Complex Systems Science
in bridging humans and nature
The whole is more than the sum of its parts. - Aristotle
More is different. - Phil Anderson
Our world is complex with heterogeneous agents, interactions, multiple layers, and so on. There are different complex systems including cities, economies, brains, ecosystems, cells, and social networks. In these complex systems, individual behaviors shape emergent systematic patterns in complex systems, e.g., bird flocks, cooperation, and traffic congestion. Complex systems scientists explore to understand the emergence and scaling from micro to macro levels. They also aim to learn the robustness and resilience of complex systems against shocks or changes. To disentangle complexity, mathematical and computational techniques are applied from statistical physics, applied mathematics, etc.
More information about complex systems science:
Introduction to the Theory of Complex Systems by Stefan Thurner, Rudolf Hanel, Peter Klimek
Networks by Mark Newman
In my research, I actively apply complex systems approaches to diverse problems of human-nature interactions to build system sustainability and establish adequate policies against disturbances. My list of methodologies are:
System modeling - dynamical modeling, agent-based modeling, network modeling)
Analytical tools - global sensitivity and uncertainty analysis, network analysis, causal inference, event coincidence analysis
Policy analysis - Monte-Carlo Filtering, multi-criteria decision analysis, Pareto optimality analysis
I am interested in three research topics that often overlap with each other. I use appropriate tools from complex system science to delve into the topic.
Resilience of Socio-Ecological Networks