002). I was a co-editor of the journal Fish and Fisheries (Wiley) between 2000 and 2021.
IBMs of fisheries exploring management options and consequences of social behaviour.
I have been working in the software implementation of different kinds of complex networks inspired in real-life populations. My software may be classified on several categories: complex networks, Aedes aegypti development, dengue epidemics, cultural behavior of populations. I am also researching in education of Deaf people in Colombia.
Senior (Tenure-Track) Assistant Professor in Work and Organizational Psychology (WOP) at the Human Sciences Department of Verona University. My expertise lies in organizational behavior, individual differences and decision-making at work, and social dynamics in the applied psychology field. In the field of fundamental research my studies explore the role of individual antecedents (e.g., Personality traits, Risk attitudes, etc.) in relation to classic I/O models (e.g., Job Demands-Resources model, Effort-Reward model, etc.). My applied research focuses on the development of interventions and policies for enhancing decision-making, and in turn well-being and job performance. Finally, in industrial research, my research aims to better integrate cognitive and behavioral theories (e.g., Theory of Planned Behavior, Prospect theory, etc.) for designing predictive models – based on agents – of social and organizational behaviors.
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
Displaying 10 of 236 results for "Momme Von Sydow" clear search