ProfessorMikhail Prokopenko
Professor in Complex Systems
Faculty of Engineering
- Professor in Complex SystemsFaculty of Engineering
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.
"I joined the University of Sydney in 2014, having worked prior with CSIRO for 20 years. This has allowed me to concentrate on strategic research full time within a highly collaborative environment. This hopefully will enable me to have a significant impact on advancing national and international research into complex systems, by enhancing my ability to productively interact across disciplines and research institutions."
FUNDED RESEARCH
- GRANTHigh-resolution multiscale modelling of pandemics: COVID-19 and beyondAustralian Research Council (ARC)2 Aug 2022 - 31 Dec 2025People funded by this grant:
- Sorrell T,
- Sintchenko V,
- Prokopenko M
- GRANTModelling the impact of opinion dynamics on the COVID-19 pandemic in AustraliaSydney Institute for Infectious Diseases (Sydney ID)1 Jan 2022People funded by this grant:
- Chang S,
- Prokopenko M
- GRANTQuantifying emergence and dynamics of foodborne epidemics in AustraliaAustralian Research Council (ARC)15 Apr 2020 - 31 Dec 2023People funded by this grant:
- Kauffman S,
- Sintchenko V,
- Sorrell T,
- Malik A,
- Prokopenko M
- GRANTAustralian housing market risks: simulation, modelling and analysisAustralian Research Council (ARC)30 Jun 2017 - 30 Jun 2020People funded by this grant:
- Brede M,
- Farmer J,
- Ormerod P,
- Harre MM,
- Prokopenko M
- GRANTApplying information thermodynamics to cell computersThe Royal Society6 Feb 2017People funded by this grant:
- Spinney R,
- Prokopenko M,
- Chu D
- GRANTCRISIS: Crisis Response in Interdependent Social-Infrastructure SystemsDVC Research1 Jan 2017People funded by this grant:
- Fletcher R,
- Lizier J,
- Penny D,
- Sleigh A,
- Miles R
- GRANTLarge-scale computational modelling of epidemics in AustraliaAustralian Research Council (ARC)30 Jun 2016 - 31 Dec 2019People funded by this grant:
- Prokopenko M,
- Gambhir M,
- Lizier J,
- Pattison P,
- Piraveenan M
- GRANTToward a Computational Theory of LifeThe Royal SocietyPeople funded by this grant:
- Chu D,
- Prokopenko M,
- Ray C