I am a developer for CoMSES Net as part of the Global Biosocial Complexity Initiative at Arizona State University. I work on improving model reuse, accessibility and discoverability through the development of the
comses.net website and the CoMSES bibliographic database (
catalog.comses.net). I also provide data analysis and software development advice on coupling models, version control, dependency management and data analysis to researchers and modelers.
My interests include model componentization, statistics, data analysis and improving model development and resuability practices.
I obtained a PhD in database information theory from the University of the West of Scotland in 2015, and have been a researcher at the James Hutton Institute ever since. My areas of research are agent-based-modelling (ABM), data curation, effective use of infrastructure as a service (IaaS), and semantic information representation and extraction using formal structures such as computerised ontologies, relational databases and any other structured or semi-structured data representations. I primarily deal with social and agricultural models and was originally taken on in the role of knowledge engineer in order to create the ontology for the H2020 project, Green Lifestyles, Alternative Models and Upscaling Regional Sustainability (GLAMURS). Subsequent work, for the Scottish Government has involved the use of IaaS, more commonly referred to as the “cloud” to create rapidly deployable and cheap alternatives to in-house high-performance computing for both ABM and Geographical Information System models.
It is the mixture of skills and interests involving modelling, data organisation and computing infrastructure expertise that I believe will be highly apposite in the duties associated with being a member of the CoMSES executive. Moreover, prior to joining academia, I spent about 25 years as a developer in commercial IT, in the agricultural, entertainment and banking sectors, and feel that such practical experience can only benefit the CoMSES network.
Applying agent-based models to archaeological data, using modern ethnoarchaeological data as an analog for behavior.
I graduated Bachelor and Master studies at the University of Warsaw, obtaining the diploma in biology at College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences (MISMaP). After graduation I worked as a freelancer in data science and statistics, then worked for 2 years as a data scientist in an IT startup and now I am working as a statistician in The Polish National Information Processing Institute (OPI PIB) in a group analysing condition of science and higher education in Poland. My interests: agent based modelling, evolutionary ecology, statistics, data science, sociology of science.
I am an anthropological archaeologist with broad interests in hunter-gatherers, lithic technology, human evolution, and complex systems theory. I am particularly interested in understanding processes of long term social, evolutionary, and adaptational change among hunter-gatherers, specifically by using approaches that combine archaeological data, ethnographic data, and computational modeling.
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.
I am interested in questions of method, and in the application of computational social models to a wide variety of national security questions (such as counterterrorism and counterinsurgency) as well as decision-making around complex natural resources such as water. My methods interest center on the use of qualitative social theory to inform the structure of computational social models, and the ways in which such models handle qualitative data. This raises questions around the nature of data and the ways in which computational social models convey information to decision-makers.
Development of spatial agent-based models to sustainability science and ecosystem service assessment, integration of agent-based model with biophysical process based model, improvement of theory of GIScience and land use change science, development of spatial analytical approach (all varieties of spatial regression), spatial data modeling including data mining, linking processes such as climate change, market, and policy to study patterns.
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).
The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.
My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.