Our Complex Systems research focuses on the building of large distributed systems with a large number of interacting entities with complex behaviours, and modelling and analysing real-life complex systems, with multiple interacting components.
Complex systems range from social networks and financial markets, to urban development, plant structures and even galaxies.
The effects of the interactions between these entities are not easily modeled, as the interactions are not close in time and space.
Complex systems are becoming ubiquitous in today’s world yet insights into their unexpected behaviour and how to design systems with particular desired behaviours is limited.
Contrary to existing work, our research capability aims to apply existing theories to real world application domains and to develop new approaches as dictated by real constraints.
Our Complex Systems research focuses on:
- advanced statistical techniques
- engineering of complex (systems of) systems with desired emergent behaviour
- integer programming
- linear and non-linear programming
- modeling and analysis of complex systems behaviour
- stochastic dynamic programming
- validation and verification of complex (adaptive) systems focused on self-organisation, emergent behaviour, adaptability and criticality among others
- stochastic dynamic programming.
We seek to help organisations understand both their internal and external operational environments, and identify opportunities for more efficient processes and capital investment.
Our research has broad industry relevance, with applications in biology, data science, defence, infrastructure and transport, social sciences, trade, management and manufacturing.
Our research and development has had significant impact in both the private and public sectors. Some notable examples include:
- combat system modelling for the Defence Science and Technology (DST) Group, including risk identification and fitness-for-purpose evaluations
- the design and implementation of an adaptive communication strategy for land operating vehicles working in distributed, contested environments
- collaboration with biologists has led to insights into the extinction and evolution of fiddler crabs in varying environmental conditions
- the identification of rumours and their source in Twitter data
- timetable optimisation for the University of Adelaide
- risk analysis of medical evacuation infrastructure in the mining industry, and equipment failures in trains
- tools to model smart cities at a high resolution and identify the potential effects of various policy changes
- developing algorithms to optimise polyurethane foam product manufacturing for Dunlop Foams Group
- creating software for a major automobile manufacturer to analyse their end-to-end manufacturing process and predict artificial limitations in capacity
- developing software for a major asphalt producer to analyse historical order data and profile likely demand by mix type and day of week.
We advise on, and lead, projects relating to:
- technical reporting
- requirements specification
- engineering complex systems and validation of their behaviours
- software tools and prototypes
- standards representation
|Dr Andrew Coyle|
|Dr Jeremy McMahon|
|Dr Matthew Britton||Wireless sensor networks; Mobile ad-hoc networks (MANETs)|
|Dr Andre Costa||Optimisation; Stochastic processes; Modelling, simulation and quantitative finance|
|Dr Hung Nguyen||Applied mathematics; Networking and telecommunications|
|Siu Wai Ho|
|Dr Claudia Szabo||Complex physical systems; Distributed and grid systems; Distributed computing; Education, technology and computing|
|Dr Marian Milhailescu|
We collaborate with various government organisations, such as: