Discovery Early Career Researcher Award - Grant ID: DE200100200
Funder
Australian Research Council
Funding Amount
$418,398.00
Summary
Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological syste ....Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.
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Saving energy on trains - demonstration, evaluation, integration. Reducing energy use from rail transport will significantly contribute to cutting carbon dioxide emissions. This project will develop a toolkit to facilitate the introduction of in-cab technologies that help train drivers save energy and stay on time. The toolkit will make it easier to demonstrate, evaluate and integrate the system in a range of railways.
Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less
Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially impor ....Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially important results in applications.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Optimisation of Signal-to-Noise Ratio in Electrical and Electromagnetic Investigations. Electrical and electromagnetic geophysical methods have been used extensively for mineral exploration, and are developing a role in salinity mapping and contaminant identification. To enhance the utility of such methods for very shallow targets (in the case of salinity) and deep targets (minerals beneath regolith)improved signal processing methods are required. The project involves the development of time-ser ....Optimisation of Signal-to-Noise Ratio in Electrical and Electromagnetic Investigations. Electrical and electromagnetic geophysical methods have been used extensively for mineral exploration, and are developing a role in salinity mapping and contaminant identification. To enhance the utility of such methods for very shallow targets (in the case of salinity) and deep targets (minerals beneath regolith)improved signal processing methods are required. The project involves the development of time-series processing techniques using robust-statistical methods and remote-referencing to improve signal-to-noise data quality. Instrumentation hardware and software developments are required for in-field data acquisition and interpretation, applied to direct current (DC) resistivity, induced polarisation (IP) and time-domain EM (TEM).Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the inter ....Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the international profile of Australian research in the area of information technology. Applied development of the outcomes will lead to the generation of valuable intellectual property. Close links to Australian industry ensures that Australian ICT companies stand to gain commercial advantage.Read moreRead less
Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to c ....Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to constraints on computational complexity. Theoretical analysis and design methodologies for such systems will be developed, resulting in basic contributions to statistical science and in cheaper communications infrastructures supporting a wider range of services through better use of limited bandwidth, power and computational complexity.Read moreRead less
Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Pr ....Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Project will develop novel designs for microarray experiments and focus on the advancement of topics crucial to Australia's success in technological research.
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