Discovery Early Career Researcher Award - Grant ID: DE200100063
Funder
Australian Research Council
Funding Amount
$394,398.00
Summary
Nonmonotone Algorithms in Operator Splitting, Optimisation and Data Science. This project aims to develop the mathematical foundations for the analysis and development of optimisation algorithms used in data science. Despite their now ubiquitous use, machine learning software packages routinely rely on a number of algorithms from mathematical optimisation which are not properly understood. By moving beyond the traditional realms of Fejér monotone algorithms, this project expects to develop the m ....Nonmonotone Algorithms in Operator Splitting, Optimisation and Data Science. This project aims to develop the mathematical foundations for the analysis and development of optimisation algorithms used in data science. Despite their now ubiquitous use, machine learning software packages routinely rely on a number of algorithms from mathematical optimisation which are not properly understood. By moving beyond the traditional realms of Fejér monotone algorithms, this project expects to develop the mathematical theory required to rigorously justify the use of such algorithms and thereby ensure the integrity of the decision tools they produce. This mathematical framework is also expected to produce new algorithms for optimisation which benefit consumers of data science such as the health-care and cybersecurity sectors.Read moreRead less
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
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.Read moreRead less
Maximizing Dimensional Efficiency With Minimal Cardinality Pattern Combinations. Making optimal use of dimensional capacity is often fundamental to the efficiency of processes in science and industry. Many important applications use combinations of patterns to achieve this. For example, in paper and in steel manufacturing, reels are divided lengthwise into cutting patterns, combined so as to minimize waste. In medicine, radiation patterns are combined to effectively treat cancerous tumours. ....Maximizing Dimensional Efficiency With Minimal Cardinality Pattern Combinations. Making optimal use of dimensional capacity is often fundamental to the efficiency of processes in science and industry. Many important applications use combinations of patterns to achieve this. For example, in paper and in steel manufacturing, reels are divided lengthwise into cutting patterns, combined so as to minimize waste. In medicine, radiation patterns are combined to effectively treat cancerous tumours. By addressing the common mathematical structure underlying pattern combination, this project will account for a hitherto neglected critical factor - the solution cardinality - making fully optimized solutions available for the first time to many applications in science and industry.Read moreRead less
Faster, cheaper, better: mathematical advances for improved design and scheduling of robotic instrumentation. This project extends previous research addressing mathematical challenges in the optimal design and scheduling of robotic instrumentation. The Partner Organisation manufactures instruments for cancer diagnostics, and designs instruments that need to produce rapid, high-quality results, at a reasonable cost in a competitive market. It is intended that powerful new scheduling algorithms wi ....Faster, cheaper, better: mathematical advances for improved design and scheduling of robotic instrumentation. This project extends previous research addressing mathematical challenges in the optimal design and scheduling of robotic instrumentation. The Partner Organisation manufactures instruments for cancer diagnostics, and designs instruments that need to produce rapid, high-quality results, at a reasonable cost in a competitive market. It is intended that powerful new scheduling algorithms will be devised to handle their complex problem, which is more challenging than standard problems. The developed methodologies aim to reduce the product development cycle and boost the competitiveness of Australian manufacturers. In addition, new theoretical and algorithmic contributions aim to enable improved scheduling in other application areas.Read moreRead less
Creating subject-specific mathematical models to understand the brain. This project aims to develop a mathematical framework that bridges the different scales of brain activities to provide a new tool for understanding the brain. Methods will be developed that unify individual neural activity with large scale brain activity. The approach will be validated by comparing predictions of interconnected models of neural populations (called mean-field models) to experimental data. The creation of subje ....Creating subject-specific mathematical models to understand the brain. This project aims to develop a mathematical framework that bridges the different scales of brain activities to provide a new tool for understanding the brain. Methods will be developed that unify individual neural activity with large scale brain activity. The approach will be validated by comparing predictions of interconnected models of neural populations (called mean-field models) to experimental data. The creation of subject-specific models from data is important, as there is large variability in neural circuits between individuals despite seemingly similar network activity. The intended outcome is new insights into the processes that govern brain function and methods for improving functional imaging of, and interfacing to, the brain.Read moreRead less
Performance Evaluation Methodologies for the Optical Internet. It will be important to Australia to be an early adopter of a next-generation Internet technology not only to ensure that the country retains its place in the world economic community of but also to ensure that its industries and citizens have access to new technologies. Techniques and methodologies emerging from this project will enable the design of Australia's future optical Internet.
The project will enable strategic decisions ....Performance Evaluation Methodologies for the Optical Internet. It will be important to Australia to be an early adopter of a next-generation Internet technology not only to ensure that the country retains its place in the world economic community of but also to ensure that its industries and citizens have access to new technologies. Techniques and methodologies emerging from this project will enable the design of Australia's future optical Internet.
The project will enable strategic decisions on the viability of new technologies, and as a result Australian service providers will have better and cheaper networks, and Australian users will enjoy better services at a lower cost.
The project will enhance the Australian knowledge base, skills base in the area of teletraffic and optical networking.
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Advances in data integration modelling for infectious disease response. This project aims to develop powerful mathematical frameworks that integrate data from multiple sources to facilitate informed decisions in response to the threat of present, and future, infectious diseases. The project expects to generate new knowledge in mathematics by advancing the tools for incorporating multiple data sources into models of infectious diseases. The expected outcomes include enhanced capacity to predict s ....Advances in data integration modelling for infectious disease response. This project aims to develop powerful mathematical frameworks that integrate data from multiple sources to facilitate informed decisions in response to the threat of present, and future, infectious diseases. The project expects to generate new knowledge in mathematics by advancing the tools for incorporating multiple data sources into models of infectious diseases. The expected outcomes include enhanced capacity to predict spatiotemporal changes in transmission of infectious diseases. This project should provide significant benefits in the advancement of modelling techniques broadly applicable to infectious disease settings, which will be demonstrated for antimalarial drug resistance – a major threat to malaria elimination.
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How calcium makes the heart grow. This project aims to develop a mathematical model of calcium signalling in heart cells to understand how calcium makes the heart grow. Our hearts grow to adapt to long-term changes, such as during development and in pregnancy or heart disease. Biochemical reactions involving calcium control the growth of heart cells and heart cells also use calcium signalling to trigger contraction with each beat. How calcium controls the heartbeat and regulates cell growth is u ....How calcium makes the heart grow. This project aims to develop a mathematical model of calcium signalling in heart cells to understand how calcium makes the heart grow. Our hearts grow to adapt to long-term changes, such as during development and in pregnancy or heart disease. Biochemical reactions involving calcium control the growth of heart cells and heart cells also use calcium signalling to trigger contraction with each beat. How calcium controls the heartbeat and regulates cell growth is unknown. This project will develop a new mathematical model of calcium signalling in heart cells to understand important cellular adaption processes. This knowledge will lead to the ability to independently control cellular pathways mediated by calcium, opening new avenues in biotechnology and biomedicine.Read moreRead less