Community and Infrastructure Resilience
Disaster Recovery
Complex Systems Modeling
Agent-Based Modeling
System Dynamics
Machine Learning
Pattern Recognition
Data Mining
Spatial Analysis and Modeling
Construction Management
Building Information Modeling

Simulation games, systemic complexity, learning, business cycles, and discrete-event simulation, modeling sustainability challenges in urban context.

As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.

Sae Schatz, Ph.D., is an applied human–systems researcher, professional facilitator, and cognitive scientist. Her work focuses on human–systems integration (HSI), with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation (M&S). Frequently, her work seeks to enhance individual’s higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with “cognitive readiness”).

My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.

My interests are to explore aspects of sustainability, resilience, and adaptive management in social-ecological systems using agent-based models and other simulation models.

General Question:
Without Central Control is self organization possible?

Specific Case:

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?

Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean