As a Program Associate in the Research Competitiveness Program, I work on a diverse portfolio of science and technology based development projects. These projects frequently involve managing peer-review processes for grant competitions and other research and development activities as well as producing their associated progress reports. Projects are often associated with the regional and national development plans of various governments and institutions both domestic and international.
My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.
To tackle the scientific challenges proposed by landscape dynamics and cooperation processes, I have developed a research methodology based on field work and companion modelling (ComMod) combined with the formalisation of the observed processes and agents based models.
This approach offers the possibility to understand : spatial, social, cultural and / or economic conditions that take place on territories, and to provide prospective scenarios.
These methods have been applied in various contexts: steep slope vineyards landscapes (2011), water resource management cooperation (2015), vegetation cover in dry climate (2017). The established research networks are still active through sustained collaborations and activities.
My technical expertise grew and evolved through investment in several workgroups: MAPS Team (Modelling Applied to Space Phenomena), OSGeo (president of the OSGeo’s French chapter between 2013 and 2016, member of the OSGeo-international chapter since 2015), various initiatives around modelling, exploration and sensibility analysis of spatial patterns behaviours, and more generally in Free Software communities.
I am interested in the socio-environmental conditions for the emergence of cooperation and mutual aid in social systems and mainly with regard to renewable resources. I consider in this context that Commons are a spatial manifestation of mutual aid.
From a technical point of view, I am very interested in the questions of model exploration (HPC), which led me to integrate the OpenMole community and to contribute to discussions about heuristic exploration.
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
I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.
My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.
In Summer 2019, I attended the Santa Fe Institute‘s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).
Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.
I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.
While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.
Professor, School of Human Evolution & Social Change
Professor, School of Complex Adaptive Systems
Affiliate Professor, School of Earth and Space Exploration
Arizona State University
My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I’ve done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
With my research, I aim to improve scientific understanding of the role interactions among cognitive, behavioral, social, and demographic processes play in human adaptation to social-ecological change. Currently, I hold a Postdoctoral Research Fellow position at University of Michigan’s School for Environment and Sustainability and an Instructor position at Portland State University’s Systems Science Program. I have a Ph.D. in Systems Science (2018) from Portland State University, and an M.A. in Economics (2007) and a B.S. in Management (1999) from Boston University.
Cognitive Social Science, Social-Ecological Systems, Multi-Agent Modeling, Complex Adaptive Systems
Without Central Control is self organization possible?
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
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).