Secondary education, agent-based modeling and computational science in education
complex systems science; implementation science; agent based modeling; health care infrastructure and population health; public health
I am currently completing a PhD on information sharing for natural resources management. Research is based on case studies on oyster farming, in the Thau Basin, France and in New South Wales, Australia
political methodology research covering agent-based modelling and simulation of political phenomena,computational models of political phenomena (political attitudes, elite, corruption, political clientelism, state capture)
I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).
Agent-based modeling and simulation of public policies.
My primary research interest is in developing spatial computer models of social phenomena and my focus, in particular, has been on crime simulation.
Agent-based computing in economics and finance
Large-scale agent-based models
Agent models calibrated by micro-data
Complex adaptive systems
Mathematical analysis of agent systems
Simulation games, systemic complexity, learning, business cycles, and discrete-event simulation, modeling sustainability challenges in urban context.