My research is focused on the security of water, food, and energy resources as well as natural resources planning and managaement. A lot of my work involves the integration of physical and social science research.
Integrating social and natural science to study coupled human-natural systems, and particularly the interactions of society with the physical environment under conditions of environmental stress.
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
Fabian Adelt graduated in computer-sciences with a minor in sociology of technology (degree: Diplom-Informatiker) at TU Dortmund University in 2011. Currently, he is research fellow at the Technology Studies Group and involved in the project “Collaborative Data- and Risk-Management in Future Grids – A Simulation Study” (KoRiSim). Between 2012 and 2015 he worked on the project “Mixed Modes of Governance as a Means of Risk Management in Complex Systems” (RiskSim). His research interests entail agent-based modelling and simulating of socio-technical systems, especially focussing on governance issues and actors’ reactions on interventions. Experience covers the fields of mobility and energy.
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.
Complex Systems
Agent-based Models
System Dynamics
Innovation
Economics
Organizational Development
energy and environmental sciences
Energy policy analysis
My research examines the most effective and efficient policies for renewable energy development using an approach that integrates input-output analysis, life cycle analysis, econometric, and agent-based modelling to estimate the impacts of the policies to economic, emission, extracted materials, renewable energy capacity and social acceptance.