Bayesian inversion and computation applied to atmospheric flux fields. This project aims to make use of unprecedented sources of measurements, from remote sensing and in situ data, to estimate the sources and sinks of greenhouse gases. An overabundance of greenhouse gases in Earth's atmosphere is arguably the most serious long-term threat to the planet's ecosystems. This project will combine measurement uncertainties, process uncertainties in the physical transport models, and any parameter unce ....Bayesian inversion and computation applied to atmospheric flux fields. This project aims to make use of unprecedented sources of measurements, from remote sensing and in situ data, to estimate the sources and sinks of greenhouse gases. An overabundance of greenhouse gases in Earth's atmosphere is arguably the most serious long-term threat to the planet's ecosystems. This project will combine measurement uncertainties, process uncertainties in the physical transport models, and any parameter uncertainties, to provide reliable uncertainty quantification for the estimates. This will be achieved with new Bayesian spatio-temporal inversions and big-data computational strategies. The resulting statistical inferences on greenhouse-gas flux fields will enable the development of critical mitigation strategies. These new statistical inferences will be a valuable resource to policy-makers worldwide, who are assessing progress towards global commitments. Further, the final product may assist in developing cost-effective mitigation strategies in the presence of uncertainty.Read moreRead less
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
Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.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
Modern statistical methods for clustering community ecology data. This project will develop statistical methods and software for clustering community ecology data, and use them to analyse systematic survey and citizen science program data collected along the Great Barrier Reef. By doing so, the project will address the dearth of statistical classification techniques for high-dimensional, multi-response data with complex relationships. When the resultant clustering methods are used to construct b ....Modern statistical methods for clustering community ecology data. This project will develop statistical methods and software for clustering community ecology data, and use them to analyse systematic survey and citizen science program data collected along the Great Barrier Reef. By doing so, the project will address the dearth of statistical classification techniques for high-dimensional, multi-response data with complex relationships. When the resultant clustering methods are used to construct bioregions and characterise species’ environmental responses, they should significantly enhance evaluations of the impact of human activity and environmental change on coral diversity. Ultimately, these evaluations can underpin future decisions in the conservation and management of the Great Barrier Reef.Read moreRead less
Leaves in 3D: photosynthesis and water-use efficiency. This project aims to develop leaf anatomical ideotypes with improved photosynthesis and water-use efficiency for wheat, rice, chickpea and cotton using novel three dimensional imaging and modelling techniques. This project expects to generate new understanding of the role of leaf anatomy on leaf function. Expected outcomes of this project include the world's first 3D spatially-explicit, anatomically accurate model of leaves of crop plants to ....Leaves in 3D: photosynthesis and water-use efficiency. This project aims to develop leaf anatomical ideotypes with improved photosynthesis and water-use efficiency for wheat, rice, chickpea and cotton using novel three dimensional imaging and modelling techniques. This project expects to generate new understanding of the role of leaf anatomy on leaf function. Expected outcomes of this project include the world's first 3D spatially-explicit, anatomically accurate model of leaves of crop plants to allow virtual experiments identifying optimized anatomy for improved photosynthetic performance. Benefits to the agricultural industry include increased crop productivity and water-use efficiency to meet future global food demand and to make the most of Australia's limited water resourcesRead moreRead less
Intelligence and national security: ethics, efficacy and accountability. This project aims to generate an ethically informed set of practice and policy guidelines for viable security intelligence collection and analysis of electronic data by liberal democracies. In the context of global terrorism and the resurgence of technologically sophisticated authoritarian states, effective intelligence collection and analysis of electronic data is crucial for the national security of liberal democratic sta ....Intelligence and national security: ethics, efficacy and accountability. This project aims to generate an ethically informed set of practice and policy guidelines for viable security intelligence collection and analysis of electronic data by liberal democracies. In the context of global terrorism and the resurgence of technologically sophisticated authoritarian states, effective intelligence collection and analysis of electronic data is crucial for the national security of liberal democratic states. Yet intelligence agencies in Australia, United States, European Union and so on, are not only under pressure to perform, but must also meet a variety of ethical challenges, notably privacy constraints and democratic accountability. This project will contribute to Australia's national security policy making environment, and to privacy and broader human rights debates, by providing an evidenced based, ethically informed set of practice and policy guidelines for viable national security intelligence practice in liberal democracies.Read moreRead less
Policy Modelling for Ageing in Emerging Economies: The Case of Indonesia. This project, in collaboration with the World Bank and the Indonesian Planning Authority, will support major social and economic policy development in a rapidly ageing region. It will break new ground by developing a cutting-edge economic policy model reflecting salient features of ageing in emerging economies, taking into account the wider implications for education, employment, formalisation, growth, and retirement. It w ....Policy Modelling for Ageing in Emerging Economies: The Case of Indonesia. This project, in collaboration with the World Bank and the Indonesian Planning Authority, will support major social and economic policy development in a rapidly ageing region. It will break new ground by developing a cutting-edge economic policy model reflecting salient features of ageing in emerging economies, taking into account the wider implications for education, employment, formalisation, growth, and retirement. It will bring the armoury of policy analysis instruments available to these countries up to the standard now enjoyed by the developed world. Indonesia, on the brink of major pension reform, will be used as a test bed. Data sets will be developed to allow the model structure to be applied to other emerging economies in Asia. Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC210100008
Funder
Australian Research Council
Funding Amount
$4,282,859.00
Summary
ARC Training Centre for Behavioural Insights for Technology Adoption (BITA). Australia needs accelerated adoption of innovation technologies to improve outcomes in health, agriculture and cybersecurity. Despite technically viable solutions, innovations fail to be adopted due to behavioural barriers. Behavioural approaches can promote significant gains by bridging the barriers to technology adoption. The Centre for Behavioural Insights for Technology Adoption will boost national productivity by i ....ARC Training Centre for Behavioural Insights for Technology Adoption (BITA). Australia needs accelerated adoption of innovation technologies to improve outcomes in health, agriculture and cybersecurity. Despite technically viable solutions, innovations fail to be adopted due to behavioural barriers. Behavioural approaches can promote significant gains by bridging the barriers to technology adoption. The Centre for Behavioural Insights for Technology Adoption will boost national productivity by identifying, designing and evaluating solutions that address these barriers. By uniting industry and government with world-leading interdisciplinary researchers, the Centre will build transformative capability in people, data and solutions and support Australian organisations to achieve higher returns on technology investment.Read moreRead less
Understanding and overcoming confusion in consumer financial decisions. This project aims to develop consumer-centred approaches to reducing the harmful effects of confusion in financial decisions by studying superannuation investment and home loan decisions where confused choices are individually and collectively costly. The project intends to develop comprehensive models to capture the full complexity of financial products and the diverse preferences and capability of consumers, then to use ad ....Understanding and overcoming confusion in consumer financial decisions. This project aims to develop consumer-centred approaches to reducing the harmful effects of confusion in financial decisions by studying superannuation investment and home loan decisions where confused choices are individually and collectively costly. The project intends to develop comprehensive models to capture the full complexity of financial products and the diverse preferences and capability of consumers, then to use advanced statistical methods to estimate the benefits of clearer decision-making. The outcomes of this project includes new models of complex financial decisions, and a better understanding of where confusion arises and the effects it may have. Decreased confusion will raise financial well-being and help communities become more resilient to financial shocks.Read moreRead less