I’m a PhD researcher at the University of Glasgow working on modelling national identity polarisation on social media platforms using ABMs.
agent-based models, social networks, python, R, NetLogo
publons.com/researcher/2900535/juan-moises-de-la-serna | orcid.org/0000-0002-8401-8018 |PhD in Psychology US.es and Master in Neuroscience and Behavioral Biology UPO.es |Part Time Online Adjunct Faculty UNIR.net |The most read author in Spain in 2020|Expert in Quality Agency for Higher Education of Latvia AIKA.LV |Nowadays, my research focuses on Potential Factors Influencing COVID-19 and Short- & Long-Term Psychological and Neurological complications after SARS-CoV-2 infection in humans
Social change with COVID-19
Farzaneh Davari is a social science researcher who has worked in many diverse fields, including agriculture, conflict, health, and human rights, just to name a few. Currently, she is a Ph.D. candidate in Computational Social Science, focusing on social-ecological complex systems and applying computational science and Agent-Based Modeling to understand resilience procedure through self-organizing and learning. Meanwhile, she is a designer and instructor of the online graduate level course of Decision-making in Complex Environments in Virginia Tech.
Social-ecological complex system, resilience-building, conflictual environment
Research Assistant Professor at the Virginia Modeling, Analysis and Simulation Center at Old Dominion University. I work in the Storymodelers research group at VMASC where we use computational modeling approaches to try to understand complex social issues. Our main project is currently focused on modeling the dynamics of how host communities respond to the rapid influx of forced migrants.
Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.
Grant Snitker, M.A., is a doctoral candidate in archaeology at Arizona State University and a National Science Foundation Graduate Research Fellow. His research focuses on prehistoric uses of controlled fire, settlement history, and environmental change. Snitker approaches these topics through geoarchaeology, archaeological survey methods, GIS modeling, and landscape/fire ecology. He currently works in Spain investigating the origins and evolution of early farming communities (7,700–4,500 cal. BP) and how they used fire to create productive agricultural landscapes. Snitker also applies his knowledge of archaeology and fire ecology as an archaeological resource advisor on wildland fire incidents here in Arizona. He works alongside firefighters to protect archaeological sites from wildfires and potentially destructive firefighting activities.
Envrionmental Archaeology, Fire Ecology, GIS, Agent-based modeling, Geoarchaeology
Eric has graduate degrees in urban planning and policy and sociology and an undergraduate degree in biology. He has worked on multiple collaborative and interdisciplinary projects and is skilled at engaging communities and other stakeholders. He is adept at qualitative research and has earned a Certificate in Geospatial Analysis and Visualization, demonstrating proficiency in Adobe Suite, ArcGIS, agent-based modeling and system dynamics modeling. He is currently writing manuscripts for publication based on his work on motivating energy retrofit decisions, energy-related urban planning, municipal decision-making on infrastructure investments, and other work on resilience and sustainability.
Conducts urban planning and policy research on energy efficiency, environmental, and infrastructure decision making.
I am a data scientist employing a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I am also working to apply Science and Technology Studies to my modeling processes in order to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling, both teaching mapping and modeling skills as well as 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. 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).
My research interests stand between natural resource management and ecological economics. The aim of my PhD project responds to the increasing demand for cross-disciplinary agent-based models that examine the disjunction between economic growth and more sustainable use of natural resources.
My research attempts to test the effectiveness of different governance and economic frameworks on managing natural resources sustainably at both regional and national levels. The goal is to simulate how communities and institutions manage the commons in complex socio-ecological systems through several case-studies, e.g. rainforest management in Australia. It is hoped that the models will highlight which combination of variables lead to positive trends in both economic and environmental indicators, which could stimulate more sustainable practices by governments, private sectors and civil society.
Amineh Ghorbani is an assistant professor at the Engineering Systems and Services Department, Delft University of Technology, the Netherlands. She is also an affiliated member of the “Institutions for Collective Action” at Utrecht University. She obtained her M.Sc. in Computer Science (Artificial intelligence) from University of Tehran (Iran) (2009, honours) and her PhD from Delft University of Technology (2013, cum laude).
During her PhD, Amineh developed a meta-model for agent-based modelling, called MAIA, which describes various concepts and relations in a socio-technical system. This modelling perspective helped her develop a modelling paradigm that she refers to as institutional modelling.
Her current area of research is understanding the emergence and dynamics of institutions (set of rule organizing human society) using modelling. She is interested in how bottom-up collective action emerges and how institutions emergence and change within communities.
evolution of institutions
community energy systems