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Ecology - Natural Resources Management (Community-based management)
I worked on natural resources management modelling in STELLA. I developed a technical and scientific model to analyze soil, climate and biological conditions to explain how Bamboo ecosystem works and how people in Cundinamarca, Colombia could focus on a sustainable model for use and manage forestry resources.
Also, I worked on the seventh framework program named: Community-based management of Environmental Challenges in Latin America -COMET-LA-. The project built a learning arena with scientists, civil society and government to identify sustainable models for governance of natural resources in social-ecological systems located in a rural context from Colombia, México and Argentina.
I am interesting in research on Modelling of governance and Community-based management of natural resources.
I’m modelling LandUse and Cover Changes, Biodiversity impact and Biological corridors for Surrogate Species shared by US and Mexico.
My main interests are system dynamics and multi agent simulation used for support of business and marketing decisions (e.g. modeling of consumer markets) and in business education (e.g. development of open source business simulators). Amongst my other interests are applied marketing research, relationships between academia and industry, financial literacy, mind and concept mapping.
My research interests stand between natural resource management and ecological economics. The aim of my PhD project responds to the increasing demand for cross-disciplinary agent-based models that examine the disjunction between economic growth and more sustainable use of natural resources.
My research attempts to test the effectiveness of different governance and economic frameworks on managing natural resources sustainably at both regional and national levels. The goal is to simulate how communities and institutions manage the commons in complex socio-ecological systems through several case-studies, e.g. rainforest management in Australia. It is hoped that the models will highlight which combination of variables lead to positive trends in both economic and environmental indicators, which could stimulate more sustainable practices by governments, private sectors and civil society.
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.
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
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.
Innovation Networks, University-Industry Links, Management and Policy for Technologies in Emerging Economies (Brazil), Agent-based Simulation.
Modeling, companion modeling, role playing games, serious games, multi-agent systems, agent-oriented simulation, complex systems, water management, artificial intelligence
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