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).
Social scientist based in Milan, Italy. Post-doctoral researcher in Sociology at the Department of Social and Political Sciences of the University of Milan (Italy), member of the Behave Lab. Adjunct professor of Social Network Analysis at the Graduate School in Social and Political Sciences of the University of Milan.
Isaac IT Ullah, PhD, (Arizona State University 2013) Dr. Ullah is a computational archaeologist who employs GIS and simulation modeling to understand the long-term dynamics of humans and the Earth System. Dr. Ullah is particularly interested in the social and environmental changes surrounding the advent of farming and animal husbandry. His focus is on Mediterranean and other semi-arid landscapes, and he conducts fieldwork in Jordan, Italy, and Kazakhstan. His field work includes survey for and excavation of early agricultural sites as well as geoarchaeological analyses of anthropogenic landscapes. His specialties include landscape evolution, complex adaptive systems science, computational methods, geospatial analysis, and imagery analysis.
Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean
The main research area is operation research in logistics with a focus on logistic cluster development and innovative technology usage. Due to mathematical background, Gružauskas focuses on quantitative analysis by conducting simulations, stochastic and dynamic models and other analytical approaches to amplify the developed theories. Gružauskas also is working as a freelance data analyst with a focus on statistical analysis, web scraping and machine learning.
Christian Reynolds is a Public Health Research Fellow at the Rowett Institute of Nutrition and Health, University of Aberdeen, and an adjunct Research Fellow at the Barbara Hardy Institute for Sustainable Environments and Technologies, University of South Australia. Christian’s research examines the economic and environmental impacts of food consumption; with focus upon food waste, sustainable diets, and the political power of food in international relations.
Christian has experience in economic input-output, material flow and environmental (Life Cycle Analysis) modelling and has published peer reviewed articles on these topics.
Interdisciplinary researcher interested in using computational modeling and analysis to study national security, urban and online behaviors, and other topics.
Development and usage of demographic microsimulation tools and applications, in particular mate-matching and statistical modeling as well as analysis of output
Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.