Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there ....Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there a major changes to existing series, improving the analysis of such series and the decisions based on them.Read moreRead less
Developing Interpretable Machine Learning Models For Clinical Imaging And Single-cell Genomics
Funder
National Health and Medical Research Council
Funding Amount
$1,312,250.00
Summary
Machine learning methods will be vital to make best use of the deluge of data generated by high-throughput technologies in biomedical science. To get the most out of these models, however, we need to be able to unpack the 'black box'. I will use curated clinical and public research data to benchmark and develop interpretable deep learning models and software tools. These models will be used for breast cancer screening programs and for analysis of complex, large-scale single-cell genomics data.
New statistical tools for mineral exploration targeting and validation. Exploration for new mineral resources depends on information gleaned from geological survey data. This project confronts important, unsolved statistical problems in the analysis of geological survey data which have direct impact on exploration targeting.
Voids in molecular crystals: Novel computational approaches to their characterization, physicochemical nature, and influence on bulk properties. Key to the research objectives is further development of our own innovative software and techniques, now used by hundreds of researchers worldwide for the visualization and exploration of the structure and properties of molecular crystals. Through involvement of postdoctoral fellows and PhD students in an international collaborative research program inv ....Voids in molecular crystals: Novel computational approaches to their characterization, physicochemical nature, and influence on bulk properties. Key to the research objectives is further development of our own innovative software and techniques, now used by hundreds of researchers worldwide for the visualization and exploration of the structure and properties of molecular crystals. Through involvement of postdoctoral fellows and PhD students in an international collaborative research program involving a synergy between software development and visualization, and sophisticated modelling of the detailed nature of molecular crystals, the project contributes directly to producing researchers familiar with state-of-the-art theoretical and computational techniques, and well equipped to match the needs of one of the nation's articulated research priorities.Read moreRead less
Quantum chemical methods: From wavefunction to density functional theory. This project aims to address a major challenge in quantum chemistry - how to extend the applicability of high-level quantum chemical methods to larger molecules. High-level quantum chemical methods can consistently obtain reliable thermochemical and kinetic data, but due to their steep computational cost, they are only applicable to relatively small molecules. The project expects to introduce new concepts and methodologies ....Quantum chemical methods: From wavefunction to density functional theory. This project aims to address a major challenge in quantum chemistry - how to extend the applicability of high-level quantum chemical methods to larger molecules. High-level quantum chemical methods can consistently obtain reliable thermochemical and kinetic data, but due to their steep computational cost, they are only applicable to relatively small molecules. The project expects to introduce new concepts and methodologies that build on recent breakthrough research in the field of ab initio computational chemistry. The new methods should be capable of energetic predictions of unprecedented accuracy for relatively large systems across the Periodic Table and will be used for the development of better density functional theory procedures.Read moreRead less
Robust Reformulation Methods. Many decision problems in engineering, business and economics are modeled as nonlinear continuous optimization problems. Often these are made difficult by the existence of constraints. In this project, we reformulate such problems as constrained nonsmooth equations, rather than optimization problems, and develop generalized Newton and quasi-Newton methods for solving them. The expected outcomes of this project include a systematic theory of reformulation methods, ....Robust Reformulation Methods. Many decision problems in engineering, business and economics are modeled as nonlinear continuous optimization problems. Often these are made difficult by the existence of constraints. In this project, we reformulate such problems as constrained nonsmooth equations, rather than optimization problems, and develop generalized Newton and quasi-Newton methods for solving them. The expected outcomes of this project include a systematic theory of reformulation methods, and robust and efficient algorithms for solving some important nonlinear continuous optimization problems. There is high potential for applications in engineering, business and finance.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.Read moreRead less
Simulation of ligand binding-induced conformational changes in biological systems. This project is focused on the development of a methodology that will allow using molecular dynamics simulations to study fundamental biochemical reactions. The benefits to the Australian community are two fold: i) the software developed will be made available to the whole scientific community through peer-reviewed publication. Australian researchers will have the possibility to exploit the software in advance thr ....Simulation of ligand binding-induced conformational changes in biological systems. This project is focused on the development of a methodology that will allow using molecular dynamics simulations to study fundamental biochemical reactions. The benefits to the Australian community are two fold: i) the software developed will be made available to the whole scientific community through peer-reviewed publication. Australian researchers will have the possibility to exploit the software in advance through collaborations with our research group. ii) During this collaboration Australian PhD students will have the opportunity to spend a few months overseas to learn about the most advanced computational techniques and interact with top researchers in the computational chemistry field.Read moreRead less
Statistical methodology for events on a network, with application to road safety. This project develops new methods to analyse road traffic accident rates, aiming to identify accident black spots and to develop an evidence base for future road design and road safety management. These methods can be applied to other types of events on a network of roads, railways, rivers, electrical wires, communication networks or airline routes.
Modelling the structure of Australian wool auction prices. Australian wool auction ($3.5-4 billions per year) is an on-going process. The prices paid in this auction market are used by the Australian production and service sectors to identify the quality preferences the international retail markets and the intermediate processors. The proposed research will optimise the information that can be extracted and used by these sectors in the production and distribution of the raw wool clip. A two- ....Modelling the structure of Australian wool auction prices. Australian wool auction ($3.5-4 billions per year) is an on-going process. The prices paid in this auction market are used by the Australian production and service sectors to identify the quality preferences the international retail markets and the intermediate processors. The proposed research will optimise the information that can be extracted and used by these sectors in the production and distribution of the raw wool clip. A two-stages algorithm in tree-based regression will be developed. The project will provide a challenge environment to train a Ph.D. student in agriculture modelling and optimisation.Read moreRead less