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
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
Seeing the forest and the trees: Cognitive and neural mechanisms underlying recognition of individual objects and sets. When confronted with a set of similar objects, such as a crowd of faces or a flow of oncoming cars, human observers can rapidly and seemingly automatically extract summary statistics of these sets of objects (e.g., mean expression or location). This research will provide insights into how the human visual system executes this massive feat of computation. This represents a vital ....Seeing the forest and the trees: Cognitive and neural mechanisms underlying recognition of individual objects and sets. When confronted with a set of similar objects, such as a crowd of faces or a flow of oncoming cars, human observers can rapidly and seemingly automatically extract summary statistics of these sets of objects (e.g., mean expression or location). This research will provide insights into how the human visual system executes this massive feat of computation. This represents a vital step in understanding vision in general and in eventually applying our knowledge to the development of artificial vision systems and to rehabilitation of visual disorders. The research will also investigate the effects of attentional load on perception of summary statistics of the environment, which is critical for tasks such as driving in busy traffic.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
Attention please! Selective attention and human associative learning. Selective attention allows us to pick useful pieces of information out of the mass of stimulation that we're faced with every moment. This project investigates how what we've previously learnt about the significance of events influences whether we'll pick them out as useful in future, and how this might be impaired by old age or mental disorder.
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
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
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
Decoding the neural representation of objects in the human brain. Humans can effortlessly recognise thousands of objects in a fraction of a second. This essential capacity is an integral part of our daily lives that allows us to recognise our keys, our car, our friends and family. This project will elucidate how humans recognise objects by investigating the neural representation of objects in the brain.