Displaying 10 of 46 results for "Rick L Riolo" clear search
Fabian Adelt graduated in computer-sciences with a minor in sociology of technology (degree: Diplom-Informatiker) at TU Dortmund University in 2011. Currently, he is research fellow at the Technology Studies Group and involved in the project “Collaborative Data- and Risk-Management in Future Grids – A Simulation Study” (KoRiSim). Between 2012 and 2015 he worked on the project “Mixed Modes of Governance as a Means of Risk Management in Complex Systems” (RiskSim). His research interests entail agent-based modelling and simulating of socio-technical systems, especially focussing on governance issues and actors’ reactions on interventions. Experience covers the fields of mobility and energy.
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
I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).
• GIS Analyst / GIS Specialist: Experienced in applying GIS tools and spatial analysis techniques to
support decision-making in urban planning, environmental management, transportation, and infrastructure
projects. Skilled in producing high-quality maps, conducting spatial analysis, and delivering actionable
geospatial insights for operational and policy use.
• Geospatial Data Scientist: Specialized in developing spatial predictive models by integrating machine
learning and geospatial data to perform risk assessment, suitability analysis, and forecasting using large-
scale datasets such as satellite imagery, climate variables, and land-use data.
• Spatial Data Engineering & Processing: Strong ability to manage and preprocess complex geospatial
datasets, including raster and vector data, DEMs, remote sensing products, and climate projections, with
rigorous attention to spatial reference systems, accuracy, and data quality control.
• GIS Workflow Automation & Optimization: Proven experience in automating geospatial workflows
using ArcGIS Pro, ArcPy, ModelBuilder, FME (ETL), and Python to improve efficiency in spatial analysis,
data processing, and large-scale mapping tasks.
• Remote Sensing & Earth Observation Analysis: Proficient in satellite imagery processing and analysis,
including cloud masking, spectral analysis, vegetation indices, land cover classification, and temporal
change detection using Google Earth Engine and Python.
• Geospatial Visualization & Cartography: Skilled in producing professional-grade thematic maps, spa-
tial dashboards, and web-based geovisualizations to communicate complex geospatial patterns to both
technical and non-technical stakeholders.
• Cross-Disciplinary Collaboration: Experienced working with multidisciplinary teams across academia,
government, and industry to deliver geospatial solutions for planning, environmental risk assessment, and
policy-driven decision-making.
Elizabeth Hunter received a BA in Mathematics and Economics at Boston University in 2011. She worked as a health economics researcher at Research Triangle Institute for three years where she worked on a team that developed the risk adjustment models for the US health insurance exchanges. She attended the University of Limerick and received an MSc in Mathematical Modelling in 2015. She completed a PhD at Technological University Dublin. Her PhD research focuses on agent-based simulations for infectious disease epidemiology with the goal of creating an agent-based simulation of Ireland. Elizabeth is currently working on the Precise4Q as a Postdoctoral researcher working on predictive modelling in stroke.
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 an agent-based modeller at the James Hutton Institute in Scotland. I specialise in large-scale modelling of social and socio-ecological systems, with a particular focus on simulating stressors and process that could give rise to transformational change. To date, my research has focused on food and agricultural systems, rural economies, and the WASH sector, with much of it informed by firsthand fieldwork in Africa, Asia, and Europe. I am also interested in leveraging open science, participatory research, quantitative ethnography, and grounded theory within modelling processes to collaboratively generate nuanced insights into individual behaviour and societal dynamics. I received the Open Science Award from the International Land Use Study Centre in 2023 for such work. I currently co-lead the European Social Simulation Association’s Special Interest Group on Modelling Transformative Change.
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.
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Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
Displaying 10 of 46 results for "Rick L Riolo" clear search