Sustainability in Computing: A Holistic View. Green computing must provide sustainable processing capabilities with high energy efficiency (lower carbon footprint) and increased product longevity (reducing the need for product replacement). While advances in technology have afforded significant reduction in power requirements, they come with inherent challenges due to uncertainties in micro-scale behaviour, high complexity of quantifying/optimising energy cost or system lifetime in extreme scale ....Sustainability in Computing: A Holistic View. Green computing must provide sustainable processing capabilities with high energy efficiency (lower carbon footprint) and increased product longevity (reducing the need for product replacement). While advances in technology have afforded significant reduction in power requirements, they come with inherent challenges due to uncertainties in micro-scale behaviour, high complexity of quantifying/optimising energy cost or system lifetime in extreme scale computing, and the interaction of non-computing components with individual computing systems. This project addresses these challenges via a holistic, multi-scale paradigm for modelling, analysis, and optimisation of energy cost, carbon footprint, and product lifetime in emerging computing systems.Read moreRead less
Automatic video annotation by learning from web data. This project aims to study next-generation video annotation technologies to automatically tag raw videos using a huge set of semantic concepts. The project will study new domain adaptation schemes and frameworks in order to substantially improve video annotation performance. The resulting prototype system can be directly used by ordinary users worldwide to search their personal videos using textual queries. The system is also applicable to vi ....Automatic video annotation by learning from web data. This project aims to study next-generation video annotation technologies to automatically tag raw videos using a huge set of semantic concepts. The project will study new domain adaptation schemes and frameworks in order to substantially improve video annotation performance. The resulting prototype system can be directly used by ordinary users worldwide to search their personal videos using textual queries. The system is also applicable to video surveillance applications, which can enhance Australia’s homeland security.Read moreRead less
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
The Monetisation of Children in the Digital Games Industry. This project aims to understand the monetisation of children in the digital games industry. It will employ innovative studies of children’s experiences in freemium games; parental attitudes and strategies; participatory research with game developers; and an examination of the platform and regulatory environment that shapes game monetisation. Expected outcomes include guidelines and recommendations for parents seeking to negotiate childr ....The Monetisation of Children in the Digital Games Industry. This project aims to understand the monetisation of children in the digital games industry. It will employ innovative studies of children’s experiences in freemium games; parental attitudes and strategies; participatory research with game developers; and an examination of the platform and regulatory environment that shapes game monetisation. Expected outcomes include guidelines and recommendations for parents seeking to negotiate children’s digital play; new ethical frameworks for the design and implementation of digital games for children; and actionable advice for policymakers and practitioners. This will bring significant benefits to Australian children, parents and game developers via improvements to the design of games for children.Read moreRead less
Positive Computing: The design of technologies that support psychological wellbeing. Designing future technology to foster psychological wellbeing has the potential to affect population-wide positive change. The design of software like apps or social media, can impact things like cyber-bullying, depression, or even foster resilience. This project aims to connect experts across multiple disciplines (psychology, technology and policy) to develop pioneering methods, knowledge, and strategies that w ....Positive Computing: The design of technologies that support psychological wellbeing. Designing future technology to foster psychological wellbeing has the potential to affect population-wide positive change. The design of software like apps or social media, can impact things like cyber-bullying, depression, or even foster resilience. This project aims to connect experts across multiple disciplines (psychology, technology and policy) to develop pioneering methods, knowledge, and strategies that will allow future technologies to play an active role in improving health, performance, and quality of life for all Australians, through research-based design for wellbeing. In doing so, Australia will lead the way on the technological front in a growing global initiative to improve the wellbeing of nations.Read moreRead less
Deep Adder Networks on Edge Devices. This project aims to empower edge devices with intelligence by developing advanced deep neural networks that address the conflict between the high resource requirements of deep learning and the generally inadequate performance of the edge. Multiplication has been the dominant type of operation in deep learning, though the addition is known to be much cheaper. This project expects to yield theories and algorithms that allow deep neural networks consisting of n ....Deep Adder Networks on Edge Devices. This project aims to empower edge devices with intelligence by developing advanced deep neural networks that address the conflict between the high resource requirements of deep learning and the generally inadequate performance of the edge. Multiplication has been the dominant type of operation in deep learning, though the addition is known to be much cheaper. This project expects to yield theories and algorithms that allow deep neural networks consisting of nearly pure additions to fulfil the requisites of accuracy, robustness, calibration and generalisation in real-world computer vision tasks. The success of this project will benefit deep learning-based products on smartphones or robots in health and cybersecurity.Read moreRead less
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
AUSLearn: AUtomated Sample Learning for Object Recognition. This project aims to enable computers to learn how to effectively use training samples for object recognition. Training sample is the only source used by computers to learn recognising objects. This project creates a new research direction that will enable the first full exploration of the power of samples. The aims will be enabled by leveraging the recent advances in reinforcement learning, fast training algorithms, and by developing n ....AUSLearn: AUtomated Sample Learning for Object Recognition. This project aims to enable computers to learn how to effectively use training samples for object recognition. Training sample is the only source used by computers to learn recognising objects. This project creates a new research direction that will enable the first full exploration of the power of samples. The aims will be enabled by leveraging the recent advances in reinforcement learning, fast training algorithms, and by developing novel deep learning algorithms. The new algorithms will benefit a wide range of applications, e.g. to effectively use car crash training samples for accurately identifying potential road crashes in transport and to effectively use rare medical imaging training data for robustly diagnosing diseases in health.Read moreRead less
Testing the Modularity of Memory. Researchers disagree about whether verbal and visual working memory (WM) storage occurs in separate modules. Recent evidence suggests that only verbal memoranda have access to a specialised module, while visual memories make use of more general resources. This project aims to re-examine interference between verbal and visual memoranda using statistical methods specialised for assessing whether multiple latent factors underlie performance on recognition memory ta ....Testing the Modularity of Memory. Researchers disagree about whether verbal and visual working memory (WM) storage occurs in separate modules. Recent evidence suggests that only verbal memoranda have access to a specialised module, while visual memories make use of more general resources. This project aims to re-examine interference between verbal and visual memoranda using statistical methods specialised for assessing whether multiple latent factors underlie performance on recognition memory tasks, examining adult and child populations. This is expected to influence applications of WM theory in many everyday settings, resulting in improvements in educational practices, workplace procedures, and clinical treatments that depend on theoretical understandings of limits in cognition.Read moreRead less
Multiview Complete Space Learning for Sparse Camera Network Research. Data analytics in video surveillance and social computing is a problem because data are represented by multiple heterogeneous features. This project will develop a multiview complete space learning framework to exploit heterogeneous properties to represent images obtained from sparse camera networks. It will integrate multiple features to identify people and understand behaviour, to build a database of activities occurring in ....Multiview Complete Space Learning for Sparse Camera Network Research. Data analytics in video surveillance and social computing is a problem because data are represented by multiple heterogeneous features. This project will develop a multiview complete space learning framework to exploit heterogeneous properties to represent images obtained from sparse camera networks. It will integrate multiple features to identify people and understand behaviour, to build a database of activities occurring in a wide area of surveillance. It will expand frontier technologies and safeguard Australia by providing warnings for hazardous (for example, overcrowding, trespassing), criminal, and terrorist situations. Results will be applicable internationally and enhance Australia’s role in machine learning and computer vision communities.Read moreRead less