Stochastic Modelling and Operations Research
Stochastic Modelling and Operations Research involves using mathematics to understand and make decisions in systems that involve randomness and/or uncertainty.
Based within the School of Mathematical Sciences, our Stochastic Modelling and Operations Research group fuses theory, computation and data to address exciting and important problems throughout the sciences and industry.
We have particular strengths in:
- modelling stochastic systems, particularly using computational techniques
- calibrating stochastic models
- modelling networks and their processes, with applications in energy and the Internet
- modelling in ecology, epidemiology and evolution
- Bayesian computational statistics
- data science.
The Stochastic Modelling and Operations Research group’s advances are of direct relevance and benefit wherever uncertainty and/or randomness exists. This includes, for example, industries and areas such as:
- the Internet
- cyber security
- power grids
- conservation science
- health care systems
- infectious disease epidemiology.
The Stochastic Modelling and Operations Research group has received significant recognition for its valuable contributions to industry and society, including prestigious medals from the Australian Academy of Science and Australian Mathematical Society.
Some recent real-world-impact highlights include:
- providing new epidemiological insight into influenza and seasonal epidemics through work with the Australian Sentinel Practices Research Network
- developing algorithms to estimate pandemic strains’ transmissibility and severity
- advising the Australian Government’s Office of Health Protection on providing personal protective equipment—and collecting epidemiological data—for pandemics
- developing tools for predicting events using open social media data, which are now being built into commercial forecasting tools for government use.
We have a long-established collaborative relationship with the University of Adelaide’s Australian Centre for Ancient DNA (ACAD). We provide ACAD with novel mathematical and statistical techniques to undertake a range of fascinating research tasks. These have included:
- genetically mapping the original peopling of Australia, for which the University and research collaborator the South Australian Museum received the 2017 Eureka Prize for Interdisciplinary Research
- genetically mapping the original peopling of South America
- detecting and quantifying species hybridisation
- investigating ancient humans’ immune- and digestive-system evolutionary pathways, and connecting these with their known behaviour.
We have expertise across a wide range of areas. Many of our researchers are available to assist with research project supervision for Master of Philosophy and Doctor of Philosophy students.
Research team Expertise Professor Nigel Bean Matrix-analytic methods; Stochastic modelling; Operations research Dr Andrew Black Stochastic modelling in ecology; Epidemiology and evolution; Bayesian computational statistics; Computational probability Dr Robert Cope Computational statistics; Epidemic forecasting; Modelling in ecology, epidemiology and evolution Dr David Green Matrix-analytic methods; Optimisation; Simulation Dr Lewis Mitchell Computational social science; Natural language processing; Ensemble data assimilation and prediction Dr Giang Nguyen Matrix-analytic methods; Brownian motion; Modelling of electricity pricing and power grids Professor Joshua Ross Stochastic modelling in ecology, epidemiology and evolution; Bayesian computational statistics; Computational probability Professor Matthew Roughan Network modelling; Internet measurement and management; Traffic analysis Dr Peter Ballard Dr Thomas Prowse
We collaborate with various industry and government organisations, including:
- ARC Centre of Excellence for Australian Biodiversity and Heritage
- ARC Centre of Excellence for Mathematical and Statistical Frontiers
- Australian Sentinel Practices Research Network
- Centre for Invasive Species Solutions
- Data to Decisions CRC
- Defence Science and Technology (DST) Group
- NHMRC Centre of Research Excellence for Policy Relevant Infectious Disease Simulation and Mathematical Modelling
- US Defense Threat Reduction Agency
Our Stochastic Modelling and Operations Research group is available to advise or lead public- and private-sector projects to assist understanding and decision-making in any large systems that involve randomness and/or uncertainty.
Related areas of research