Our teaching programmes prepare undergraduate and graduate students for working in industry and academia. The most important skills they learn are how to think for themselves, how to learn for themselves, how to see the big picture and how to get straight to the heart of the matter. Our research aligns with current and anticipated future needs of industry and society. There is always room for significant innovation in how problems are solved.

Can we help? Find out below, under Prospective Partnerships.

We are helping Southern Innovation further improve their world-leading algorithms for nuclear spectroscopy. The underlying signal processing challenge is identifying the sizes and locations of each individual pulse in a stream of noisy measurements. This would be straightforward if not for pulses having long tails and piling up on each other. Two sufficiently close pulses are indistinguishable from a single pulse. Advanced statistical methods are required for resolving this pulse pile-up problem.

With DFS Advisory Services we are working on financial time-series prediction problems. One goal is determining fundamental limits on data-driven forecasting. While statistical models can provide a wealth of information, the challenge is tuning their parameters with only limited data. Another goal is seeking ways to augment existing data by utilising recent ideas from network science. The third goal is refining the interface between statistical models and human decision making.

With support from iMove Australia we have an industry-funded Ph.D. student working with Sensys Gatso Australia to develop signal processing algorithms for identifying different types of vehicles from radar returns. The current focus is determining the number of axles on trucks as they drive past a fixed radar unit.

There is a number of mechanisms which enable us to engage with industry partners depending on the nature and urgency of the work. Our expertise includes optimisation, statistical signal processing, modelling, prediction, data science, machine learning and software and hardware development.

Consultancies are best for high-priority work. Types of consultancy work include the following:

• Algorithm design and implementation
• Software and hardware development
• Commissioned report on state-of-the-art solutions to particular problems
• Simulation studies
• Expert witness.

Government-funded grants from the Australian Research Council's Linkage Programs, the Department of Industry, Science, Energy and Resource's funding schemes and other sources are well-suited to collaborative research projects spanning three or more years. This funding can be used to hire a postgraduate researcher to work full-time on the research project. Such projects can deliver highly innovative solutions.

Industry-funded Ph.Ds provide a cost-effective means of exploring novel solutions while simultaneously training a potential future recruit. In the first year of candidature the Ph.D. student will take appropriate graduate-level courses while developing a thorough understanding of the research project. The bulk of the research is carried out in the second and third years.

Industry-aligned Capstone Projects are an opportunity to work with final-year engineering students on a year-long project of your choosing. The only commitment is in the form of weekly or fortnightly meetings with the students during semesters.