Novel methodology advancing applied Bayesian statistics and applications. Bayesian statistical inference has become the dominant statistical method in significant areas of application. The project aims to develop and apply novel Bayesian computational algorithms. Outcomes will advance scientific understanding in significant multi-disciplinary areas such as infectious diseases, neurological disease and human behaviour.
Geodetic groups: foundational problems in algebra and computer science. The project aims to resolve important and longstanding open problems in Geometric Group Theory and Theoretical Computer Science. Since the 1980s researchers have conjectured that the geometric property of being geodetic is equivalent to several purely algebraic, algorithmic, and language-theoretic characterisations.
The project team's expertise in geodesic properties of groups, the interaction between formal languages and g ....Geodetic groups: foundational problems in algebra and computer science. The project aims to resolve important and longstanding open problems in Geometric Group Theory and Theoretical Computer Science. Since the 1980s researchers have conjectured that the geometric property of being geodetic is equivalent to several purely algebraic, algorithmic, and language-theoretic characterisations.
The project team's expertise in geodesic properties of groups, the interaction between formal languages and groups, and the theory of rewriting systems, together with recent breakthroughs by the team ensures that significant results can be expected.
Benefits include training research students and postdoctoral researchers in cutting-edge techniques, and advancing fundamental knowledge in mathematics and computer science.Read moreRead less
ARC Centre of Excellence for Plant Success in Nature and Agriculture. The ARC CoE for Plant Success in Nature and Agriculture will discover the adaptive strategies underpinning productivity and resilience in diverse plants and deepen knowledge of the genetic and physiological networks driving key traits. Using novel quantitative and computational approaches, the Centre will link gene networks with traits across biological levels, giving breeders an unparalleled predictive capacity. The Centre wi ....ARC Centre of Excellence for Plant Success in Nature and Agriculture. The ARC CoE for Plant Success in Nature and Agriculture will discover the adaptive strategies underpinning productivity and resilience in diverse plants and deepen knowledge of the genetic and physiological networks driving key traits. Using novel quantitative and computational approaches, the Centre will link gene networks with traits across biological levels, giving breeders an unparalleled predictive capacity. The Centre will accelerate technologies to transfer successful networks into crops and build legal frameworks to secure this knowledge. With a uniquely multidisciplinary team, the Centre will deliver new strategies to address the problems of food security and climate change, establishing Australia as a global leader in these areas.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101268
Funder
Australian Research Council
Funding Amount
$386,820.00
Summary
Stochastic mathematical modelling of the Wnt signalling pathway. The Wnt signalling pathway is pivotal in multicellular organisms, regulating cellular processes such as proliferation, apoptosis and migration. Faulty Wnt signalling is associated with degenerative diseases, developmental disorders and cancers and is therefore a potential target for therapeutic drugs. This project will perform a stochastic spatial simulation of the Wnt signalling pathway which will be matched to experimental data. ....Stochastic mathematical modelling of the Wnt signalling pathway. The Wnt signalling pathway is pivotal in multicellular organisms, regulating cellular processes such as proliferation, apoptosis and migration. Faulty Wnt signalling is associated with degenerative diseases, developmental disorders and cancers and is therefore a potential target for therapeutic drugs. This project will perform a stochastic spatial simulation of the Wnt signalling pathway which will be matched to experimental data. The model will be extended to integrate with the cell cycle. Increased proliferation in tumours has been linked to mutations in Wnt components. Using the extended model, the effect of Wnt-targeting therapeutic cancer drugs on cancer cell proliferation rates will be predicted and compared to experiments.Read moreRead less
Mathematical models of cell migration in three-dimensional living tissues. This project aims to develop mathematical models of cell migration in crowded, living tissues. Existing models rely solely on stochastic simulations, and therefore provide no general mathematical insight into how properties of the crowding environment (obstacle shape, size, density) affect the migration of cells through that environment. This project will produce mathematical analysis, mathematical calculations and exact ....Mathematical models of cell migration in three-dimensional living tissues. This project aims to develop mathematical models of cell migration in crowded, living tissues. Existing models rely solely on stochastic simulations, and therefore provide no general mathematical insight into how properties of the crowding environment (obstacle shape, size, density) affect the migration of cells through that environment. This project will produce mathematical analysis, mathematical calculations and exact analytical tools that quantify how the crowding environment in three-dimensional living tissues affects the migration of cells within these tissues. Long term effects will be the translation of this new mathematical knowledge into decision support tools for researchers from the life sciences.Read moreRead less
Mathematical models of 4D multicellular spheroids. Mathematical models have a long, successful history of providing biological insight, and new mathematical models must be developed to keep pace with emerging technologies. Modern experimental procedures involve studying 3D multicellular spheroids with fluorescent labels to show both the location of cells and the cell cycle progression. This 4D data (3D spatial information + cell cycle time) provides vast information. No mathematical models ha ....Mathematical models of 4D multicellular spheroids. Mathematical models have a long, successful history of providing biological insight, and new mathematical models must be developed to keep pace with emerging technologies. Modern experimental procedures involve studying 3D multicellular spheroids with fluorescent labels to show both the location of cells and the cell cycle progression. This 4D data (3D spatial information + cell cycle time) provides vast information. No mathematical models have been specifically developed to interpret/predict 4D spheroids. This project will deliver the first high-fidelity mathematical models to interpret/predict 4D spheroid experiments in real time, providing quantitative insight into innate mechanisms and responses to various intervention treatments. Read moreRead less
Australian Laureate Fellowships - Grant ID: FL150100150
Funder
Australian Research Council
Funding Amount
$2,413,112.00
Summary
Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statist ....Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statistics and translating this knowledge to real-world challenges in industry, environment and health. The new big data statistical analysts trained through the project could also create much needed capacity at national and international levels.Read moreRead less
Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in mi ....Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in microscale tissue properties are lacking. The tools developed by this project will be used to generate new magnetic resonance image based maps to convey information on tissue microstructure changes in the human brain. Additionally, the mathematical tools developed will be transferable to other applications where diffusion and transport in heterogeneous porous media play a role.Read moreRead less
Robust inferences for analysis of longitudinal data. This project will develop novel statistical tools. Outcomes of this project will enable more reliable data analysis and more cost effective designs in environmental and biological studies.
Predicting strength of porous materials. This project aims to develop a predictive theory of strength for unflawed, low-ductile porous materials – an unsolved problem in computational solid mechanics. Three-dimensional printing of lightweight, porous materials is used in industry, medicine and science. The project will develop the theory and conduct experiments on porous metallic and polymeric samples made using additive manufacturing, which require understanding and optimisation of the building ....Predicting strength of porous materials. This project aims to develop a predictive theory of strength for unflawed, low-ductile porous materials – an unsolved problem in computational solid mechanics. Three-dimensional printing of lightweight, porous materials is used in industry, medicine and science. The project will develop the theory and conduct experiments on porous metallic and polymeric samples made using additive manufacturing, which require understanding and optimisation of the building of fine scale features. Understanding strength should improve design of stronger materials, by using and extending the capabilities of three-dimensional printing. These advances will further provide a much-needed basis for a fundamental understanding of fracture in other porous materials important to society such as concrete, rocks, porous ceramics and bone implants.Read moreRead less