Research interests Complex systems - which include things such as power and data grids, communication and transport systems, social networks and ecosystems - evolve and 'self-organise' over time. This can result in both benefits and challenges. Professor Mikhail Prokopenko's research aims to leverage the benefits while also addressing the challenges. "Self-organisation is pervasive: individual organisms within a swarm achieve collective coherence out of isolated actions; ecosystems develop spatial structures in order to deal with diminishing resources; and large-scale natural and social systems including bushfires, landslides and disease epidemics feature spontaneous, scale-invariant behaviour. "Sometimes self-organisation strengthens the overall system, increasing its resilience in the face of external disturbances, adaptability to new tasks and scalability with respect to new constraints, but in some regimes it can also manifest itself as a crisis. Examples of such crises include cascading power failures, loss of data in sensor and communication networks, traffic disruptions, epidemic outbreaks and ecosystem collapses. "The general objective of my research is to alleviate these problems by understanding and computational modelling of the critical phenomena intrinsic to self-organisation, and ultimately increase the robustness and resilience of a diverse range of complex systems from digital circuitry to power grids to social networks. "This will result in increased productivity, lower maintenance costs, less downtime and greater overall safety and reliability, as well as contribute to global health and sustainability by identifying more timely and precise emergency interventions during socio-ecological, socio-economic and technological system crises. "Studying how order is created out of interactions, despite a relentlessly increasing flow of entropy, is one of the most rewarding scientific experiences, and finding ways to guide processes that seemingly spontaneously self-organise, towards desirable outcomes is among the most complex of engineering tasks.