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
Categorisation, communication and the local environment. Languages around the world incorporate different systems of categories, and understanding this variation can contribute to a better understanding of similarities and differences between cultures. This project examines how linguistic variation is shaped in part by variation in the local physical and social environment. The methods include computational analyses of large electronic data sets including dictionaries and linguistic corpora tha ....Categorisation, communication and the local environment. Languages around the world incorporate different systems of categories, and understanding this variation can contribute to a better understanding of similarities and differences between cultures. This project examines how linguistic variation is shaped in part by variation in the local physical and social environment. The methods include computational analyses of large electronic data sets including dictionaries and linguistic corpora that have become available only recently, and psychological experiments that probe the causal mechanisms that lead to variation across languages. The outcomes include computational tools that pick out key differences between languages and therefore support cross-cultural communication.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
The neurobiology of curiosity. This project aims to define the neurobiology of curiosity by combining cutting-edge techniques in computational modelling, pharmacointervention and neuroimaging. It is expected to lead to a comprehensive neuroscientific framework of curiosity, which will characterise its evolution over the lifespan, and its dependency on key neurotransmitter systems. Expected outcomes include a legacy of open access stimulus & data sets; the development of a global collaborative ne ....The neurobiology of curiosity. This project aims to define the neurobiology of curiosity by combining cutting-edge techniques in computational modelling, pharmacointervention and neuroimaging. It is expected to lead to a comprehensive neuroscientific framework of curiosity, which will characterise its evolution over the lifespan, and its dependency on key neurotransmitter systems. Expected outcomes include a legacy of open access stimulus & data sets; the development of a global collaborative network; and an increase in our national capacity and profile in decision neuroscience. The benefits of this project include laying the foundations for future interventions to improve curiosity, with potential downstream effects on many aspects of education, social & public policy.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
Prefrontal dopamine in the dynamic processes of learning across lifetime. To facilitate age-specific adaptive action in a changing environment, how we learn changes not only as we grow, but also as we age. However, the neurobiological processes in these age-related changes are poorly studied. This is a significant knowledge gap that needs to be addressed to promote healthy cognitive development and ageing. This research program aims to examine the contribution of prefrontal dopamine and its rece ....Prefrontal dopamine in the dynamic processes of learning across lifetime. To facilitate age-specific adaptive action in a changing environment, how we learn changes not only as we grow, but also as we age. However, the neurobiological processes in these age-related changes are poorly studied. This is a significant knowledge gap that needs to be addressed to promote healthy cognitive development and ageing. This research program aims to examine the contribution of prefrontal dopamine and its receptors D1 and D2 in associative learning and its inhibition at 9 distinct ages spanning development to ageing in male and female rats. The outcomes will provide a new neuroscientific framework to understand learning and memory throughout life, which will foster new research opportunities and inform our education and health.Read moreRead less
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