Trust-Oriented Data Analytics in Online Social Networks. Trust-oriented data analytics is essential in online social networks for reducing deceitful interactions and enhancing trust between users. This project aims to systematically devise innovative solutions by considering rich social contextual information as an important source of trust. The expected outcomes of this project include innovative solutions from a fundamental perspective to the challenges of context-aware trust propagation, trus ....Trust-Oriented Data Analytics in Online Social Networks. Trust-oriented data analytics is essential in online social networks for reducing deceitful interactions and enhancing trust between users. This project aims to systematically devise innovative solutions by considering rich social contextual information as an important source of trust. The expected outcomes of this project include innovative solutions from a fundamental perspective to the challenges of context-aware trust propagation, trust network searching/matching, and trustworthy/malicious user prediction in online social networks. This project is significant as it will advance the knowledge base for enabling a trustworthy social networking environment, benefiting billions of Australian and worldwide online social network users.Read moreRead less
Scaling Disk-Resident Learned Indexes For Database Systems. This project aims to investigate new disk-resident learned indexing algorithms to store and process data in database systems by advancing the state-of-the-art in memory-resident learned modeling. This project expects to generate new knowledge in the area of digital storage technologies utilising novel and efficient techniques in learned indexing for big data. This should provide significant benefits to enable modern database systems to ....Scaling Disk-Resident Learned Indexes For Database Systems. This project aims to investigate new disk-resident learned indexing algorithms to store and process data in database systems by advancing the state-of-the-art in memory-resident learned modeling. This project expects to generate new knowledge in the area of digital storage technologies utilising novel and efficient techniques in learned indexing for big data. This should provide significant benefits to enable modern database systems to scale with the massive growth of data, improve the efficiency of data processing, improve the effectiveness of projects that utilise big data, and dramatically reduce energy costs in Australian data centres when storing and retrieving data from databases and lower their carbon footprints.Read moreRead less
Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. T ....Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. The new paradigm should produce significant benefits for all fields in which the consequences of predictive inaccuracy are severe. Problems that lead to substantial economic, financial or environmental loss if predictions are incorrect will be given particular attention.Read moreRead less
Precision Epigenetics: Targeting The Epigenome To Treat Disease
Funder
National Health and Medical Research Council
Funding Amount
$1,940,576.00
Summary
Epigenetic marks are changes made to the DNA that allow genes to be switched off in some cells and switched on in others. These marks are critical to normal development and often go wrong in disease. We aim to find genes that add epigenetic marks to the DNA and understand how they co-operate at the molecular level to switch genes off. Our focus is on one such gene, SMCHD1. We are developing new drugs against SMCHD1 to treat incurable neurodevelopmental disorder PWS and muscular dystrophy FSHD.
Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation ....Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and road networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100668
Funder
Australian Research Council
Funding Amount
$435,000.00
Summary
Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations ....Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big streaming temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and social analysis.Read moreRead less
Next-Generation Distributed Graph Engine for Big Graphs. This project aims to develop an efficient and scalable distributed graph engine to process big graphs. In particular, we will investigate the foundations for the distributed real-time graph engine, focusing on graph storage and graph operators, and then provide solutions for a set of representative graph mining and query processing tasks. Expected outcomes of this project include theoretical foundations and a scalable real-time graph engin ....Next-Generation Distributed Graph Engine for Big Graphs. This project aims to develop an efficient and scalable distributed graph engine to process big graphs. In particular, we will investigate the foundations for the distributed real-time graph engine, focusing on graph storage and graph operators, and then provide solutions for a set of representative graph mining and query processing tasks. Expected outcomes of this project include theoretical foundations and a scalable real-time graph engine to process big graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and road networks.Read moreRead less
Unraveling ocean mixing and air-sea forcing along the Indo-Pacific exchange. This project aims to collect unprecedented observations and develop high resolution model simulations to examine changes in the Indonesian Throughflow (ITF) north of Australia. This project expects to develop new knowledge of ocean-atmosphere interactions along the path of the ITF from the Pacific to the Indian Ocean, which are the powerhouse that drives changes in winds and rainfall around Australia and the entire Indo ....Unraveling ocean mixing and air-sea forcing along the Indo-Pacific exchange. This project aims to collect unprecedented observations and develop high resolution model simulations to examine changes in the Indonesian Throughflow (ITF) north of Australia. This project expects to develop new knowledge of ocean-atmosphere interactions along the path of the ITF from the Pacific to the Indian Ocean, which are the powerhouse that drives changes in winds and rainfall around Australia and the entire Indo-Pacific region. Expected outcomes include a 1000-fold increase in the observations of mixing in the Indonesian seas and new understanding of the ocean-atmosphere processes that control water property change along the ITF. This should lead to strong improvement in the skill of climate forecast models in the Australian region.Read moreRead less
Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suic ....Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suicide risk; use these systems to investigate how different situational factors interact with different combinations of service interventions to influence suicide risk; and share the findings to reduce railway suicide in Australia and overseas.Read moreRead less
Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. ....Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. The expected outcome is a national prototype, serving the public with accurate and trusted time, that will form the basis of the next generation timekeeping system for the Internet and the Internet of Things. Expected benefits include enhanced productivity across the digital economy, and resilience to GPS failures.Read moreRead less