New mathematics for multi-extremal optimization and diffusion tensor imaging. This project aims to establish numerically certifiable mathematical theory and methods for semi-algebraic optimisation problems. Numerically certifiable optimisation principles and techniques are vital for the practical use of optimisation technologies because they can be readily implemented by common computer models and algorithms. Yet no such methodologies exist for multi-extremal, semi-algebraic optimisation problem ....New mathematics for multi-extremal optimization and diffusion tensor imaging. This project aims to establish numerically certifiable mathematical theory and methods for semi-algebraic optimisation problems. Numerically certifiable optimisation principles and techniques are vital for the practical use of optimisation technologies because they can be readily implemented by common computer models and algorithms. Yet no such methodologies exist for multi-extremal, semi-algebraic optimisation problems which are common in modern science and medicine. The expected outcomes of this project include enhanced optimisation methods for diffusion tensor imaging, an emerging technology in brain sciences.Read moreRead less
Innovations in sparse optimisation: big data nonsmooth optimisation. This project aims to produce innovative optimisation methods capable of solving a wide range of practical problems that are currently too complex to be solved. Optimisation involving huge data sets is ubiquitous. Sparse optimisation has emerged as a challenging frontier of modern optimisation because it effectively computes an optimal solution with desired low complexity structure so that a resulting solution can be efficiently ....Innovations in sparse optimisation: big data nonsmooth optimisation. This project aims to produce innovative optimisation methods capable of solving a wide range of practical problems that are currently too complex to be solved. Optimisation involving huge data sets is ubiquitous. Sparse optimisation has emerged as a challenging frontier of modern optimisation because it effectively computes an optimal solution with desired low complexity structure so that a resulting solution can be efficiently stored, implemented and utilised, and is robust to the data inexactness. This project aims at developing innovative mathematical techniques and efficient numerical schemes for solving sparse optimisation problems. The intended outcomes will have significant impact on many areas of science, medicine and engineering, where sparse optimisation is used, including cancer radiotherapy optimal planning.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101147
Funder
Australian Research Council
Funding Amount
$407,600.00
Summary
First-principles design of atomic defects for quantum technologies. This project aims to address the issue of designing and engineering better single-photon sources based on atomic defects in solids, a crucial building block for many quantum technologies. Using advanced first-principles quantum mechanical theories and calculations, the project expects to produce fundamental knowledge of key mechanisms and properties, and to use this to inform the design of new atomic defects for tailored applica ....First-principles design of atomic defects for quantum technologies. This project aims to address the issue of designing and engineering better single-photon sources based on atomic defects in solids, a crucial building block for many quantum technologies. Using advanced first-principles quantum mechanical theories and calculations, the project expects to produce fundamental knowledge of key mechanisms and properties, and to use this to inform the design of new atomic defects for tailored applications as quantum emitters. The expected outcomes, including novel methodologies, will contribute to different research areas, from condensed matter and materials physics to quantum science and technology. This project should provide significant benefits in accelerating quantum technology innovation in Australia.Read moreRead less
Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms dev ....Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms developed are expected to allow straightforward deployment of robotic teams. There are myriad applications for cooperative robotic agents, ranging from surveillance, to environmental monitoring using underwater and aerial drone formations – with an array of benefits and impacts including economic, commercial and societal. The results are intended to ensure and cement Australia’s front-line position in the current technological revolution known as “Industry 4.0”.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101527
Funder
Australian Research Council
Funding Amount
$420,000.00
Summary
Real-time control with safety guarantees: theory and applications . Modern network control systems, such as transport systems with self-driving cars, are becoming bigger, more complex and human-involved. The systems are usually equipped with intelligent devices, such as numerous sensing, fast processors and communication components. To adapt to this change and to benefit from these new intelligent devices, efficient algorithms for control and management need to be developed. This project aims to ....Real-time control with safety guarantees: theory and applications . Modern network control systems, such as transport systems with self-driving cars, are becoming bigger, more complex and human-involved. The systems are usually equipped with intelligent devices, such as numerous sensing, fast processors and communication components. To adapt to this change and to benefit from these new intelligent devices, efficient algorithms for control and management need to be developed. This project aims to develop novel optimisation-based control techniques, as well as efficient optimisation algorithms, for future control systems with an emphasis on distributed implementations, taking safety and real-time constraints such as limited computation and communication resources into consideration. Read moreRead less
Engineering one dimensional quantum phases with nanostructured Josephson junction arrays. This project aims to engineer novel quantum electronic devices based on strongly-coupled, one-dimensional superconducting microcircuits. These will be realised using chains of nanoscale superconducting islands fabricated on a chip. The project expects to achieve a special type of insulating state, where individual charges can be transported one by one. This would be significant as a primary standard that pr ....Engineering one dimensional quantum phases with nanostructured Josephson junction arrays. This project aims to engineer novel quantum electronic devices based on strongly-coupled, one-dimensional superconducting microcircuits. These will be realised using chains of nanoscale superconducting islands fabricated on a chip. The project expects to achieve a special type of insulating state, where individual charges can be transported one by one. This would be significant as a primary standard that precisely links time (or frequency) to charge. The project also aims to create a current mirror device, in which a supercurrent sent down one chain induces a reflected supercurrent in the other, forming the basis of a new superconducting quantum bit. Other devices will be used to study a simplified model related to high temperature superconductors.Read moreRead less
Fast approximate inference methods: new algorithms, applications and theory. This project aims to develop new algorithms and theory for fast approximate inference and lay down infrastructure to aid future extensions. Fast approximate inference methods are a principled and extensible means of fitting large and complex statistical models to big data sets. They come into their own in applications where speed is paramount and traditional approaches are not feasible. The project aims to lead to prac ....Fast approximate inference methods: new algorithms, applications and theory. This project aims to develop new algorithms and theory for fast approximate inference and lay down infrastructure to aid future extensions. Fast approximate inference methods are a principled and extensible means of fitting large and complex statistical models to big data sets. They come into their own in applications where speed is paramount and traditional approaches are not feasible. The project aims to lead to practical outcomes from better business decision-making for insurance data warehouses, to improved medical imaging technology.Read moreRead less
Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful ....Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful visualisations, and evaluate using real world social network and biological network data sets. The new models, metrics and algorithms produced by this project will be used in the next generation Visual Analytic tools to enable analysts develop accurate insights and new knowledge of complex data.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100486
Funder
Australian Research Council
Funding Amount
$363,182.00
Summary
Drone witnessing: technologies of perception in war and culture. This project aims to investigate how drones and other technologies of perception are changing how we bear witness and determine the meaning, importance and truth of events. The project will generate new knowledge about the impact of drone warfare and drone technologies on forms and processes of witnessing by analysing both primary and creative texts and by conducting field research into new practices of testimony. Anticipated outco ....Drone witnessing: technologies of perception in war and culture. This project aims to investigate how drones and other technologies of perception are changing how we bear witness and determine the meaning, importance and truth of events. The project will generate new knowledge about the impact of drone warfare and drone technologies on forms and processes of witnessing by analysing both primary and creative texts and by conducting field research into new practices of testimony. Anticipated outcomes include a critical and conceptual framework for witnessing, new terms to inform public debates about the cultural impact of increased reliance on drones in war and culture, and new channels for knowledge exchange between drone and autonomous system designers, humanities scholars and creative practitioners.Read moreRead less
Sublinear algorithms for visual analytics of extreme-scale networks. This project aims to design new sublinear algorithms for the visual analytics of extreme-scale networks, involving billions of nodes. Based on algorithmics for graph drawing, integrating sublinear algorithms and distributed algorithms, the project will introduce new quality metrics for good visualisation of extreme-scale networks, design new sublinear-time algorithms to compute good visualisation, implement them in a distribute ....Sublinear algorithms for visual analytics of extreme-scale networks. This project aims to design new sublinear algorithms for the visual analytics of extreme-scale networks, involving billions of nodes. Based on algorithmics for graph drawing, integrating sublinear algorithms and distributed algorithms, the project will introduce new quality metrics for good visualisation of extreme-scale networks, design new sublinear-time algorithms to compute good visualisation, implement them in a distributed computing environment, and evaluate with a real world social network and biological network data sets. The new algorithms produced by this project will be used in the next generation visual analytic tools for extreme-scale data to enable analysts develop new insights and new knowledge of extreme-scale data.Read moreRead less