Discovery Early Career Researcher Award - Grant ID: DE240100168
Funder
Australian Research Council
Funding Amount
$413,847.00
Summary
Self-Supervised Sequential Biomedical Image-Omics. This project aims to develop a self-supervised sequential biomedical image-omics model to uncover the underlying biological processes e.g., normal or abnormal. Sequential biomedical images are state-of-the-art imaging modalities which allow to depict changes in progression to the human body. New self-supervised machine learning algorithms are proposed to derive features from heterogenous and unlabelled sequential images. These derived features w ....Self-Supervised Sequential Biomedical Image-Omics. This project aims to develop a self-supervised sequential biomedical image-omics model to uncover the underlying biological processes e.g., normal or abnormal. Sequential biomedical images are state-of-the-art imaging modalities which allow to depict changes in progression to the human body. New self-supervised machine learning algorithms are proposed to derive features from heterogenous and unlabelled sequential images. These derived features will then be used to characterise the morphological and functional changes, which provide opportunities to increase understanding of progression of diseases of individual subject. The outcome from this project will provide new insights into system biology with potential future benefits in healthcare.Read moreRead less
Novel tractography-guided MRI methods for studying healthy brain ageing. Advances in imaging, and particularly Magnetic Resonance Imaging, have opened a new era in the study of the brain enabling a myriad of neuroscience discoveries. This project aims to develop new analysis methods to study and understand the variability in the human brain during ageing, exploiting the wealth of information contained in the so-called tractogram, a mapping of the brain’s wiring. This project expects to develop i ....Novel tractography-guided MRI methods for studying healthy brain ageing. Advances in imaging, and particularly Magnetic Resonance Imaging, have opened a new era in the study of the brain enabling a myriad of neuroscience discoveries. This project aims to develop new analysis methods to study and understand the variability in the human brain during ageing, exploiting the wealth of information contained in the so-called tractogram, a mapping of the brain’s wiring. This project expects to develop innovative imaging biomarkers to characterise the brain changes in the course of healthy brain ageing. Expected outcomes include novel imaging tools for neuroscience, which should allow us to map trajectories of normative healthy brain ageing and use them to identify lifestyle factors that impact these trajectories.Read moreRead less
High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful me ....High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful methods that will be mathematically rigorous and suitable for a wide variety of applications. The benefits are that the project will boost Australia’s position as a leader in innovation, and contribute to future developments over a wide area, from aerospace engineering to personalised computational oncology.Read moreRead less
Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists ....Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists and policymakers and the project outputs should provide widespread and significant benefits by improving policy and boosting Australia’s comparative advantage.Read moreRead less
Bayesian inference for psychological theories with intractable likelihood. This project pursues breakthroughs which allow important questions of basic and applied science to be addressed using mathematical theories from cognitive psychology. Advances are made through an interdisciplinary effort, combining recent developments in econometric and statistical methods and cognitive science. The outcomes will advance knowledge and open up new avenues for applied research in important aspects of psych .... Bayesian inference for psychological theories with intractable likelihood. This project pursues breakthroughs which allow important questions of basic and applied science to be addressed using mathematical theories from cognitive psychology. Advances are made through an interdisciplinary effort, combining recent developments in econometric and statistical methods and cognitive science. The outcomes will advance knowledge and open up new avenues for applied research in important aspects of psychology. This research will result in new methods available to the wider scientific community which open up new horizons for understanding basic cognition, and human behavior in many domains. Read moreRead less
Flexible models and methods for cognitive model-based decision-making. This project aims to apply mathematical decision models to important questions of basic and applied science. Advances will be pursued through an interdisciplinary effort, combining recent developments in econometric and statistical methods, cognitive science and computing. The expected outcomes will bring a proven and powerful approach to a new range of questions investigating psychological aspects of choices about health c ....Flexible models and methods for cognitive model-based decision-making. This project aims to apply mathematical decision models to important questions of basic and applied science. Advances will be pursued through an interdisciplinary effort, combining recent developments in econometric and statistical methods, cognitive science and computing. The expected outcomes will bring a proven and powerful approach to a new range of questions investigating psychological aspects of choices about health care and consumer purchases. This project will provide significant benefits to the wider scientific community to understand basic cognition, and human behaviour in many domains.Read moreRead less
High Dimensional Computation and Uncertainty. This project aims to establish powerful computational methods for high-dimensional problems - methods that are rigorous, and carefully tailored to specific applications, from physics, environment, manufacturing and finance, and often driven by uncertainty. The project will generate new knowledge in the area of high-dimensional computation, and develop technological innovations in key areas of science and industry. Expected outcomes include improved c ....High Dimensional Computation and Uncertainty. This project aims to establish powerful computational methods for high-dimensional problems - methods that are rigorous, and carefully tailored to specific applications, from physics, environment, manufacturing and finance, and often driven by uncertainty. The project will generate new knowledge in the area of high-dimensional computation, and develop technological innovations in key areas of science and industry. Expected outcomes include improved control of uncertainty in industry, enhanced international and interdisciplinary collaborations, and significant publications and presentations in international forums. The technological advancements will help boost Australia's position as a world leader in innovation.Read moreRead less
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
Interpretable Behaviour Analysis with External Structured Knowledge. This project aims to develop novel interpretable neural models for predictive analytics tasks on human behaviour, operating on sequence behaviour data associated with external supportive structured knowledge. It is expected to present theoretical foundations for robust representation learning on heterogeneous behaviour data and interpretable machine reasoning models, which can support a broad scope of intelligent systems. Expec ....Interpretable Behaviour Analysis with External Structured Knowledge. This project aims to develop novel interpretable neural models for predictive analytics tasks on human behaviour, operating on sequence behaviour data associated with external supportive structured knowledge. It is expected to present theoretical foundations for robust representation learning on heterogeneous behaviour data and interpretable machine reasoning models, which can support a broad scope of intelligent systems. Expected outcomes will be a next-generation interpretable behaviour analysis system with versatile abilities to reason over various data structures and provide a high-level interpretability about its reasoning procedure. The benefits will span the research and industry sectors, e.g., retail, healthcare, service provider.Read moreRead less
Statistical Analysis of State-Dependent Government Spending Multipliers. This project aims to provide a new statistical analysis of the government spending multiplier by acknowledging that government spending is the sum of sectoral spending which has heterogeneous effects on the economy. An added complication is that the multiplier can also be state-dependent, meaning that its magnitude can differ across recessions and expansions. Expected outcomes of this project include a better understanding ....Statistical Analysis of State-Dependent Government Spending Multipliers. This project aims to provide a new statistical analysis of the government spending multiplier by acknowledging that government spending is the sum of sectoral spending which has heterogeneous effects on the economy. An added complication is that the multiplier can also be state-dependent, meaning that its magnitude can differ across recessions and expansions. Expected outcomes of this project include a better understanding of the components of the multiplier by novel decomposition and the development of a new statistical test for the state-dependency of the multiplier. This should provide significant benefits to researchers by bringing in new tools and insights and to policymakers by providing timely guidance on fiscal policies.Read moreRead less