Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Developing Interpretable Machine Learning Models For Clinical Imaging And Single-cell Genomics
Funder
National Health and Medical Research Council
Funding Amount
$1,312,250.00
Summary
Machine learning methods will be vital to make best use of the deluge of data generated by high-throughput technologies in biomedical science. To get the most out of these models, however, we need to be able to unpack the 'black box'. I will use curated clinical and public research data to benchmark and develop interpretable deep learning models and software tools. These models will be used for breast cancer screening programs and for analysis of complex, large-scale single-cell genomics data.
Ontology Based Multisite Distributed Software Development. Increasingly clients in cities are developing software overseas or in regional centres. The participating companies have found existing centralized software engineering techniques inadequate for multisite development. This project produces new principles and techniques for multisite distributed software development. Thus it proposes a new methodology, a new project management approach, a new workflow tracking technique and a new concept ....Ontology Based Multisite Distributed Software Development. Increasingly clients in cities are developing software overseas or in regional centres. The participating companies have found existing centralized software engineering techniques inadequate for multisite development. This project produces new principles and techniques for multisite distributed software development. Thus it proposes a new methodology, a new project management approach, a new workflow tracking technique and a new concept of software object/component that allows differentiated access. A platform is also developed for use in field studies for validation and benchmarking. The results will help Australia become a provider of software services for international clients and permit devolution to regional centres.Read moreRead less
Preparing Australia For Genomic Medicine: A Proposal By The Australian Genomics Health Alliance
Funder
National Health and Medical Research Council
Funding Amount
$25,000,000.00
Summary
The sequencing of the human genome brings the possibility of more accurate identification of the underlying basis of many diseases. This technology has moved so rapidly, however, that clinical access has been limited. In this application, a national alliance of clinicians, researchers, health economists and policymakers will evaluate the case for clinical genomics across inherited disease and cancer, determine how best to deliver this to the patient and train a capable workforce.
Discovery Early Career Researcher Award - Grant ID: DE170101081
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t ....Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Transcription factor – enhancer – promoter based regulatory networks. This project aims to develop new understanding on how multicellular organisms (including humans) develop, and how mutations in distant regions of the genome can affect human traits. The way the human genome is interpreted by the cellular machinery is still a mystery. We have a reference sequence and know where the majority of coding genes are, but we are far from understanding how the genome is regulated to generate the divers ....Transcription factor – enhancer – promoter based regulatory networks. This project aims to develop new understanding on how multicellular organisms (including humans) develop, and how mutations in distant regions of the genome can affect human traits. The way the human genome is interpreted by the cellular machinery is still a mystery. We have a reference sequence and know where the majority of coding genes are, but we are far from understanding how the genome is regulated to generate the diversity of cell types in our bodies. Enhancer regions interact with proximal promoters to regulate gene expression level and tissue-specificity. This project aims to develop transcriptional regulatory network models using high throughput chromatin interaction data and expression perturbation to link promoter and enhancers genome-wide.Read moreRead less
Identification Of Glaucoma Susceptibility Variants By Exome Sequencing In Extended Pedigrees Showing Prior Evidence Of Gene Segregation.
Funder
National Health and Medical Research Council
Funding Amount
$694,002.00
Summary
Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for tr ....Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for treatment or diagnosis.Read moreRead less
Automation of metric temporal reasoning. A major contemporary engineering concern is to ensure the predictable and robust operation of computer systems involving software, hardware, and human users. The need for systematic and careful construction of such systems requires the development of formal methods based on a dense view of time rather than the traditional step-by-step models.