A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algor ....A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algorithm-based search obtain the optimal number of layers, clusters and base classifiers. The expected outcomes of the proposed framework are advances in classifier learning. The final outcome may be novel methods which will bring in diversity during the learning of the base classifiers and provide an optimal ensemble classifier for real-world applications.Read moreRead less
Mechanisms of nerve fibre guidance by molecular gradients. Brain wiring is crucial for brain function. The project will investigate the basic principles underlying the development of brain wiring, using both experiments and mathematical models. This will lead a predictive model of how wiring develops, both in normal and abnormal situations.
Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide ....Bio-inspired Computing for Problems with Dynamically Changing Constraints. The aim of this project is to design bio-inspired computing methods for dynamically changing environments. Dynamic problems arise frequently in the areas of engineering, logistics, and manufacturing. Such problems are usually subject to a large set of constraints that change over time due to changes in resources. Algorithms that can deal with such dynamic changes would benefit decision-makers. The project aims to provide a foundational theory as the basis for the design of bio-inspired algorithms dealing with dynamically changing constraints and provide approaches for dealing with important industrial problems.Read moreRead less
Extending fuzzy logic. Fuzzy logic is good for dealing with uncertain data somewhat like people do, and this technique has been used in train braking systems, computer animation etc, but can be slow for problems with large or complex data especially if the data are changing with time. The project will design efficient fuzzy logic algorithms capable of dealing with complex real world problems.
Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis f ....Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis for the development of platform technology capable of monitoring and detection of neural health status. Success is expected to yield a new generation of smart dynamic non-invasive systems that will be critical for developing effective solutions to counter life threating conditions for a large cross section of the Australian population.Read moreRead less
Memetic algorithms and adaptive memory metaheuristics for large scale combinatorial optimisation problems arising in biomarker discovery. Despite modern supercomputers, the world depends on combinatorial optimisation, the branch of mathematics and computer science that involves finding optimal solutions when it is impossible to enumerate all solutions. We bring complementary skills to address the core set of the five most challenging problems arising from novel biotechnologies.
Unleashing the power of a supernetwork-driven approach for bioinformatics. Supernetworks are built “above and beyond” existing networks. In bioinformatics they arise from the integration of a set of networks with different types of nodes and edges. While large companies and governments have already understood the importance of decision problems in supernetworks, the power of this perspective has not yet been exploited in the life sciences. Using supercomputer-based approaches together with memet ....Unleashing the power of a supernetwork-driven approach for bioinformatics. Supernetworks are built “above and beyond” existing networks. In bioinformatics they arise from the integration of a set of networks with different types of nodes and edges. While large companies and governments have already understood the importance of decision problems in supernetworks, the power of this perspective has not yet been exploited in the life sciences. Using supercomputer-based approaches together with memetic algorithms, this project will address the first key areas that will lead to smart information use of existing networks in distributed databases. This project will deliver the next generation of algorithms for network alignment, identification of connected-cohesive subnetworks and embedding large graphs in multi-planar structures.Read moreRead less
Challenging systems to discover vulnerabilities using computational red teaming. Computational red teaming concerns the design of computational models to role play intelligent adversaries. These adversaries who are determined to exploit a system rely on creative thinking to discover system-level vulnerabilities by challenging system design, implementation or operations. This project closes a gap in the risk assessment literature by designing automated computational red teaming methods to discove ....Challenging systems to discover vulnerabilities using computational red teaming. Computational red teaming concerns the design of computational models to role play intelligent adversaries. These adversaries who are determined to exploit a system rely on creative thinking to discover system-level vulnerabilities by challenging system design, implementation or operations. This project closes a gap in the risk assessment literature by designing automated computational red teaming methods to discover vulnerabilities associated with intentional risks. Scientific outcomes include novel automated skill assessment algorithms and new search techniques to exploit assumptions that could have been overlooked otherwise. Practical outcomes include robust risk assessment tools, strong research training, and high impact publications.Read moreRead less
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud mark ....Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud market, benefiting consumers and providers.Read moreRead less