Modelling Adversarial Noise for Trustworthy Data Analytics. Adversarial robustness is a core property of trustworthy machine learning. This project aims to equip machines with the ability to model adversarial noise for defending adversarial attacks. The project expects to produce the next great step for artificial intelligence – the potential to robustly explore and exploit deceptive data. Expected outcomes of this project include theoretical foundations for modelling adversarial noise and the n ....Modelling Adversarial Noise for Trustworthy Data Analytics. Adversarial robustness is a core property of trustworthy machine learning. This project aims to equip machines with the ability to model adversarial noise for defending adversarial attacks. The project expects to produce the next great step for artificial intelligence – the potential to robustly explore and exploit deceptive data. Expected outcomes of this project include theoretical foundations for modelling adversarial noise and the next generation of intelligent systems to accommodate data in a noisy and hostile environment. This should benefit science, society, and the economy nationally and internationally through the applications to trustworthily analyse their corresponding complex data. 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
The role of social-emotional learning in attaining literacy and numeracy. This project aims to characterise variability in developmental pathways to literacy and numeracy, and the factors that contribute to this variation, utilising innovative analytical approaches and population data. This project expects to generate new knowledge regarding the role of school-based social-emotional learning programs in supporting children’s achievement of literacy and numeracy. Expected outcomes of the project ....The role of social-emotional learning in attaining literacy and numeracy. This project aims to characterise variability in developmental pathways to literacy and numeracy, and the factors that contribute to this variation, utilising innovative analytical approaches and population data. This project expects to generate new knowledge regarding the role of school-based social-emotional learning programs in supporting children’s achievement of literacy and numeracy. Expected outcomes of the project include enhanced collaboration with government to deliver policy-relevant information on the most effective targets and timing for delivering social-emotional programs that maximise academic learning. This should assist policy makers to develop better strategies to support every child’s academic achievement.Read moreRead less
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
Gendered engagement and participation in sciences and mathematics. This project aims to identify the reasons for the declining numbers of girls (and boys) studying sciences, technology, engineering and mathematics (STEM) subjects during secondary school. This project will conduct complementary longitudinal studies in Australia, in collaboration with leading international scholars, analysing declining motivations, especially for girls/women, to show how this predicts different STEM career choices ....Gendered engagement and participation in sciences and mathematics. This project aims to identify the reasons for the declining numbers of girls (and boys) studying sciences, technology, engineering and mathematics (STEM) subjects during secondary school. This project will conduct complementary longitudinal studies in Australia, in collaboration with leading international scholars, analysing declining motivations, especially for girls/women, to show how this predicts different STEM career choices and actual occupational outcomes, to yield theoretical developments and inform policy to improve the participation of girls/women (and boys/men) in these fields. Expected outcomes of this project include the provision of comprehensive evidence-informed recommendations to Federal and State government, industry and education stakeholders, which will enable the coordinated development of intervention programs to address these issues.Read moreRead less
Testing the Modularity of Memory. Researchers disagree about whether verbal and visual working memory (WM) storage occurs in separate modules. Recent evidence suggests that only verbal memoranda have access to a specialised module, while visual memories make use of more general resources. This project aims to re-examine interference between verbal and visual memoranda using statistical methods specialised for assessing whether multiple latent factors underlie performance on recognition memory ta ....Testing the Modularity of Memory. Researchers disagree about whether verbal and visual working memory (WM) storage occurs in separate modules. Recent evidence suggests that only verbal memoranda have access to a specialised module, while visual memories make use of more general resources. This project aims to re-examine interference between verbal and visual memoranda using statistical methods specialised for assessing whether multiple latent factors underlie performance on recognition memory tasks, examining adult and child populations. This is expected to influence applications of WM theory in many everyday settings, resulting in improvements in educational practices, workplace procedures, and clinical treatments that depend on theoretical understandings of limits in cognition.Read moreRead less
Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications ....Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications including consistency checking and spatial query pre-processing. The project will help in extracting knowledge from massive spatial databases, meeting the growing needs of naive users for spatial information and establishing Australia as a major player in spatial cognition research and in the development of geo-location services.Read moreRead less
Situated Anomaly Detection in an Open Environment. This project aims to investigate situated anomaly detection in an open environment. Existing anomaly detection techniques follow the setting of conventional machine learning and discover anomalies from a set of collected data. In contrast, this project proposes to develop the next-generation of anomaly detection algorithms by learning from interactions with an open environment, which enables the discovery of new anomalies and the early detection ....Situated Anomaly Detection in an Open Environment. This project aims to investigate situated anomaly detection in an open environment. Existing anomaly detection techniques follow the setting of conventional machine learning and discover anomalies from a set of collected data. In contrast, this project proposes to develop the next-generation of anomaly detection algorithms by learning from interactions with an open environment, which enables the discovery of new anomalies and the early detection of anomalies. The established theories and developed algorithms will advance frontier technologies in machine intelligence. The success of the project will contribute to a wide range of real applications in cybersecurity, defence and finance, bringing massive social and economic benefits. Read moreRead less
Inventiveness and the progress of product innovation. Quantitative models of inventiveness will be used to forecast the potential rate of improvement of a technology and to re-design products to improve more rapidly and steadily. By focusing on innovation in products and technologies in energy conversion, this research can guide development funding for low-carbon energy generation.
Control and learning for enhancing capabilities of quantum sensors. This project aims to develop new theories and algorithms to enhance capabilities in engineering quantum sensors from the perspective of systems and control. The project is significant because it is anticipated to advance key knowledge and provide systematic methods to enable achievement of high-precision sensing for wide applications, e.g., early disease detection, medical research, discovery of ore deposits and groundwater moni ....Control and learning for enhancing capabilities of quantum sensors. This project aims to develop new theories and algorithms to enhance capabilities in engineering quantum sensors from the perspective of systems and control. The project is significant because it is anticipated to advance key knowledge and provide systematic methods to enable achievement of high-precision sensing for wide applications, e.g., early disease detection, medical research, discovery of ore deposits and groundwater monitoring. The intended outcomes are fundamental theories, effective control and learning algorithms for achieving highly-sensitive sensors. These outcomes should make important contributions to and deliver new knowledge and skills for Australia's sensing industries, which could benefit Australia's economic growth.Read moreRead less