Network inhomogeneities can strongly affect the critical dynamics of spreading models if the graph

dimension is finite, causing large fluctuations and nonuniversal power-laws in extended control

parameter spaces. This provides an alternative or an extension of self-organized criticality, observed in

nature very frequently. These Griffiths Effects (GE) are generated by rare-regions and can be observed

even in finite scale-free graphs. Real networks are very often modular, that may enhance GE-s and may

lead to true Griffiths phases, where the fluctuations diverge. Participation in the research of GE-s in

various network models with large scale simulations or by other methods would be the target of this topic.

Besides spreading models, applicable to pandemics, we study synchronisation transitions from this point

of view in brain and in power-grid models, where frustrated synchronization and chimera states emerge.

Usage of an efficient tool, based on numerical solution of Kuramoto equation, for power-grid cascade

faliure simualtion is planned. GPU based simulations of critical connectome models is targeted.