Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, ....Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100153
Funder
Australian Research Council
Funding Amount
$361,446.00
Summary
Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to impr ....Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to improve project awareness, and to increase productivity goals. The outcomes would include a comprehensive decision and awareness support system for software projects, based on automating the creation and continual updating of developer activity summaries and measures.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100941
Funder
Australian Research Council
Funding Amount
$392,778.00
Summary
Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects bef ....Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects before they impact end users. This should provide significant benefits including accelerating the productivity of the software industry while preventing software defects in many critical domains including smart city and e-health applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100021
Funder
Australian Research Council
Funding Amount
$413,665.00
Summary
An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s as ....An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s assistant, consisting of a set of automated tools, covering software development, testing and maintenance. This should provide significant benefits to the Australian software development industry by improving developers’ productivity and reduce overall project costs.Read moreRead less
Secure Crowdsourcing Classification with Privacy Protection against Servers. This project aims to enable comprehensive quality data classification via secure crowdsourcing. The quality of a data-intensive process, such as a Machine Learning algorithm, depends on the input data quality. By using a crowdsourcing classification, the project expects to overcome the painstaking and costly process of humans correctly annotating extensive input data from diverse real information. The expected outcomes ....Secure Crowdsourcing Classification with Privacy Protection against Servers. This project aims to enable comprehensive quality data classification via secure crowdsourcing. The quality of a data-intensive process, such as a Machine Learning algorithm, depends on the input data quality. By using a crowdsourcing classification, the project expects to overcome the painstaking and costly process of humans correctly annotating extensive input data from diverse real information. The expected outcomes are innovative technologies, guaranteeing accuracy and confidentiality of annotation results whilst protecting the privacy of data classification results. It enhances data-intensive outputs quality, which will benefit large data-intensive applications, such as cybersecurity protections via intrusion detection.Read moreRead less
Efficient Multi-key Homomorphic Encryption and Its Applications. Multi-key homomorphic encryption (MKHE) is a key technology that functions to allow multiple users to supply their private input for collaboration in the cloud while keeping the user data confidential. Unfortunately, it is very difficult to obtain efficient MKHEs. This project aims to overcome this challenge by enabling novel efficient MKHEs. The expected outcomes of this project are to develop innovative cryptographic technologies ....Efficient Multi-key Homomorphic Encryption and Its Applications. Multi-key homomorphic encryption (MKHE) is a key technology that functions to allow multiple users to supply their private input for collaboration in the cloud while keeping the user data confidential. Unfortunately, it is very difficult to obtain efficient MKHEs. This project aims to overcome this challenge by enabling novel efficient MKHEs. The expected outcomes of this project are to develop innovative cryptographic technologies which realise efficient MKHEs, together with their cryptographic libraries and practical applications in solving industry problems. This will provide direct economic benefits to Australian industry through the enablement of advanced technologies and low-cost business solutions which are developed in Australia.Read moreRead less
Enabling Anonymity and Privacy for Blockchain Technology in a Quantum World. Blockchain is a promising technology in the digital world today. However, existing approaches for enabling blockchain applications, particularly with privacy protection and anonymity, are vulnerable to quantum computer attacks. This project aims to enable novel cryptographic mechanisms together with their cryptographic libraries for protecting blockchain in the quantum world, hence, post-quantum secure blockchain. The e ....Enabling Anonymity and Privacy for Blockchain Technology in a Quantum World. Blockchain is a promising technology in the digital world today. However, existing approaches for enabling blockchain applications, particularly with privacy protection and anonymity, are vulnerable to quantum computer attacks. This project aims to enable novel cryptographic mechanisms together with their cryptographic libraries for protecting blockchain in the quantum world, hence, post-quantum secure blockchain. The expected outcomes of this project include innovative technologies, as well as secure and practical post-quantum protocols for protecting future blockchain applications. This will provide economic and social benefits to Australian industry through the enablement of advanced technologies which are developed in Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100019
Funder
Australian Research Council
Funding Amount
$408,000.00
Summary
A Scalable and Adaptive-Resilient Blockchain. This project aims to address the security and scalability challenges that limit blockchain adoption. Existing blockchains do not scale and are vulnerable to attacks (e.g. with a total loss of over US$1 billion in 2019). This project expects to improve security by adaptively enforcing the currently broken security assumptions, and to improve scalability by designing blockchains with high concurrency via relaxed criteria on the ordering of transactions ....A Scalable and Adaptive-Resilient Blockchain. This project aims to address the security and scalability challenges that limit blockchain adoption. Existing blockchains do not scale and are vulnerable to attacks (e.g. with a total loss of over US$1 billion in 2019). This project expects to improve security by adaptively enforcing the currently broken security assumptions, and to improve scalability by designing blockchains with high concurrency via relaxed criteria on the ordering of transactions. The expected outcomes include foundations and practical solutions for self-adaptive, secure and scalable blockchains. The benefits of this would be improved confidence in and capacity for building blockchain applications, which have a predicted value of over US$3.1 trillion by 2030.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100415
Funder
Australian Research Council
Funding Amount
$432,483.00
Summary
Cross-layer Design for Ultra-reliable Low-latency Communications. This project aims to develop fundamental theories and practical technologies for ultra-reliable low-latency communications – one of the grand challenges in 5G cellular networks. Due to the dynamic nature of wireless networks, existing approaches dividing networks into multiple layers cannot guarantee a hard deadline with high reliability. The outcomes of the project will be cross-layer models for characterising the end-to-end perf ....Cross-layer Design for Ultra-reliable Low-latency Communications. This project aims to develop fundamental theories and practical technologies for ultra-reliable low-latency communications – one of the grand challenges in 5G cellular networks. Due to the dynamic nature of wireless networks, existing approaches dividing networks into multiple layers cannot guarantee a hard deadline with high reliability. The outcomes of the project will be cross-layer models for characterising the end-to-end performance, a prediction and communication co-design framework for improving the delay-reliability trade-off, and an online architecture for implementing model-based algorithms in real networks. They will underpin the development of remote control and advancing automation in manufacturing, transportation, mining, etc.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101091
Funder
Australian Research Council
Funding Amount
$402,160.00
Summary
Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of th ....Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of this project include new theories, techniques, and an automated system that provides insightful feedback, suitable reviewer recommendations, and fine-grained effort prioritisation. Significant benefits are expected to improve the production of Australia's software and the quality of safety-critical software systems.Read moreRead less