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Research Topic : Applied statistics
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  • Funded Activity

    ARC Future Fellowships - Grant ID: FT200100188

    Funder
    Australian Research Council
    Funding Amount
    $950,000.00
    Summary
    A fast comparative method for historical linguistics. Linguists are able to infer ancient histories of languages by a procedure known as the Comparative Method. Its results are used in related studies of human genetic and cultural change. However, the Comparative Method is a manual-only process and thus currently is a bottleneck for the science of unravelling the human past. This project aims to overcome this limitation and significantly accelerate linguistic discovery, by combining recent advan .... A fast comparative method for historical linguistics. Linguists are able to infer ancient histories of languages by a procedure known as the Comparative Method. Its results are used in related studies of human genetic and cultural change. However, the Comparative Method is a manual-only process and thus currently is a bottleneck for the science of unravelling the human past. This project aims to overcome this limitation and significantly accelerate linguistic discovery, by combining recent advances in computational language processing, statistics and cultural-evolutionary modelling. By producing innovative mathematical means for rapidly discovering ancient language relationships, it will enable a breakthrough in our capacity to uncover human linguistic, genetic and cultural heritage worldwide.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE160100999

    Funder
    Australian Research Council
    Funding Amount
    $295,020.00
    Summary
    Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-maki .... Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-making processes require intensive consideration of all possible outcomes in the modelled environment. In comparison to previous optimisation methods, the FBSDE approach is easier to work with and much more informative. The project's main potential applications are multiplayer games with mean-field interaction and financial markets with partial information.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT170100470

    Funder
    Australian Research Council
    Funding Amount
    $800,000.00
    Summary
    Understanding the robustness and plasticity of metabolite concentrations. This project aims to further the understanding of how organisms mitigate the effects of changing environment by altering metabolite concentrations, important for food quality, energetics, and health. Through this understanding, the project provides the potential to precisely tailor metabolic intervention strategies, highly beneficial for applied sciences. The expected outcome of the project is a suite of computational appr .... Understanding the robustness and plasticity of metabolite concentrations. This project aims to further the understanding of how organisms mitigate the effects of changing environment by altering metabolite concentrations, important for food quality, energetics, and health. Through this understanding, the project provides the potential to precisely tailor metabolic intervention strategies, highly beneficial for applied sciences. The expected outcome of the project is a suite of computational approaches that allow for integration of large-scale data with networks to predict metabolite concentration ranges. This will provide significant benefit with the aim of maintaining outstanding research in Australia, and has clear potential for improved human health and enhanced food quality via metabolic reprogramming.
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