Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC220100035
Funder
Australian Research Council
Funding Amount
$4,958,927.00
Summary
ARC Training Centre for Hyphenated Analytical Separation Technologies . The toughest analytical science challenges typically require advanced analytical technologies to acquire the desired solutions. In the field of separation science this inevitably involves hyphenated separation technologies, specifically the combination of chromatography and mass spectrometry. Advancing this technology to its full capability requires the collaborative strength of academic, industry and end-user partnerships, ....ARC Training Centre for Hyphenated Analytical Separation Technologies . The toughest analytical science challenges typically require advanced analytical technologies to acquire the desired solutions. In the field of separation science this inevitably involves hyphenated separation technologies, specifically the combination of chromatography and mass spectrometry. Advancing this technology to its full capability requires the collaborative strength of academic, industry and end-user partnerships, providing the materials and inspiration for young researchers to apply novel hyphenated methods to complex environmental and industrial systems. This Centre will deliver fundamental developments in hyphenated technologies, new analytical capability, and applied outcomes across multiple end-user groups and interests. Read moreRead less
Targeting conjugated markers with new metabolomic methods. Detecting the illicit use of natural steroids like testosterone, or compounds that modulate natural steroid levels, remains the greatest challenge for drug testing in all forms of sport. This project aims to develop new metabolomic methods based on liquid chromatography-high resolution mass spectrometry to detect the changes occurring in the conjugated steroid profile following the administration of steroids or steroid modulators. The in ....Targeting conjugated markers with new metabolomic methods. Detecting the illicit use of natural steroids like testosterone, or compounds that modulate natural steroid levels, remains the greatest challenge for drug testing in all forms of sport. This project aims to develop new metabolomic methods based on liquid chromatography-high resolution mass spectrometry to detect the changes occurring in the conjugated steroid profile following the administration of steroids or steroid modulators. The intended outcome will be a set of sensitive and analytical methods using a range of newly identified conjugated steroid markers and associated reference materials, which promises to enhance integrity and animal welfare in the thoroughbred racing industry.
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Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less
New methods in spectral geometry. This project aims to use methods from mathematical scattering theory to resolve problems in the spectral analysis and index theory of differential operators. Both areas underpin the theoretical understanding of physical materials at micro length scales where quantum phenomena dominate. The project will develop new mathematical results in spectral analysis and geometry, and apply its results to theoretical models of quantum phenomena whose spectral properties are ....New methods in spectral geometry. This project aims to use methods from mathematical scattering theory to resolve problems in the spectral analysis and index theory of differential operators. Both areas underpin the theoretical understanding of physical materials at micro length scales where quantum phenomena dominate. The project will develop new mathematical results in spectral analysis and geometry, and apply its results to theoretical models of quantum phenomena whose spectral properties are at the limit of the range of mathematical techniques. Solving these problems is expected to influence non-commutative analysis.Read moreRead less
Terahertz lasers in the fight against illicit substances. This project aims to investigate the application of cutting-edge terahertz laser technology with new spectroscopic methods, for detection of illicit substances. Using a collaborative approach, the project aims to bring together expertise in laser physics, spectroscopy, law enforcement and instrumentation, and seeks to develop new sources and detection protocols which will offer new capabilities to law enforcement, aiding in detection and ....Terahertz lasers in the fight against illicit substances. This project aims to investigate the application of cutting-edge terahertz laser technology with new spectroscopic methods, for detection of illicit substances. Using a collaborative approach, the project aims to bring together expertise in laser physics, spectroscopy, law enforcement and instrumentation, and seeks to develop new sources and detection protocols which will offer new capabilities to law enforcement, aiding in detection and identification protocols for illicit substances.Read moreRead less
Reliable and accurate statistical solutions for modern complex data. This project aims to develop novel methods for reliable and accurate statistical modelling with modern, complex correlated and error-prone data. The project expects to make significant strides towards future-proofing statistical data analysis, equipping practitioners with a suite of robust and computationally efficient methods which provide confidence in the stability and reproducibility of results obtained, while offering guar ....Reliable and accurate statistical solutions for modern complex data. This project aims to develop novel methods for reliable and accurate statistical modelling with modern, complex correlated and error-prone data. The project expects to make significant strides towards future-proofing statistical data analysis, equipping practitioners with a suite of robust and computationally efficient methods which provide confidence in the stability and reproducibility of results obtained, while offering guarantees on their transferability over a range of populations. This will provide important benefits as they are applied in predicting endangered marine species for fisheries conservation, and in enhancing our national understanding of the relationship between education achievement and financial success. Read moreRead less
Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alter ....Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alteration occurring during gravity driven convection. Expected outcomes are the in-situ characterisation of solid-surface interactions and predictions of multi-phase fluid flow. The project benefits the Australian resources sector by improving injectivity, storage efficiency and security of supercritical CO2 storage projects.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC220100030
Funder
Australian Research Council
Funding Amount
$4,978,958.00
Summary
ARC Training Centre for Next-Gen Architectural Manufacturing. The Centre will generate specialised workforce capacity within Australia’s architectural sector. Leveraging advanced architectural computing discoveries will connect architectural design with the opportunities afforded by advanced manufacturing systems. The Centre will triangulate world-leading researchers, visionary partners, and talented graduates, integrating research into practice through digital business strategies, augmented int ....ARC Training Centre for Next-Gen Architectural Manufacturing. The Centre will generate specialised workforce capacity within Australia’s architectural sector. Leveraging advanced architectural computing discoveries will connect architectural design with the opportunities afforded by advanced manufacturing systems. The Centre will triangulate world-leading researchers, visionary partners, and talented graduates, integrating research into practice through digital business strategies, augmented intelligence, and computing domains of expertise. The Centre’s program of industry-embedded PhD’s, national/international placements, short courses, and post-doctoral projects will co-develop the change agents needed to transform the architectural profession to meet our nation’s immediate strategic needs.Read moreRead less
Thermodynamics inversion for mineral systems. This project aims to provide a newly developed science approach to the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP). AusLAMP provides unparalleled geophysical information aimed at unravelling the tectonic history of the Australian continent and its mineral potential. The project will use thermodynamically based geodynamic simulators to jointly analyse and quantify intraplate deformation. This will illuminate the cause of dri ....Thermodynamics inversion for mineral systems. This project aims to provide a newly developed science approach to the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP). AusLAMP provides unparalleled geophysical information aimed at unravelling the tectonic history of the Australian continent and its mineral potential. The project will use thermodynamically based geodynamic simulators to jointly analyse and quantify intraplate deformation. This will illuminate the cause of driving fluid flow thorough the lithosphere, mineralisation phenomena, their datasets and geometries, and dynamic aspects of the processes driving mineral systems.Read moreRead less