Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can g ....Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can greatly speed up an algorithm and improve its accuracy. This project aims to design improved algorithms that harness auxiliary data to solve selected high-impact NP-hard graph problems, and will build a new empowering theory to discern when auxiliary data can be used to improve algorithms.Read moreRead less
Ancient stars: the origin of elements. The story of the origin of the elements fascinates mankind and touches many branches of science. This project combines new stellar population models of the oldest stars with new data from the Australian million-star GALactic Archaeology with HERMES (GALAH) survey to address basic astrophysical problems: mixing in stars, mass transfer in binary stars and measurement of the masses of the first stars. Knowing how these ancient stars behave is crucial to unders ....Ancient stars: the origin of elements. The story of the origin of the elements fascinates mankind and touches many branches of science. This project combines new stellar population models of the oldest stars with new data from the Australian million-star GALactic Archaeology with HERMES (GALAH) survey to address basic astrophysical problems: mixing in stars, mass transfer in binary stars and measurement of the masses of the first stars. Knowing how these ancient stars behave is crucial to understanding element production in the early Universe, both in our Milky Way and distant galaxies. By statistically comparing new models to the GALAH data, this project aims to measure the masses of the oldest galactic stars directly impacting branches of astrophysics from planets to galaxies.Read moreRead less
The red belly blockchain: a scalable blockchain for internet of things. This project aims to offer a blockchain that scales with the number of participants. There have been major investments in blockchain technologies during the last year as blockchains promise to disrupt industries like supply chains. Unfortunately, blockchains cannot solve this problem in their current form, because they cannot scale. They require resources that grow with the number of participants and yet fail at providing in ....The red belly blockchain: a scalable blockchain for internet of things. This project aims to offer a blockchain that scales with the number of participants. There have been major investments in blockchain technologies during the last year as blockchains promise to disrupt industries like supply chains. Unfortunately, blockchains cannot solve this problem in their current form, because they cannot scale. They require resources that grow with the number of participants and yet fail at providing increasing performance. The project will leverage many devices of limited resources to offer higher performance and will impact the distributed computing field by establishing a new connection between energy efficient systems and highly scalable distributed algorithms.Read moreRead less
Rethinking animals in research: Developing a novel ethical framework. Current approaches to animal ethics face challenges addressing significant problems in animal research. These problems include: harms to research workers and animals, poor translation of results from animals to humans leading to ineffective treatments and poorly directed future research efforts. This project addresses these challenges by developing an innovative, empirically-informed relational approach to animal ethics. The n ....Rethinking animals in research: Developing a novel ethical framework. Current approaches to animal ethics face challenges addressing significant problems in animal research. These problems include: harms to research workers and animals, poor translation of results from animals to humans leading to ineffective treatments and poorly directed future research efforts. This project addresses these challenges by developing an innovative, empirically-informed relational approach to animal ethics. The new approach will deliver a novel framework that minimises harms to humans and animals, and improves the quality of results obtained from experiments. Benefits include a more ethically robust practice of animal research and more targeted deployment of finite research resources.Read moreRead less
Provably Secure Cryptography Techniques: Effective, Elegant, and Economic. This project aims to contribute to advanced knowledge and techniques to remove relaxed proof factors from provable security. Cryptography nowadays can be proven secure and must be provably secure before being adopted for data protection. Until today, most cryptography schemes are still using some relaxed proof factors to prove security, but using these relaxed factors was risky. The expected outcomes are proof methodolog ....Provably Secure Cryptography Techniques: Effective, Elegant, and Economic. This project aims to contribute to advanced knowledge and techniques to remove relaxed proof factors from provable security. Cryptography nowadays can be proven secure and must be provably secure before being adopted for data protection. Until today, most cryptography schemes are still using some relaxed proof factors to prove security, but using these relaxed factors was risky. The expected outcomes are proof methodologies for researchers to prove security in an easy way (effective), cryptography techniques for proving security without any relaxed proof factors for cryptography schemes (elegant), and more practical cryptography schemes with elegant proofs to enable Australians to receive benefit from secure data protection (economic).
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Defining disease: Addressing the problem of overdiagnosis. This project will investigate and define the limits of physical disease, to answer questions about when a presentation is a disease, and when it is simply a risk factor or mild condition. The ensuing account of disease will make a practical contribution to growing international concern about asymptomatic people being diagnosed and treated for conditions that will not cause any health problems ("overdiagnosis"). The research will provide ....Defining disease: Addressing the problem of overdiagnosis. This project will investigate and define the limits of physical disease, to answer questions about when a presentation is a disease, and when it is simply a risk factor or mild condition. The ensuing account of disease will make a practical contribution to growing international concern about asymptomatic people being diagnosed and treated for conditions that will not cause any health problems ("overdiagnosis"). The research will provide normative grounds for evaluating disease claims. Results will reduce the harm caused by people receiving treatment that they do not require, make a practical contribution to debates about the scope of health care, and yield findings that can help to reduce the cost-burdens associated with overdiagnosis.Read moreRead less
Deep Adder Networks on Edge Devices. This project aims to empower edge devices with intelligence by developing advanced deep neural networks that address the conflict between the high resource requirements of deep learning and the generally inadequate performance of the edge. Multiplication has been the dominant type of operation in deep learning, though the addition is known to be much cheaper. This project expects to yield theories and algorithms that allow deep neural networks consisting of n ....Deep Adder Networks on Edge Devices. This project aims to empower edge devices with intelligence by developing advanced deep neural networks that address the conflict between the high resource requirements of deep learning and the generally inadequate performance of the edge. Multiplication has been the dominant type of operation in deep learning, though the addition is known to be much cheaper. This project expects to yield theories and algorithms that allow deep neural networks consisting of nearly pure additions to fulfil the requisites of accuracy, robustness, calibration and generalisation in real-world computer vision tasks. The success of this project will benefit deep learning-based products on smartphones or robots in health and cybersecurity.Read moreRead less
Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network sec ....Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network security and climate extremes. The project expects to change our way of thinking in how to be smarter about what data we use (and collect) for analysis, rather than relying on brute force analysis of large datasets. The project is expected to transform the knowledge base of the discipline, and the resulting techniques will enable across-the-board research advances for many industries and disciplines.Read moreRead less
New statistical methods for identifying micro-ribonucleic acid (miRNA) regulatory networks. Understanding gene regulatory networks is critical in the understanding of fundamental biological systems. These networks have important implications for the discovery of fundamental mechanisms relating to the diagnosis and management of many illnesses. This research will provide new statistical methods to identify regulatory micro-ribonucleic acid modules and to understand their relationship in gene regu ....New statistical methods for identifying micro-ribonucleic acid (miRNA) regulatory networks. Understanding gene regulatory networks is critical in the understanding of fundamental biological systems. These networks have important implications for the discovery of fundamental mechanisms relating to the diagnosis and management of many illnesses. This research will provide new statistical methods to identify regulatory micro-ribonucleic acid modules and to understand their relationship in gene regulatory networks through multiple covariance estimation and multivariate classification techniques. My results should enable researchers to better understand the regulation underlying biological systems, leading to improved human health, medical and biological research outcomes.Read moreRead less
Algorithmics for visual analytics of massive complex networks. The project will provide new scalable algorithms for visual analytics of massive complex networks. These fast algorithms will enable security analysts to detect abnormal behaviours such as money laundering, biologists to understand protein-protein interaction networks, and support software engineers new ways of understanding large software systems.