Unraveling Emergent Complexity: A Neural-Inspired Framework for Multi-Scale Network Dynamics
Name of applicant
Guoqing Gao
Title
Postdoctoral Fellow
Institution
Imperial College London and University of Oxford
Amount
DKK 2,560,250
Year
2025
Type of grant
Internationalisation Fellowships
What?
This project develops a unified, neural-inspired framework to model emergent complexity in multi-scale networks - focusing on synchronization and cascading failures in power grids and neural systems. It bridges physics, neuroscience, and control theory to uncover shared dynamical laws.
Why?
Emergent behaviors like blackouts or seizures arise unpredictably in critical systems due to nonlinear, multi-scale interactions. Understanding their shared principles is crucial for enhancing resilience in power grids and for advancing theories of self-organized criticality across disciplines.
How?
The project integrates multi-scale Kuramoto models, graph theory, and neural mass models across four phases at Imperial, Aalborg, and Oxford. Through theoretical modeling and real-world data from Ørsted and epilepsy research, it synthesizes a cross-domain framework and open-source tools.