I study human dimensions of natural resource management and resource use by under-represented populations—often in developing nations—to enhance our understanding of conflicts involving land use, natural resources, and conservation from an interdisciplinary, systematic lens. My research spans subjects such as common pool resource management and policy, decentralization, and land use/land cover change drivers and trends relating to population rise and environmental change.
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).
Using modeling and simulation to support the development of resilient infrastructures
Agent-based modelling of sustainable residential electricity consumer behaviour
Agent-based computational economics (ACE); development and use of ACE test beds for the study of electric power market operations; development and use of ACE test beds for the study of water, energy, and climate change
Amineh Ghorbani is an assistant professor at the Engineering Systems and Services Department, Delft University of Technology, the Netherlands. She is also an affiliated member of the “Institutions for Collective Action” at Utrecht University. She obtained her M.Sc. in Computer Science (Artificial intelligence) from University of Tehran (Iran) (2009, honours) and her PhD from Delft University of Technology (2013, cum laude).
During her PhD, Amineh developed a meta-model for agent-based modelling, called MAIA, which describes various concepts and relations in a socio-technical system. This modelling perspective helped her develop a modelling paradigm that she refers to as institutional modelling.
Her current area of research is understanding the emergence and dynamics of institutions (set of rule organizing human society) using modelling. She is interested in how bottom-up collective action emerges and how institutions emergence and change within communities.
evolution of institutions
community energy systems
I am a first year PhD student at the Jill Dando Institute for Security and Crime Science at University College London
Researcher in sustainable production and consumption, the service economy, energy markets, and electricity balancing mechanisms.