Next-generation Intelligent Explorations of Geo-located Data . This project aims to build a next-generation intelligent exploration framework over massive geo-located data, varying from points-of-interest to areas-of-interest data, in order to dramatically enhance user experiences when interacting with various forms of geo-located data over maps. Expected outcomes include novel exploration models, efficient and scalable algorithms for retrieving and visualizing the exploration results, online up ....Next-generation Intelligent Explorations of Geo-located Data . This project aims to build a next-generation intelligent exploration framework over massive geo-located data, varying from points-of-interest to areas-of-interest data, in order to dramatically enhance user experiences when interacting with various forms of geo-located data over maps. Expected outcomes include novel exploration models, efficient and scalable algorithms for retrieving and visualizing the exploration results, online updating of personal preferences during the life cycle of exploration, as well as a prototype system to evaluate and demonstrate practical value of the research. It will complement existing map services and significantly benefit many location-aware services, e.g., logistics, health services and urban planning.Read moreRead less
Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points ....Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points of interest rather than directly seeking trips from others to set destinations. It also aims to introduce privacy-aware dynamic matching of sharers, and expand to transportation at large, to generate new shared transportation services. The expected outcome of this project is to elevate today's taxi-like ride-sharing services to true ride-sharing arrangements. This is expected to provide benefits such as reduced traffic and emissions, as well as addressing parking issues and other traffic problems.Read moreRead less
Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The chal ....Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The challenge is to analyse individuals’ personal data, and discover how they differentiate from and overlap with others’. This project expects to enable businesses to deepen customer satisfaction and individuals to better understand their personal place in a connected world.Read moreRead less
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools ....Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools to facilitate government, companies, individuals, and organisations to enhance their information gathering and privacy-preserving capabilities. This is expected to enhance the credibility of the government and organisations and save the possible financial loss of companies and individuals.Read moreRead less
Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the ext ....Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the extent of such biases, and develop models that are both more socially equitable, as well as less prone to expose private data in the learned representations. In doing so, it will make NLP more accessible to new populations of users, and remove socio-technological barriers to NLP uptake.Read moreRead less
Sensor stream pattern mining for automatic anomaly recognition and intervention. This project will develop a general framework of accurate automatic recognition of meaningful anomalies in multivariate sensor data streams that require action to avoid detrimental events and allow automatic intervention for efficient mitigation. Existing anomaly recognition algorithms miss many patterns and manually relating co-occurring stream patterns to an anomaly is inefficient and error-prone. The project expe ....Sensor stream pattern mining for automatic anomaly recognition and intervention. This project will develop a general framework of accurate automatic recognition of meaningful anomalies in multivariate sensor data streams that require action to avoid detrimental events and allow automatic intervention for efficient mitigation. Existing anomaly recognition algorithms miss many patterns and manually relating co-occurring stream patterns to an anomaly is inefficient and error-prone. The project expects to develop methods for intercepting a combination of co-occurring patterns to ascertain what an anomaly is and identify the anomaly and its stages that indicate the necessity of intervention. This project will advance techniques for sensor stream data mining and enable general applications of sensor surveillance and automatic mechanical intervention.Read moreRead less
A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location da ....A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location data and enhanced international collaborations. The project will support and enhance a wide range of indoor applications such as emergency services, assisted healthcare systems, indoor asset tracking, event planning, indoor venue management, and consumer experience.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100188
Funder
Australian Research Council
Funding Amount
$438,582.00
Summary
Generating Plots with Dialogue Based Executable Semantic Parsing. This project aims to address the limited abilities of dialogue systems by developing new models and data collection techniques. The project expects to address a major gap in Natural Language Processing using a model that generates computer code and updates it in response to user requests. Expected outcomes of this project include a system that interacts with a user in plain English to analyse data, and efficient methods of trainin ....Generating Plots with Dialogue Based Executable Semantic Parsing. This project aims to address the limited abilities of dialogue systems by developing new models and data collection techniques. The project expects to address a major gap in Natural Language Processing using a model that generates computer code and updates it in response to user requests. Expected outcomes of this project include a system that interacts with a user in plain English to analyse data, and efficient methods of training the system with minimal expert input. This should provide significant benefits to research and business by broadening the accessibility and efficiency of data analysis, enabling faster and wiser decisions.Read moreRead less