Improving predictions of species distribution dynamics. This project aims to mainstream methods for improved prediction of species distributions under the impacts of environmental change. This is important because these predictions are commonly used to guide environmental decisions, but the standard modelling methods used to produce them have critical limitations. This project intends to (i) make key statistical developments to methods for modelling dynamics of species distributions and (ii) tra ....Improving predictions of species distribution dynamics. This project aims to mainstream methods for improved prediction of species distributions under the impacts of environmental change. This is important because these predictions are commonly used to guide environmental decisions, but the standard modelling methods used to produce them have critical limitations. This project intends to (i) make key statistical developments to methods for modelling dynamics of species distributions and (ii) translate the methods into practice, through guidelines, tools and training, engagement with users and case studies addressing species of current concern. This should provide significant benefits because it will enable better decisions and more effective and cost-efficient management actions.Read moreRead less
Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification ....Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of the inevitable trade-offs between fairness and utility. The benefits of the project should include better ways of managing these trade-offs, a competitive advantage for Australian firms developing the technology, and will ensure that the country retains a social license to use the technology.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL200100176
Funder
Australian Research Council
Funding Amount
$3,128,080.00
Summary
Theoretical Foundations of Ethical Machine Learning. The project will develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project will develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of t ....Theoretical Foundations of Ethical Machine Learning. The project will develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project will develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of the inevitable trade-offs between fairness and utility. The benefits of the project will include the best possible ways of managing these trade-offs, competitive advantage for Australian firms developing the technology, and will ensure that the country retains a social license to use the technology.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101535
Funder
Australian Research Council
Funding Amount
$363,000.00
Summary
Ancient genomics of Western Australian taxa to inform conservation management. The project aims to apply genomic approaches to infer the genetic health and evolutionary history of three threatened, iconic Western Australian taxa: black cockatoos, ghost bats and woylies. Genomic data provide a powerful lens through which to study species, but the applications of genomic techniques in conservation biology have been sparse. Effective restoration and conservation initiatives require an understanding ....Ancient genomics of Western Australian taxa to inform conservation management. The project aims to apply genomic approaches to infer the genetic health and evolutionary history of three threatened, iconic Western Australian taxa: black cockatoos, ghost bats and woylies. Genomic data provide a powerful lens through which to study species, but the applications of genomic techniques in conservation biology have been sparse. Effective restoration and conservation initiatives require an understanding of species' former population sizes, connectivity and biodiversity. The project seeks to elucidate the population genetic, phylogenetic, and conservation genetic parameters of the three species at the genomic level using DNA isolated from modern and ancient sources (eg museum skins and fossils). The information gained may inform conservation efforts for some of Australia’s endangered biota.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100578
Funder
Australian Research Council
Funding Amount
$355,208.00
Summary
Next generation soil carbon satellite-based measurement for carbon markets. Soil carbon sequestration is a federal government priority to offset greenhouse gas emissions. Efforts to advance this opportunity are hindered by the high technical costs of soil carbon quantification. This project will develop an innovative and potentially commercialisable technology that integrates ground data, unmanned aerial vehicles (UAVs), satellites, Eddy covariance CO2 flux towers, soil carbon (C) models, and ar ....Next generation soil carbon satellite-based measurement for carbon markets. Soil carbon sequestration is a federal government priority to offset greenhouse gas emissions. Efforts to advance this opportunity are hindered by the high technical costs of soil carbon quantification. This project will develop an innovative and potentially commercialisable technology that integrates ground data, unmanned aerial vehicles (UAVs), satellites, Eddy covariance CO2 flux towers, soil carbon (C) models, and artificial intelligence (AI) to improve the accuracy of satellite-based soil C modelling. The project will provide an accurate and cost-effective solution to quantification of soil C changes to unlock a large potential of carbon offsets in rangelands in Australia and worldwide.Read moreRead less