Digital nomadism: How IT enables new forms of working and organising. This project aims to gain a better understanding of digital nomadism. Digital nomads use IT platforms to work remotely over the Internet while perpetually travelling. The project will develop new knowledge by better understanding of how IT transforms work and enable digital nomadism, the motivations and values of workers and their clients/organisations engaged in digital nomadism and the implications and consequences of digita ....Digital nomadism: How IT enables new forms of working and organising. This project aims to gain a better understanding of digital nomadism. Digital nomads use IT platforms to work remotely over the Internet while perpetually travelling. The project will develop new knowledge by better understanding of how IT transforms work and enable digital nomadism, the motivations and values of workers and their clients/organisations engaged in digital nomadism and the implications and consequences of digital nomadism for workers and clients/organisations. The project is expected to have a significant impact on policy and public discourse by providing an in-depth explanation and understanding of digital nomadism based on rigorous research.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Affective sensing technology for the detection and monitoring of depression and melancholia. This project will develop reliable and affective sensing technology and evaluate it as an objective measure of depressive disorders; a leading cause of disability worldwide. Outcomes will significantly support and aid clinicians in their diagnosis and treatment, thus providing a major breakthrough with significant research, healthcare and commercial possibilities.
Productivity and work-life balance in technology-enabled virtual work environments. This project examines the impact of technology-enabled virtual work environments on the productivity and work-life balance of professional knowledge workers. Guidelines will be developed that improve organisational and individual outcomes for professional knowledge workers who use technology extensively in their interactions with others.
Governance of information technology programmes: achieving accountability, control and success. This project aims to improve the effectiveness with which IT-enabled programmes are managed by public and private organisations. The theoretical knowledge and guides for good practice emerging from this study will contribute to increased success in managing and delivering complex and vital programmes across Australia.
Artificial intelligence meets wireless sensor networks: filling the gaps between sensors using spatial reasoning. Monitoring potential disaster regions and integrating available information with expert knowledge can prevent disasters and save many lives. The outcome of our project is one of the key components for intelligent systems that can autonomously monitor the environment, make the correct inferences and issue appropriate warnings and recommendations.
Pattern Discovery of Discriminating Behaviour Associated with Hidden Communities. A sound understanding of discriminating behaviour in hidden communities, e.g. market manipulation, is essential for effective intervention and prevention. This project will deliver novel and workable algorithms and tools for modelling and pattern discovery of such behaviour. This will safeguard Australia by tackling crucial business and social issues like abnormal trading, online crime and terrorism, thereby enhanc ....Pattern Discovery of Discriminating Behaviour Associated with Hidden Communities. A sound understanding of discriminating behaviour in hidden communities, e.g. market manipulation, is essential for effective intervention and prevention. This project will deliver novel and workable algorithms and tools for modelling and pattern discovery of such behaviour. This will safeguard Australia by tackling crucial business and social issues like abnormal trading, online crime and terrorism, thereby enhancing public confidence, compliance and security in both the economy and society, by preventing and reducing economic and social impact. It will create skills and outcomes to further Australia's leadership in managing emerging data mining challenges and applications, and will deepen collaboration with eminent researchers worldwide.Read moreRead less
Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training ....Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training, which are anticipated to deepen our understanding of visual representation and make it easier to build and deploy computer vision applications and services. Examples of benefits include modernising machines in manufacturing and farming with visual intelligence. Read moreRead less
Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge ....Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge for optimising both hardware and software resources of a FC system. Outcomes of this project include practical solutions through building novel mathematical frameworks and optimisation objectives. The project is expected to provide efficient monitoring and control of intelligent spaces, management of urban and rural environments and will have applications in the areas of energy, security, transport and public health.Read moreRead less
Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less