Displaying 10 of 89 results for "Marisa Faggini" clear search
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.
Electrical and Computer Engineer (NTU, Athens), M.Sc. and Ph.D. on Artificial Intelligence (Univ. Paris VI, France). Formerly senior researcher in the Institute of Communication and Computer Systems (NTU, Athens). I have taught a variety of courses on intelligent, complex and biological systems and cognitive science. I have participated in numerous national and european R&D projects and I have authored about a hundred articles in journals, books and conference proceedings, at least half of them as a single author. I am frequent reviewer for journals, conferences and research grants. My research interests lie on the intersection of biological, complex and cognitive systems and applications.
Area: Complex Biological, Social and Sociotechnical Systems
Specific focus: Origins of intelligent behavior
I work as a Senior Researcher at the Centre for Modeling Social Systems (CMSS) at the Norwegian Research Centre (NORCE) sinde 2023. Before, I worked as an Expert Research Engineer at the CEA LIST Institute, Paris-Saclay University in France from 2013 to 2023. I hold a PhD in Artificial Intelligence degree from the Paul Sabatier University (France) and a PhD in Computer Engineering degree from the Ege University (Turkey).
I work in the field of complex adaptive systems, specializing in multi-agent systems, simulation, machine learning, collective intelligence, self-organization, and self-adaptation. I am interested in contributing to innovative projects and research in these domains.
My experience spans across multiple large-scale international research projects in areas such as green urban logistics, blockchain for nuclear applications, autonomous robotics systems and simulation of biological neural networks.
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
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.
Dissertation: Narrative Generation for Agent-Based Models
Abstract: This dissertation proposes a four-level framework for thinking about having agent-based models (ABM) generate narrative describing their behavior, and then provides examples of models that generate narrative at each of those levels. In addition, “interesting” agents are identified in order to direct the attention of researchers to the narratives most likely to be worth spending their time reviewing. The focus is on developing techniques for generating narrative based on agent actions and behavior, on techniques for generating narrative describing aggregate model behavior, and on techniques for identifying “interesting” agents. Examples of each of these techniques are provided in two different ABMs, Zero-Intelligence Traders (Gode & Sunder, 1993, 1997) and Sugarscape (Epstein & Axtell, 1996).
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.
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.
collective action
institutional emergence
evolution of institutions
community energy systems
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.
I am currently enrolled as a graduate student at UC3M, working towards a MS degree in Computational and Applied Mathematics. Upon completing my current program, my intention is to further my education in Applied Economics, with a specific focus on the intersection of Climate and Development Economics.
My research pursuits center around investigating the impacts of climate change on developing nations. Additionally, I am interested in studying the repercussions of fast fashion consumption, examining its effects on working conditions, the environment, and the overall well-being of individuals in the countries where these garments are manufactured. In my ongoing master’s thesis, I employ Agent-Based Modeling to simulate the attitudes of individual consumers towards fast fashion. The model captures behavioral shifts influenced by peers, social media, and governmental factors. This research aligns with my broader interests in comprehending public perspectives on global matters, underscoring the crucial influence of individual attitudes in confronting and finding solutions to these challenges.
Development Economics, Environmental Economics, Sustainability, Environment, Climate change, Climate justice, Energy, Clean Energy, Renewable Energy, Complex systems
Displaying 10 of 89 results for "Marisa Faggini" clear search