Evolutionary analyses of short-read sequences from pooled samples. This project aims to provide biologists with a means of making sound, statistical inferences about evolution by using next-generation data from mixed samples. When biologists make statements about history, they use evolutionary trees, frequently reconstructed from the genetic data of many individuals. Next-generation sequencing provides large amounts of genetic data at low cost, but biologists have difficulty using these data for ....Evolutionary analyses of short-read sequences from pooled samples. This project aims to provide biologists with a means of making sound, statistical inferences about evolution by using next-generation data from mixed samples. When biologists make statements about history, they use evolutionary trees, frequently reconstructed from the genetic data of many individuals. Next-generation sequencing provides large amounts of genetic data at low cost, but biologists have difficulty using these data for evolutionary research, particularly when they sample mixtures of DNA from many individuals. The anticipated value of this project is that it allows evolutionary biologists to capitalise on the benefits of next-generation sequencing, without sacrificing their ability to make reliable inferences about history.Read moreRead less
How novel ribosomal RNA gene repeat variants drive cellular function. The hundreds of ribosomal RNA gene repeat copies are a remarkable part of our genomes, as they encode the machinery responsible for all cellular protein synthesis and shape the structure of the nucleus. However, due to their high degree of sequence similarity, they still have not been assembled into the human genome reference. This project will resolve this impasse and furthermore uncover the functional impacts of a newly iden ....How novel ribosomal RNA gene repeat variants drive cellular function. The hundreds of ribosomal RNA gene repeat copies are a remarkable part of our genomes, as they encode the machinery responsible for all cellular protein synthesis and shape the structure of the nucleus. However, due to their high degree of sequence similarity, they still have not been assembled into the human genome reference. This project will resolve this impasse and furthermore uncover the functional impacts of a newly identified molecular diversity in the ribosomal RNA gene repeats. Outcomes include new paradigms for how the ribosomal RNA gene repeats drive protein synthesis and genome structure, and a blueprint to develop novel genomics applications for human health, biotechnology, and agriculture.Read moreRead less
Improving Modern Programming Language Performance: A Memory-Conscious Approach. The performance of modern programming languages such as Java and C# lags that of imperative languages such as C and Fortran. A significant source of the performance gap is poor memory behavior, which future computer architectures will exacerbate. This project addresses the problem of poor memory behavior in modern programming languages such as Java and C# through an integrated attack that incorporates new garbage c ....Improving Modern Programming Language Performance: A Memory-Conscious Approach. The performance of modern programming languages such as Java and C# lags that of imperative languages such as C and Fortran. A significant source of the performance gap is poor memory behavior, which future computer architectures will exacerbate. This project addresses the problem of poor memory behavior in modern programming languages such as Java and C# through an integrated attack that incorporates new garbage collection algorithms, run-time techniques that optimize running programs, and new compiler analyses with both static and dynamic optimizations. The project will give Australia an
international presence in a research area of great academic and commercial importance.
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Micro Virtual Machines: Abstraction, contained. This project will address a systemic source of inefficiency in widely used software which leads to many programs running as much as ten times slower and using considerably more energy than necessary, shortening battery life on mobile phones and increasing costs for large server farms. This inefficiency is endemic because it is due to the underlying languages rather than the particular software. This project will address this problem by developing a ....Micro Virtual Machines: Abstraction, contained. This project will address a systemic source of inefficiency in widely used software which leads to many programs running as much as ten times slower and using considerably more energy than necessary, shortening battery life on mobile phones and increasing costs for large server farms. This inefficiency is endemic because it is due to the underlying languages rather than the particular software. This project will address this problem by developing a high efficiency substrate, called a micro virtual machine, on which languages may be built.Read moreRead less
Genome evolution & adaptation of the multinuclear wheat stripe rust fungus. Animals and plants package their genomes into a single nucleus within each cell. In contrast, millions of fungal species accommodate multiple nuclei containing individual haploid genomes. It is currently unknown what the evolutionary implications are for this unusual genome division into multiple nuclei. Here we explore the evolutionary consequences of genome division into multiple nuclei for the first time by applying c ....Genome evolution & adaptation of the multinuclear wheat stripe rust fungus. Animals and plants package their genomes into a single nucleus within each cell. In contrast, millions of fungal species accommodate multiple nuclei containing individual haploid genomes. It is currently unknown what the evolutionary implications are for this unusual genome division into multiple nuclei. Here we explore the evolutionary consequences of genome division into multiple nuclei for the first time by applying cutting edge genome biology tools and algorithms. The economically significant study system is the devastating wheat stripe rust fungus. This pathogen costs Australian farmers over $100 million a year. New understanding is expected to lead to better disease management, reduced fungicide applications, and increased yields.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
Finding and exploiting interesting paths in multidimensional information spaces. This project will invent a new approach for searching within a large complex information space, finding interesting paths between points within the space, visualising the results, and supporting rich, human-centric user interaction with queries and results. This project will embody these techniques in a novel, internet-scale framework to support rapid development of large path search and visualisation applications. ....Finding and exploiting interesting paths in multidimensional information spaces. This project will invent a new approach for searching within a large complex information space, finding interesting paths between points within the space, visualising the results, and supporting rich, human-centric user interaction with queries and results. This project will embody these techniques in a novel, internet-scale framework to support rapid development of large path search and visualisation applications. Evaluation will be via development of several exemplar applications. The techniques and framework will be applicable to a broad range of economically important problems in areas as diverse as health, travel, scientific publication search, product marketing and software engineering.Read moreRead less
Machine-checked Foundations for Verified Vote Counting. The project will deliver a general methodology for developing formal logical specifications of the Acts of Parliament for many common systems for counting votes in preferential elections. The project will deliver corresponding computer programs to count votes according to these systems and will deliver formal independently checkable proofs that the programs meet their specification. Such formally verified computer programs provide a legally ....Machine-checked Foundations for Verified Vote Counting. The project will deliver a general methodology for developing formal logical specifications of the Acts of Parliament for many common systems for counting votes in preferential elections. The project will deliver corresponding computer programs to count votes according to these systems and will deliver formal independently checkable proofs that the programs meet their specification. Such formally verified computer programs provide a legally sound basis for counting votes by computer. The methodology will also allow electoral commissioners to improve the natural language descriptions of the relevant Acts of Parliament which are often woefully out of date with current practice.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less