Displaying 10 of 277 results for "Jon Norberg" clear search
• 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.
Charlotte is an International PhD graduate originally from New Zealand who first came to ASU to pursue her PhD in Anthropology in Aug 2013, thanks to receiving a Science and Innovation Scholarship through the Fulbright Program. She holds a BS majoring in Genetics and a BA majoring in Anthropology from Otago University, New Zealand. She received her Masters in Anthropology in May 2015 and her PhD in Anthropology in 2022 both from ASU. Her main areas of interest are Human Migration, Migration Decision Making, and Environmental Perceptions.
At present she is an Assistant Research Scientist with the School of Complex Adaptive Systems at ASU where she is primarily focused on her roles as the administrative coordinator for CoMSES.NET and The Open Modeling Foundation. She is also adjunct Anthropology faculty at Phoenix College, and Chandler-Gilbert Community College teaching various undergraduate anthropology courses. She is deeply interested in how computational tools and technologies can be used to explore complex adaptive systems, explore possible futures, and better inform policy and decision makers at the leading edge of change.
My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.
Hello,
My name is Roberto and I am a graduate student at The Pennsylvania State University. I am in the “Information Sciences - Cybersecurity and Information Assurance program”, through which I discovered my interest in ABM. I am conducting my capstone research project on how to make ABM more effective in the disaster recovery planning process of IT companies. I am currently looking for interview candidates to conduct my research. If you or anyone you know have experience using ABM for disaster recovery planning in IT or tech, please reach out!
I learned about ABM through the Intelligent Agents course at Penn State, where we modeled everything from terrorist attacks to social relationships. I was immediately interested in ABM due to the potential and capabilities that it provides in so many areas. I hope to make ABM more popular in IT disaster recovery planning through my research, while learning more about ABM myself.
Cyber security
Agent-Based Modeling
Information Technology
Disaster Recovery
I hold a MA in Prehistory and a master degree in International Relations, both obtained at the Sapienza University of Rome. After this I obtained a PhD in Pre- and Protohistory and Aegean Archaeology from the University of Heidelberg in cotutelle de thèse with the University of Paris 1 Sorbonne Panthéon. Since 2018 I hold a permanent position as senior researcher at the Italian National Research Council. Prior to this I had worked as postdoctoral researcher at the Ruhr University of Bochum, University of Heidelberg, University of Amsterdam and University of Mainz.
I specialize in prehistoric archaeology (6 to 2 mill BC) with a focus on the Balkans and Central Mediterranean. My interest stretches from the relationship between past identities and material culture, large mobility patterns and cultural transmission to development of archaeological theory, network analysis and Agent-based Modelling, archaeological discourses in present day identity building and political uses of archaeology.
Improving agent models and architectures for agent-based modelling and simulation applied to crisis management. In particular modelling of BDI agents, emotions, cognitive biases, social attachment, etc.
Designing serious games to increase awareness about climate change or natural disasters; to improve civil engagement in sustainable urban planning; to teach Artificial Intelligence to the general public; to explain social phenomena (voting procedures; sanitary policies; etc).
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.
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.
My research focuses on building a systemic understanding of coupled human-natural systems. In particular, I am interested in understanding how patterns of land-use and land-cover change emerge from human alterations of natural processes and the resulting feedbacks. Study systems of interest include those undergoing agricultural to urban conversion, typically known as urban sprawl, and those in which protective measures, such as wildfire suppression or flood/storm impact controls, can lead to long-term instability.
Dynamic agent- and process-based simulation models are my primary tools for studying human and natural systems, respectively. My past work includes the creation of dynamic, process-based simulation models of the wildland fires along the urban-wildland interface (UWI), and artificial dune construction to protect coastal development along a barrier island coastline. My current research involves the testing, refinement, extension of an economic agent-based model of coupled housing and land markets (CHALMS), and a new project developing a generalized agent-based model of land-use change to explore local human-environmental interactions globally.
Displaying 10 of 277 results for "Jon Norberg" clear search