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Australian Laureate Fellowships - Grant ID: FL170100006
Funder
Australian Research Council
Funding Amount
$3,016,065.00
Summary
Pattern analysis for accelerating scientific innovation. This project aims to determine how pattern recognition can be harnessed to accelerate and expand the capability of experimental optimisation that underpins scientific innovation. Disrupting current experimental methods, this new framework will use data-driven models to guide humans through experimental complexity. The expected outcomes of the project include advancing the theory and practice of pattern recognition in Bayesian optimisation ....Pattern analysis for accelerating scientific innovation. This project aims to determine how pattern recognition can be harnessed to accelerate and expand the capability of experimental optimisation that underpins scientific innovation. Disrupting current experimental methods, this new framework will use data-driven models to guide humans through experimental complexity. The expected outcomes of the project include advancing the theory and practice of pattern recognition in Bayesian optimisation by solving both fundamental and translatory problems, totally transforming the way complex experimental explorations can be done. The project will establish Australia as a leader in innovation-led productivity in the 4th industrial revolution, which will include ground-breaking investigations into the use of pattern recognition to navigate complexity in the experimental process.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL170100117
Funder
Australian Research Council
Funding Amount
$3,208,192.00
Summary
On snapping up semantics of dynamic pixels from moving cameras. The project aims to develop a suite of original models and algorithms for processing and understanding videos captured by moving cameras, and to establish the mathematical foundations for deep learning-based computer vision to provide theoretical underpinnings. The project expects to generate new knowledge that will transform moving-camera computer vision with step-changes in visual quality enhancement, compression and acceleration ....On snapping up semantics of dynamic pixels from moving cameras. The project aims to develop a suite of original models and algorithms for processing and understanding videos captured by moving cameras, and to establish the mathematical foundations for deep learning-based computer vision to provide theoretical underpinnings. The project expects to generate new knowledge that will transform moving-camera computer vision with step-changes in visual quality enhancement, compression and acceleration technologies, and solutions for fundamental computer vision tasks. A new concept of feature complexity for measuring the discriminant and learnable abilities of features from deep models will also be defined. The outcomes of the project will be critical for enabling autonomous machines to perceive and interact with the environment.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL140100012
Funder
Australian Research Council
Funding Amount
$2,830,000.00
Summary
Stress-testing algorithms: generating new test instances to elicit insights. Stress-testing algorithms: generating new test instances to elicit insights. This project aims to develop a new paradigm in algorithm testing, creating novel test instances and tools to elicit insights into algorithm strengths and weaknesses. Such advances are urgently needed to support good research practice in academia, and to avoid disasters when deploying algorithms in practice. Extending our recent work in algorith ....Stress-testing algorithms: generating new test instances to elicit insights. Stress-testing algorithms: generating new test instances to elicit insights. This project aims to develop a new paradigm in algorithm testing, creating novel test instances and tools to elicit insights into algorithm strengths and weaknesses. Such advances are urgently needed to support good research practice in academia, and to avoid disasters when deploying algorithms in practice. Extending our recent work in algorithm testing for combinatorial optimisation, described as 'ground-breaking,' this project aims to tackle the challenges needed to generalise the paradigm to other fields such as machine learning, forecasting, software testing, and other branches of optimisation. An online repository of test instances and tools aim to provide a valuable resource to improve research practice and support new insights into algorithm performance.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
Australian Laureate Fellowships - Grant ID: FL200100096
Funder
Australian Research Council
Funding Amount
$3,367,940.00
Summary
Mapping the genetic and lifestyle landscape of Healthy Ageing. This project aims to dissect how genes interact with the environment to control healthy ageing using a multidisciplinary approach combining state-of-the-art omics technologies, metabolic and ageing phenotyping and genetic analysis and a highly diverse model system. The project is expected to establish fundamental new understanding of the ageing process by identifying genes that regulate ageing either alone or in response to diet; by ....Mapping the genetic and lifestyle landscape of Healthy Ageing. This project aims to dissect how genes interact with the environment to control healthy ageing using a multidisciplinary approach combining state-of-the-art omics technologies, metabolic and ageing phenotyping and genetic analysis and a highly diverse model system. The project is expected to establish fundamental new understanding of the ageing process by identifying genes that regulate ageing either alone or in response to diet; by defining the mechanism by which such genes control ageing and by identifying biomarkers that predict different ageing outcomes. This knowledge will contribute to future strategies based on genetic testing and biomarkers to optimise healthy ageing in humans. Read moreRead less
Australian Laureate Fellowships - Grant ID: FL150100106
Funder
Australian Research Council
Funding Amount
$2,951,945.00
Summary
Bio-metrology and modelling of a complex system: the malaria parasite. Bio-metrology and modelling of a complex system: the malaria parasite: This fellowship project aims to develop a cross-disciplinary program to measure, model and manipulate a complex cellular system — sexual differentiation of the human malaria parasite. Combining life and physical sciences with powerful imaging techniques, the project seeks to develop quantitative biochemical, biophysical and modelling techniques to probe a ....Bio-metrology and modelling of a complex system: the malaria parasite. Bio-metrology and modelling of a complex system: the malaria parasite: This fellowship project aims to develop a cross-disciplinary program to measure, model and manipulate a complex cellular system — sexual differentiation of the human malaria parasite. Combining life and physical sciences with powerful imaging techniques, the project seeks to develop quantitative biochemical, biophysical and modelling techniques to probe a complex system in a way previously not possible. It expects to integrate and correlate thousands of measurements of the dynamic processes inside cells and use these datasets to generate rigorous and sophisticated mathematical models that can predict drivers of commitment for transformation of the parasite to a sexual phase in preparation for transmission to mosquitoes. This holistic approach hopes to deliver new biotechnology and biomedical outcomes, including new ways to combat disease in livestock and humans.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100149
Funder
Australian Research Council
Funding Amount
$3,280,000.00
Summary
Autonomous learning for decision making in complex situations. The project aims to create a novel research direction – autonomous machine learning for data-driven decision-making – that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively h ....Autonomous learning for decision making in complex situations. The project aims to create a novel research direction – autonomous machine learning for data-driven decision-making – that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively handle tremendous uncertainties in data, learning processes and decision outputs, particularly enabling smart learning in massive domains, massive streams, and massive-agent sequentially changing environments. The project’s outcomes are expected to improve data-driven decision-making in multiple industry sectors.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL110100281
Funder
Australian Research Council
Funding Amount
$2,777,066.00
Summary
Large-scale statistical machine learning. This research program aims to develop the science behind statistical decision problems as varied as web retrieval, genomic data analysis and financial portfolio optimisation. Advances will have a very significant practical impact in the many areas of science and technology that need to make sense of large, complex data streams.
Australian Laureate Fellowships - Grant ID: FL230100100
Funder
Australian Research Council
Funding Amount
$3,300,000.00
Summary
Forces in Nature: Tissue mechanics and cell sociology. Epithelial cells cover surfaces in the body, forming a shield to protect us from the environment. Despite their importance, we understand poorly how the cells communicate. This project aims to test the novel concept that epithelial cells communicate via transmission and detection of mechanical forces, using an innovative combination of cellular and biophysical experiments and physical theory. The expected outcomes are new knowledge, interdis ....Forces in Nature: Tissue mechanics and cell sociology. Epithelial cells cover surfaces in the body, forming a shield to protect us from the environment. Despite their importance, we understand poorly how the cells communicate. This project aims to test the novel concept that epithelial cells communicate via transmission and detection of mechanical forces, using an innovative combination of cellular and biophysical experiments and physical theory. The expected outcomes are new knowledge, interdisciplinary training for young scientists, new national research capacity and growing international collaborations. Benefits include enhancing Australia’s scientific linkages and research capacity and providing fundamental knowledge that could lead to future advances in bioengineering and drug discovery. Read moreRead less
Australian Laureate Fellowships - Grant ID: FL140100179
Funder
Australian Research Council
Funding Amount
$2,800,000.00
Summary
Controlling gene expression with synthetic RNA-binding proteins. Controlling gene expression with synthetic RNA-binding proteins. The growth and development of living organisms is largely determined by the genes they contain, but converting the genetic information into biological activity requires intermediary processes involving RNA and proteins that bind to and process RNA. This project aims to understand how the largest class of RNA-binding protein in plants recognise their target RNAs and ai ....Controlling gene expression with synthetic RNA-binding proteins. Controlling gene expression with synthetic RNA-binding proteins. The growth and development of living organisms is largely determined by the genes they contain, but converting the genetic information into biological activity requires intermediary processes involving RNA and proteins that bind to and process RNA. This project aims to understand how the largest class of RNA-binding protein in plants recognise their target RNAs and aims to develop custom-designed proteins for switching genes on or off. This technology will be used to create new hybrid cereal varieties and will also be valuable for applications in human health, such as the correction of genetic mutations.Read moreRead less