Jörn Davidsen, Prof.
Dr. rer. nat. in Theoretical Physics, Christian-Albrechts University of Kiel, Germany, 2001
Areas of Research
Complexity Science
Physical, geophysical, chemical, living and human-made systems often show behaviors that cannot be understood by studying their building blocks or constituents to ever finer detail but that are emergent. The concept of emergence can be summarized by the statement that there exists an entity (e.g. an organism) which is more than the sum of its parts. This is often used as the defining property of a complex system. Many of these complex systems can be represented as a collection of dynamical units coupled via complex architectures. Complex network theory offers a unified description of these complex systems and has been invaluable in discovering unifying characteristics and principles despite the intrinsic differences between systems. Understanding these emergent characteristics and principles, their stability and the self-organization processes leading to them in non-equilibrium systems is one of the central quests of modern physics. The research of my group aims to tackle this challenge. Prominent examples include seismicity and neural signaling or biological signaling processes in general, with immense importance for society. A detailed understanding of seismicity is required to ensure successful seismic hazard assessment and to explore the possibility of successful earthquake prediction. A detailed understanding of the brain is essential to tackle brain related diseases such as Alzheimer's and epilepsy.
Physical, geophysical, chemical, living and human-made systems often show behaviors that cannot be understood by studying their building blocks or constituents to ever finer detail but that are emergent. The concept of emergence can be summarized by the statement that there exists an entity (e.g. an organism) which is more than the sum of its parts. This is often used as the defining property of a complex system. Many of these complex systems can be represented as a collection of dynamical units coupled via complex architectures. Complex network theory offers a unified description of these complex systems and has been invaluable in discovering unifying characteristics and principles despite the intrinsic differences between systems. Understanding these emergent characteristics and principles, their stability and the self-organization processes leading to them in non-equilibrium systems is one of the central quests of modern physics. The research of my group aims to tackle this challenge. Prominent examples include seismicity and neural signaling or biological signaling processes in general, with immense importance for society. A detailed understanding of seismicity is required to ensure successful seismic hazard assessment and to explore the possibility of successful earthquake prediction. A detailed understanding of the brain is essential to tackle brain related diseases such as Alzheimer's and epilepsy.
Spreading & triggering processes
Fluid-induced seismicity
Computational neuroscience & the critical brain
Rock fracture & frictional sliding
Statistical seismology
Network neuroscience
Synchronization & chimera states
Sociophysics
Climate dynamics & climate networks
Supervising degrees
Physics and Astronomy - Doctoral: Seeking Students
Physics and Astronomy - Masters: Seeking Students
More information
Working with this supervisor
I am always looking for excellent and motivated students. Current specific topics of interest include but are not limited to complex network theory, neuronal avalanches and brain networks, earthquake triggering, network inference and network information as well as rock fracture and hydraulic fracturing. Many of the ongoing theoretical and computational projects are pursued in close collaboration with experimentalists. You can find my contact details on my homepage.