In the Driver's seat: role of trace elements in enabling crustal fluid flow. This proposal aims to systematically investigate the role of trace elements in controlling the kinetics, product composition, and feed-back between fluid flow and the reaction interface, in fluid-driven mineral reactions. This project expects to provide a framework for the integration of activator trace elements in models of crustal fluid flow and their application in the recovery of base, precious, and critical metals, ....In the Driver's seat: role of trace elements in enabling crustal fluid flow. This proposal aims to systematically investigate the role of trace elements in controlling the kinetics, product composition, and feed-back between fluid flow and the reaction interface, in fluid-driven mineral reactions. This project expects to provide a framework for the integration of activator trace elements in models of crustal fluid flow and their application in the recovery of base, precious, and critical metals, using interdisciplinary approaches across geochemistry, mineral engineering and material sciences. Expected outcomes include improved prediction of the transport of metals and fluids in geo-systems. This should provide significant benefits towards integrating the mineral value chain from exploration to mining and metallurgy.Read moreRead less
Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a sys ....Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing. Read moreRead less
Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given comp ....Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given computational budget. Expected outcomes of this project include efficient, effective and broadly applicable time series classification technologies. This should provide significant benefits to myriad sectors, transforming data science for time series problems and supporting innovation in industry, commerce and government.Read moreRead less
Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowled ....Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowledge and an approach to fast-adapt bilevel optimization solutions when required computing resources change. The anticipated outcomes should significantly improve the reliability of ML with benefits for safety learning and computing resource optimisation in ML-based data analytics.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Constraint-based Privacy Preserving BioSignal Data Management on Blockchain. This project aims to address the issue of user privacy in Bio-Signal data analysis by utilizing the capabilities of differential privacy, smart contracts and blockchain technologies. This project expects to generate new knowledge in the area of privacy to develop an advanced privacy-preserving Bio-Signal data analytic framework. The expected outcomes of this project include increased privacy of user data, and the unifi ....Constraint-based Privacy Preserving BioSignal Data Management on Blockchain. This project aims to address the issue of user privacy in Bio-Signal data analysis by utilizing the capabilities of differential privacy, smart contracts and blockchain technologies. This project expects to generate new knowledge in the area of privacy to develop an advanced privacy-preserving Bio-Signal data analytic framework. The expected outcomes of this project include increased privacy of user data, and the unification of standards on human-specific data analysis, saving time and money spent on privacy breaches. This should provide significant benefits in preserving the quality and integrity of the healthcare services provided by the Australian government and private sector.Read moreRead less
Time Series Classification for Complex Dynamic Global Problems. This project aims to increase understanding of complex dynamic processes by creating new ways of analysing large quantities of data collected over time. These new approaches will be specifically designed to greatly improve the understanding obtained from time varying data for trillions of global earth observation data points in an application-agnostic way that is applicable to many tasks. The outcomes are expected to advance the the ....Time Series Classification for Complex Dynamic Global Problems. This project aims to increase understanding of complex dynamic processes by creating new ways of analysing large quantities of data collected over time. These new approaches will be specifically designed to greatly improve the understanding obtained from time varying data for trillions of global earth observation data points in an application-agnostic way that is applicable to many tasks. The outcomes are expected to advance the theory and practice of time-series data analysis and transform the analysis of complex dynamics. This should support innovation in industry, commerce, government and research and magnify benefit from many data investments including the $1 billion Australian governments invest annually in satellite imaging.Read moreRead less
Combating Fake News on Social Media: From Early Detection to Intervention. The project aims to detect fake news early to minimise the negative impact of false information. This project expects to devise novel solutions to address technical challenges for detection of fake news with scarce signals. Expected outcomes of this project include a suite of data mining and machine learning models for identification of fake news from the social media stream, prediction of user propagation of false infor ....Combating Fake News on Social Media: From Early Detection to Intervention. The project aims to detect fake news early to minimise the negative impact of false information. This project expects to devise novel solutions to address technical challenges for detection of fake news with scarce signals. Expected outcomes of this project include a suite of data mining and machine learning models for identification of fake news from the social media stream, prediction of user propagation of false information as well as recommendation of truthful news to counteract adversarial fake news. This project should generate technologies that enhance the integrity of the online echo system and benefit media providers and online population within Australia and across the world. Read moreRead less
The sparrows in the mining towns: a century of adaptation to contamination. Our research will characterise how contamination from the extraction of precious metals can spread through the environment and how it effects a highly urbanised bird – the house sparrow. In many cases, populations of these birds have been intimately associated with mining operations for over a century, and our recent work has provided evidence of adaptation over time. House sparrows provide a great natural system to unde ....The sparrows in the mining towns: a century of adaptation to contamination. Our research will characterise how contamination from the extraction of precious metals can spread through the environment and how it effects a highly urbanised bird – the house sparrow. In many cases, populations of these birds have been intimately associated with mining operations for over a century, and our recent work has provided evidence of adaptation over time. House sparrows provide a great natural system to understand the genetic potential of organisms to adapt to anthropomorphic change in the environment connected with the resources industry. Our work, will bring new insight into the future management of environmental contamination, and the mitigation of adverse effects arising from resource extraction.Read moreRead less
Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques fo ....Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques for situation awareness in big media. We expect to develop a system to evaluate the proposed situation awareness framework. The outcomes of the project will benefit social media analysis and big data fields. It will also improve the government services by enabling the real time situation awareness in crisis.Read moreRead less