Optimisation technology is ubiquitous in our society. It schedules planes and their crews, coordinates the production of steel, and organises the transportation of iron ore from mines to ports. Optimisation schedules power restoration after major disasters, clears the day-ahead and real-time markets to deliver electricity to millions of people. It organises kidney exchanges and cancer treatments and helps scientists understand the fundamental fabric of life.
The optimisation research group carries out fundamental and applied research that addresses grand challenges faced by our society in environmental and societal resilience, future energy systems, logistics, supply chains, and transportation. Our mission is to contribute pioneering scientific results in computational optimisation, to build innovative optimisation systems to tackle increasingly complex applications, to integrate our research with NICTA research groups and business teams as well as the ICT ecosystem, and to work with our governmental, industrial, and university partners to deliver societal outcomes.
The optimisation research group envisions a world in which optimisation technology is pervasive across all segments of our society and integrated in an analytics pipeline, spanning data, immersive, predictive, and prescriptive analytics. In such a future, optimisation technology not only boosts operational productivity, quality of service, and scientific discovery in numerous sectors; it also supports evidence-based policy making and improves resilience, sustainability, and quality of life in our society. This vision requires a truly multi-disciplinary approach, across computer science, economics, the physical and social sciences, and arts and entertainment.
Optimisation Research Group Coordinator
Phone: +61 406 086 170
- ClusPath: A Temporal-driven Clustering to Infer Typical Evolution Paths
- Evolution of Privacy Loss in Wikipedia
- A Hybrid Heuristic for the 2L-VRP with Clustered Backhauls
- Optimizing Long-running Action Histories in the Situation Calculus through Search
- Beyond Theory and Data in Preference Modeling: Bringing Humans into the Loop