Within an interdisciplinary researcher team, he develops large-scale agent-based models (ABM) that are able to describe complex global systems. Such models will help to analyze the future potential of innovations and trends. Among other studies in the context of Global Systems Science, the current study analysis and models green growth initiatives.
The current example of the future electric car market aims to describe the global macro-economic system by small-scale interaction of billions of agents and their decisions. For tackling such large models, high-performance computing is used in cooperation with several leading computing centers and companies.
Andreas Geiges studied Environmental Engineering in Stuttgart and received his PhD in the related field of stochastic modeling, uncertainty quantification and optimized data acquisition for environmental systems. Furthermore, he has experience in the fields “high-performance computing”, “risk quantification” and “data analysis”.
With his engineering background in numerical modeling, he mainly contributes in the conceptual development of models for uncertain systems. His interests are modeling of environmental-related systems, the energy market with the special focus on renewable energies and energy efficiency as well as possible paths towards sustainable mobility.