Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high ....Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.Read moreRead less
Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an in ....Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an increased understanding of neural mechanisms underlying sensory selectivity, the development of novel techniques, and enhanced capacity for interdisciplinary collaborations. The project will provide significant knowledge as the developed biomimetic algorithms should be applicable for increased performance in drones or other unmanned vehicles.Read moreRead less
Efficient Management of Things for the Future World Wide Web. The future World Wide Web will connect billions of physical objects, which will offer exciting capabilities to change the world and improve the quality of human lives, just as what the Web has done in the past 20 years. Effectively and efficiently managing things is one inevitable challenge in this new era and is much more complicated than managing traditional Web documents. This project aims to focus on this key problem and develop n ....Efficient Management of Things for the Future World Wide Web. The future World Wide Web will connect billions of physical objects, which will offer exciting capabilities to change the world and improve the quality of human lives, just as what the Web has done in the past 20 years. Effectively and efficiently managing things is one inevitable challenge in this new era and is much more complicated than managing traditional Web documents. This project aims to focus on this key problem and develop novel techniques for linking resource-constrained things to the Web, searching them using a new search engine, as well as discovering latent relationships among things for advanced management tasks such as things recommendation and composition.Read moreRead less
Continuously learning to see. The ultimate goal of computer vision is to make a machine able to understand the world through analysis of images or videos. The new machine learning techniques developed in this project will enable previously impossible methods of computer vision and help strengthen Australia's competitiveness in this important area.
Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor ....Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.Read moreRead less