Discovery Early Career Researcher Award - Grant ID: DE200100200
Funder
Australian Research Council
Funding Amount
$418,398.00
Summary
Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological syste ....Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.
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Construction of near optimal oscillatory regimes in singularly perturbed control systems via solutions of Hamilton-Jacobi-Bellman inequalities. Problems of optimal control of systems evolving in multiple time scales arise in a great variety of applications (from diet to environmental modelling). This project addresses the challenge of analytically and numerically constructing rapidly oscillating controls that would 'near optimally coordinate' the slow and fast dynamics.
Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, i ....Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, integer models usually assume the data is known with certainty, which is often not the case in the real world. This project will develop new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms. Read moreRead less
Occupational measures, perturbations and complex deterministic systems. When tackling complex problems, scientists and engineers seek methods that judiciously exploit stochasticity and perturbations as antidotes to unpredictability of outputs that the latter can induce if they inadvertently influence their models. The project proposes for this study vaccine-like perspective of stochasticity and singular perturbations.
Improving Choice Models: Multiple Goal Pursuit and Multi-Stage Decision Processes. This project aims to develop new econometric models of choice behaviour that recognise individuals adopt “how to decide” strategies when choosing between alternatives. Existing models simplistically assume that people evaluate all goods and choose the best of them, when in fact they ignore some goods, select what information is relevant, pursue multiple goals, and otherwise deviate from the assumptions commonly ma ....Improving Choice Models: Multiple Goal Pursuit and Multi-Stage Decision Processes. This project aims to develop new econometric models of choice behaviour that recognise individuals adopt “how to decide” strategies when choosing between alternatives. Existing models simplistically assume that people evaluate all goods and choose the best of them, when in fact they ignore some goods, select what information is relevant, pursue multiple goals, and otherwise deviate from the assumptions commonly made in econometric models. Filling in this significant gap in the choice modelling literature constitutes a significant contribution to improving our understanding of human decision making and policy analysis in every area of human endeavour.Read moreRead less
Accounting for preference seperability in stated choice experiments. This project aims to unite three separate streams of applied economic research into a single framework in order to develop a micro-economically consistent framework for demand forecasting and analysis. Forecasting demand to improve product performance or policy impacts requires realistic representations of how humans actually make choices. Combining theories of preference separability with recent developments in both activity a ....Accounting for preference seperability in stated choice experiments. This project aims to unite three separate streams of applied economic research into a single framework in order to develop a micro-economically consistent framework for demand forecasting and analysis. Forecasting demand to improve product performance or policy impacts requires realistic representations of how humans actually make choices. Combining theories of preference separability with recent developments in both activity and time use modelling and stated choice techniques, the project plans to develop new insights into consumer equilibrium as well as new econometric methods to test for the assumption of preference separability. Project outcomes would lead to an improved understanding of consumer behaviour as well as demand forecasting, with benefits to studies involving the need for benefit cost comparisons.Read moreRead less
Airborne spatial tracking to save endangered species. Airborne spatial tracking to save endangered species. This project aims to develop an automated and distributed spatial tracking approach using low cost Unmanned Aerial Vehicles (UAVs) to locate and study endangered wildlife. Understanding animal behaviour and habits with granular spatial data is essential to develop effective monitoring and conservation strategies. Spatial tracking of radio collared wildlife using radio telemetry is a critic ....Airborne spatial tracking to save endangered species. Airborne spatial tracking to save endangered species. This project aims to develop an automated and distributed spatial tracking approach using low cost Unmanned Aerial Vehicles (UAVs) to locate and study endangered wildlife. Understanding animal behaviour and habits with granular spatial data is essential to develop effective monitoring and conservation strategies. Spatial tracking of radio collared wildlife using radio telemetry is a critical but costly tool for acquiring this data. This project anticipates that airborne spatial tracking using intelligent spatial tracking algorithms on board low cost UAV teams will allow more precise understanding of wildlife for evidence-based conservation and management in a changing global climate.Read moreRead less
Optimal electromaterial structures for energy applications. This project aims to develop new mathematical and modelling approaches to determine optimal configurations and parameters for material structures created from three-dimensional printing of combined metals and electromaterials. Electromaterials are needed for sustainable energy, but solving coupled-systems of highly nonlinear governing equations is needed for optimal control of spatial arrangement and composition in nano and micro-struct ....Optimal electromaterial structures for energy applications. This project aims to develop new mathematical and modelling approaches to determine optimal configurations and parameters for material structures created from three-dimensional printing of combined metals and electromaterials. Electromaterials are needed for sustainable energy, but solving coupled-systems of highly nonlinear governing equations is needed for optimal control of spatial arrangement and composition in nano and micro-structural domains. Dealing with this mathematical complexity is critical to developing high efficiency energy generation and gas storage systems. This is expected to enhance transport mechanisms within electrochemical devices and create opportunities for industry to use electrofunctional materials.Read moreRead less
Saving energy on trains - demonstration, evaluation, integration. Reducing energy use from rail transport will significantly contribute to cutting carbon dioxide emissions. This project will develop a toolkit to facilitate the introduction of in-cab technologies that help train drivers save energy and stay on time. The toolkit will make it easier to demonstrate, evaluate and integrate the system in a range of railways.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100030
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software ....Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software control. The test bed will empower Australian researchers in network technologies and dependent applications (for example, multimedia and security) to collaboratively develop and demonstrate novel ideas at scale. This is expected to benefit Australia by giving our researchers international recognition in this nascent area, and developing a national talent pool for local industry.Read moreRead less