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.
Multi-modal virtual microscopy for quantitative diagnostic pathology. This project will contribute to the next generation of virtual microscopy systems that provide innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of diagnostic pathology. These tools will especially contribute to the screening and diagnosis of cervical, lung and bladder cancer.
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
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
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
Data Exploitation for Critical Infrastructure Protection: Gathering Intelligence from Digital Evidence Collected from IT Networks and Process Control Systems. This proposal addresses the National Priority of Safeguarding Australia and its results will serve as a major input into current Australian Federal Government and Defence initiatives in digital evidence collection and exploitation as part of process control system security. It will play a significant part in satisfying the Australian commu ....Data Exploitation for Critical Infrastructure Protection: Gathering Intelligence from Digital Evidence Collected from IT Networks and Process Control Systems. This proposal addresses the National Priority of Safeguarding Australia and its results will serve as a major input into current Australian Federal Government and Defence initiatives in digital evidence collection and exploitation as part of process control system security. It will play a significant part in satisfying the Australian community that steps are being taken to safeguard national services and will develop techniques for protecting Australia against criminal or terrorist cyber attack on national services infrastructure. It will serve to develop niche Australian research expertise in this very specialised international field.Read moreRead less
From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden ....From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.Read moreRead less
How is information organised in the mind? Learning structured mental representations from data. One of the biggest questions in psychology is to understand the principles that the mind uses to organise information. This project is both a search for these underlying psychological laws, and an attempt to develop new statistical technologies and mathematical tools that can be used to organise information in applied settings.
Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat ....Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.Read moreRead less
The microbe factory: a novel approach to benign minerals processing. The purpose of this project is to reduce the environmental impact of current mining practices. The anticipated outcome of this project is the replacement of toxic chemicals used in the separation of minerals with the novel use of environmentally benign microbes.