Geosimulation of Human and Elephant Conflict in Tanzania

My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.

The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.

Three fields interest me in research: the study of market from a behavioral point of view, focusing on loyalty, trust, quality convention; then the study of institutions, their dynamics and the predictions/diagnostics that can be made following Ostrom’s IAD framework; eventually discussions on epistemology and validation about ABM.

Down Networks is a real time, progressively agile non profit startup whose goals are to fund its research via pragmatically aggressive altruistic entrepreneurial pursuits informed by proprietary in-house techniques, open source technology and refined scientific methodology.

Modeling coupled natural/human systems, climate impacts and mitigation policy.

Innovation Networks, University-Industry Links, Management and Policy for Technologies in Emerging Economies (Brazil), Agent-based Simulation.

Mathematical modeling and simulation in social sciences, biology, physics, and signal processing.

complex network and electronic commerce

• Social learning and cultural evolution
• Hunter-gatherers
• Evolutionary medicine