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
With my research, I aim to improve scientific understanding of the role interactions among cognitive, behavioral, social, and demographic processes play in human adaptation to social-ecological change. Currently, I hold a Postdoctoral Research Fellow position at University of Michigan’s School for Environment and Sustainability and an Instructor position at Portland State University’s Systems Science Program. I have a Ph.D. in Systems Science (2018) from Portland State University, and an M.A. in Economics (2007) and a B.S. in Management (1999) from Boston University.
Cognitive Social Science, Social-Ecological Systems, Multi-Agent Modeling, Complex Adaptive Systems
This paper investigates how collective action is affected when the interaction is driven by the underlying hierarchical structure of an organization, e.g., a company. The performance of collection action is measured as the rate of contribution to a public good, e.g., an organization’s objective.
Without Central Control is self organization possible?
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
I am a Ph.D. student studying the interactions between external regulations and social norms in natural resource management and international development. In particular, I am looking to use mixed methods research, including ethnographic research, field experiments, and agent-based computational models to explore the sustainability of market-based interventions and their possible perverse outcomes.
I am a Professor in the School of Sustainability and the Director of the Center for Behavior, Institutions and the Environment. I want to understand how people solve collective problems at different levels of scale, especially those problems related to sustainability of our environment. Our society experience unprecedented challenged to sustain common resource for future generations at a scale we have never experienced before. What makes groups cooperate? What is the role of information? How does the ecological context affect the social fabric? How do they deal with a changing environment? How can we use these insight to address global challenges? To do this research I combine behavioral experiments, agent-based modeling and case study analysis.
I am a computer scientist by training and full stack software engineer / systems administrator and have been building cyberinfrastructure for computational social science at ASU since 2006; these projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, and CoMSES Net, where I serve as a co-director.
I’m also a Software / Data Carpentries maintainer and instructor and a member of the Force 11 Software Citation Implementation Working Group.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable & reproducible scientific computation.