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Field of Research : Probability Theory
Australian State/Territory : VIC
Field of Research : Statistics
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  • Funded Activity

    Discovery Projects - Grant ID: DP0209179

    Funder
    Australian Research Council
    Funding Amount
    $50,000.00
    Summary
    Stein's method for probability approximation. Data of counts in time, such as incoming calls in telecommunications and the clusters of palindromes in a family of herpes-virus genomes, arise in an extraordinarily diverse range of fields from science to business. These problems can be modelled by sums of random variables taking values 0 and 1 in probability theory, thus permitting approximate calculations which are often good enough in practice. This project will obtain such approximate solutions .... Stein's method for probability approximation. Data of counts in time, such as incoming calls in telecommunications and the clusters of palindromes in a family of herpes-virus genomes, arise in an extraordinarily diverse range of fields from science to business. These problems can be modelled by sums of random variables taking values 0 and 1 in probability theory, thus permitting approximate calculations which are often good enough in practice. This project will obtain such approximate solutions and estimate the errors involved. Applications include analysis of data in insurance, finance, flood prediction in hydrology.
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    Funded Activity

    Discovery Projects - Grant ID: DP120102398

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Random network models with applications in biology. Complex biological systems consist of a large number of interacting agents or components, and so can be studied using mathematical random network models. We aim to gain deeper insights into the laws emerging as the random networks evolve in time. This can help us to deal with dangerous disease epidemics and better understand the human brain.
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    Funded Activity

    Discovery Projects - Grant ID: DP150101459

    Funder
    Australian Research Council
    Funding Amount
    $591,800.00
    Summary
    Random Discrete Structures: Approximations and Applications. The behaviour of many real world systems can be modelled by random discrete structures evolving over time. For example, the sizes of populations of frogs in some close patches of forests can be modelled as interacting random processes. The aim of the project is to investigate large discrete random structures that arise from real world application in areas such as biology, complex networks and insurance. The proposed project is at the i .... Random Discrete Structures: Approximations and Applications. The behaviour of many real world systems can be modelled by random discrete structures evolving over time. For example, the sizes of populations of frogs in some close patches of forests can be modelled as interacting random processes. The aim of the project is to investigate large discrete random structures that arise from real world application in areas such as biology, complex networks and insurance. The proposed project is at the interface of mathematics and 'big data' applications and so the work of the project aims to provide theoretical and heuristic underpinnings useful in the algorithms and techniques of practitioners. Understanding the applications in the project requires new, broadly applicable methods and developing such is a complementary aim.
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    Funded Activity

    Discovery Projects - Grant ID: DP180100613

    Funder
    Australian Research Council
    Funding Amount
    $327,316.00
    Summary
    Random walks with long memory. This project aims to study novel random walk models with long memory, including systems of multiple random walkers that interact through their environment. This would provide a mathematical understanding of phenomena such as aggregation in colonies of bacteria, and ant colony optimisation algorithms. The project aims to produce highly cited publications, and to train future researchers.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100559

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Finite Markov chains in statistical mechanics and combinatorics. Finite Markov chains can be viewed as random walks in a finite set. In applications, this set often consists of certain combinatorial objects whose typical properties are to be understood. If the set is large, obtaining exact solutions to such problems is generally infeasible. Markov chains can provide a highly efficient method to generate randomised approximations in such cases, but only if they equilibrate at a rate that grows sl .... Finite Markov chains in statistical mechanics and combinatorics. Finite Markov chains can be viewed as random walks in a finite set. In applications, this set often consists of certain combinatorial objects whose typical properties are to be understood. If the set is large, obtaining exact solutions to such problems is generally infeasible. Markov chains can provide a highly efficient method to generate randomised approximations in such cases, but only if they equilibrate at a rate that grows slowly with the size of the set of objects under study. The project will study several classes of Markov chains that have been developed to study a number of notoriously difficult problems in statistical mechanics and combinatorics, and determine under what conditions they provide efficient approximation schemes.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT160100166

    Funder
    Australian Research Council
    Funding Amount
    $776,000.00
    Summary
    Phase transitions in stochastic systems. This project aims to understand models of physical and biological phenomena in the presence of uncertainty/randomness. Such models often exhibit phase transitions if a variable defining the model is modified. For example, a population explosion can occur if the average number of offspring per individual is larger than one, while macroscopic defects can occur in a material if the density of microscopic defects is larger than some threshold. This research c .... Phase transitions in stochastic systems. This project aims to understand models of physical and biological phenomena in the presence of uncertainty/randomness. Such models often exhibit phase transitions if a variable defining the model is modified. For example, a population explosion can occur if the average number of offspring per individual is larger than one, while macroscopic defects can occur in a material if the density of microscopic defects is larger than some threshold. This research could lead to strategies for directing physical and biological systems towards preferred states or phases, and better prediction of adverse events such as fracturing of Antarctic sea ice.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE140101201

    Funder
    Australian Research Council
    Funding Amount
    $366,404.00
    Summary
    Planar Brownian motion and complex analysis. This project will study a number of related problems concerning both Brownian motion and complex analysis. These include questions about Brownian exit time, conformally invariant processes such as Stochastic Loewner Evolution, and the fundamentals of complex analysis. Many of these questions are at the forefront of modern probability theory. The outcomes of this project will bring the questions considered into a position of prominence in the fields of .... Planar Brownian motion and complex analysis. This project will study a number of related problems concerning both Brownian motion and complex analysis. These include questions about Brownian exit time, conformally invariant processes such as Stochastic Loewner Evolution, and the fundamentals of complex analysis. Many of these questions are at the forefront of modern probability theory. The outcomes of this project will bring the questions considered into a position of prominence in the fields of probability and analysis, and bring international attention to Australia as a hub of important research.
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