Research fellow, PhD Candidate (University of Kassel)
Energy system transiton modelling * stakeholder and market modelling, governance and policy modelling, * agent-based modelling (ABM), optimisation, * model coupling, open and integrative modelling framework, * open source, S4F
Flood Risk Management, Coupled Human-Natural System Modelling, Socio-hydrological Modelling, Agent-Based Modelling, Human Behaviour Modelling, Agent-Based Social Simulation, Hydrological and Hydraulic Modeling, Geographic Information Systems (GIS), Mapping, Risk Modelling and Risk Visualization, Disaster Risk Reduction
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
Land cover changes spatial agents based modelling
Forest fire risk modelling
Geographical information based modelling
Decision support for land planning
social-ecological modelling; cognitive modelling; agent-based modeling&simulation; data science; smart city modelling; artificial intelligence; large-scale simulation
Poverty and sustainability
Agent Based Modelling
Southeast Asian economies
Interested in IWRM approach, analyzing coupled human-water relationship, Hydrological modelling, Bayesian networks, Agent based modelling