Displaying 10 of 11 results Python clear search
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.
I’m max hart, a seasoned academic consultant specializing in Assignments & dissertation Help at New Assignment Help UK. Struggling to complete coding tasks on time can be stressful, especially when Python concepts start getting complex. From basic syntax to advanced topics like data structures, machine learning, and automation, expert guidance can make a real difference. Many students now rely on Help With Python Assignment to understand logic clearly and submit well-structured solutions without errors. With professional Assignment Help uk, learners receive personalised support, plagiarism-free work, and timely delivery that aligns with university standards. This kind of assistance not only improves grades but also builds confidence in programming skills, making future projects and exams much easier to handle.
• 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.
Olá, I’m Daniel! 👋
I’m an R(esearcher) at the University of São Paulo (USP) working on complex systems and data science. My family name is actually KACHvartanian, but I go by Vartanian to save everyone from a linguistic workout.
I love building open-source tools, being part of active communities, and working with the R, Python, and NetLogo programming languages. When I’m not coding, I’m likely watching a good movie, seeing friends, wandering through new places, or tinkering with some obscure new thing that may or may not go anywhere.
PhD student at Victoria University of Wellington.
Modelling social-ecological systems and governance of the commons. Currently working in the Python and Java ecosystems. Public code hosted at https://codeberg.org/tkristinwilson
I’m am computational social scientist and data scientist with a background in political communication and social media research that specialises in agent-based simulation, social network analysis and the computational study of social media behaviour.
For the last three years, I was a Research Associate in Computational Social Science at Durham University designing and evaluating algorithms for realistic artificial social networks in Julia by creating a taxonomy of existing generator papers, accessible as an interactive, open-access database (RShiny dashboard), in addition to exploring the interdependencies of social network’s structural properties.
For my PhD in Politics at Glasgow University (2023) I designed and implemented an agent-based model of online polarisation and offline protest mobilisation, applied to Catalonia’s independence movement in Spain.
agent-based models, social networks, echo chambers, polarisation, social influence, protest mobilisation
NetLogo, R, Julia and Python
Leonardo Grando is a Ph.D. at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
Mathematical modeling
agent-based modeling
coupling of agent-based models and mathematical models
machine learning algorithms
deep learning algorithms
Statistical inference
infectious diseases modeling
I’ve been building cyberinfrastructure and research software for computational social science and the study of complex adaptive systems at Arizona State University since 2006. Past and current projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, Synthesizing Knowledge of Past Environments (SKOPE), the Port of Mars, and CoMSES Net, where I serve as co-director and technical lead.
I also work to improve the state of open, transparent, reusable, and reproducible computational science as a Carpentries instructor and maintainer for the Plotting and Programming in Python and Good Enough Practices for Scientific Computing lessons, currently co-chair the Consortium of Scientific Software Registries and Repositories and Open Modeling Foundation Cyberinfrastructure Working Group, and serve on the DataCite Services and Technology Steering Group and CSDMS’s Basic Model Interface open source governance council.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable, reproducible, and interoperable scientific computation.
Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.
Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory
Displaying 10 of 11 results Python clear search