Pattern formation of precursor films: a new mathematical model. This project aims to develop a new mathematical model to predict the pattern formation of a new class of permanent lubricants. Ionic liquids are conductive and do not evaporate, creating a unique opportunity to develop such coatings. These thin films form patterns where the pattern type (patches, stripes or holes) depends on the liquid/surface interaction. Only some patterns result in good lubrication; current limited understanding ....Pattern formation of precursor films: a new mathematical model. This project aims to develop a new mathematical model to predict the pattern formation of a new class of permanent lubricants. Ionic liquids are conductive and do not evaporate, creating a unique opportunity to develop such coatings. These thin films form patterns where the pattern type (patches, stripes or holes) depends on the liquid/surface interaction. Only some patterns result in good lubrication; current limited understanding of the pattern formation process hampers selection of a good lubricant for a chosen material. Current mathematical approaches are computationally expensive and time consuming. The new model expected from this project would provide a cheap, fast and reliable alternative for screening suitable liquid/surface pairs.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL210100110
Funder
Australian Research Council
Funding Amount
$3,021,288.00
Summary
New Approaches to Understand How Form and Function Shape Complex Systems. As biology and medicine transform into quantitative sciences, existing mathematical methods are often inadequate to explain the data they generate. This project aims to unlock the potential of such biomedical data through the development of new mathematical approaches that combine concepts from pure and applied mathematics, statistics and data science, and then to investigate their ability to generate mechanistic insight i ....New Approaches to Understand How Form and Function Shape Complex Systems. As biology and medicine transform into quantitative sciences, existing mathematical methods are often inadequate to explain the data they generate. This project aims to unlock the potential of such biomedical data through the development of new mathematical approaches that combine concepts from pure and applied mathematics, statistics and data science, and then to investigate their ability to generate mechanistic insight into fundamental biomedical processes. In this way, the project expects to affect a paradigm shift in mathematical biology while strengthening Australia’s reputation as a world-leader in mathematical biology. An outcome from this project could be new mathematical models that guide decision making in the clinic.Read moreRead less
A dynamical systems theory approach to machine learning. Forecasting the future state of a high-dimensional complex multi-scale system is a challenge we face in areas ranging from climate science to epidemiology. Even when basic physical mechanisms have been identified, the actual evolution equations are often unknown. This project will develop a computationally cheap machine learning framework for forecasting. The proposed mathematical framework provides a forecast together with a quantificati ....A dynamical systems theory approach to machine learning. Forecasting the future state of a high-dimensional complex multi-scale system is a challenge we face in areas ranging from climate science to epidemiology. Even when basic physical mechanisms have been identified, the actual evolution equations are often unknown. This project will develop a computationally cheap machine learning framework for forecasting. The proposed mathematical framework provides a forecast together with a quantification of its uncertainty. We will develop sophisticated mathematical theory underpinning the novel methodology, as well as applying it to the perennial problem of subgrid-scale parametrisation of tropical convection, a missing key element in current climate models.Read moreRead less
Solving inverse problems with Iterative regularisation and convex penalties. This project aims to develop and investigate new computational procedures for the solution of inverse problems which do not have the usual smoothness properties (or source conditions) required for the traditional regularisation methods. Examples of such inverse problems are very common and include image restoration, photo-acoustic tomography and spectroscopy. It is anticipated that this project will substantially extend ....Solving inverse problems with Iterative regularisation and convex penalties. This project aims to develop and investigate new computational procedures for the solution of inverse problems which do not have the usual smoothness properties (or source conditions) required for the traditional regularisation methods. Examples of such inverse problems are very common and include image restoration, photo-acoustic tomography and spectroscopy. It is anticipated that this project will substantially extend the toolbox of methods for such problems utilising ideas from Banach spaces, convex analysis, parallel computing and optimisation. This project is expected to make a substantial contribution to a better understanding of inverse problems and their solution procedures.Read moreRead less
Power Control and Scheduling for Cellular Communications. Australia is a major user of cellular communications technology with four 3G networks. There is huge public interest in core performance metrics including coverage, quality of service, power consumption and cost. The research covered by this proposal is aimed at improving the above performance metrics and hence achieving greater satisfaction from the Australian public in their wireless communication systems.
Operations research without convexity. Operations Research (OR) is one of the most applicable areas of mathematics and of importance for the future of technologically advanced Australia. However, applications of OR often require convexity. This is a serious limitation. A new approach, monotonic analysis, which is applicable to a broad class of nonconvex problems, was given birth by the CI. Promising results have been obtained and leading researchers around the world (including the Presidents ....Operations research without convexity. Operations Research (OR) is one of the most applicable areas of mathematics and of importance for the future of technologically advanced Australia. However, applications of OR often require convexity. This is a serious limitation. A new approach, monotonic analysis, which is applicable to a broad class of nonconvex problems, was given birth by the CI. Promising results have been obtained and leading researchers around the world (including the Presidents of the Canadian Mathematical and French Applied Mathematics Societies) are keen to work with the CI developing this topic. This project both cements and extends world leadership in this field.Read moreRead less
Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share si ....Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share similar patterns. Association of these patterns with features of 3-dimensional structures of protein families and their functional characteristics can contribute towards the understanding of the relationship between primary structure and function of a protein.Read moreRead less
Safe Adaptive Control. Adaptive controllers are intelligent controllers, which can redesign themselves as they learn more about the environment. There are many algorithms for adaptive controllers; some of them can cause unacceptable behaviour during the learning process. Safe adaptive controllers are those for which this behaviour is ruled out. This project is concerned with developing procedures for guaranteeing the safety property in a wide variety of situations.
Uncertainties in coherent transport of particles and intrinsic properties. This Project aims to quantify the uncertainty of a model output in terms of uncertainties in modelling assumptions, by developing new mathematical techniques and applying them to real-world data. This will be in the context of assessing the accuracy of tracking coherently moving structures (e.g., hurricanes, oceanic biodiversity hotspots, pollutant patches, insect swarms) from experimental/observational data sets. Novel, ....Uncertainties in coherent transport of particles and intrinsic properties. This Project aims to quantify the uncertainty of a model output in terms of uncertainties in modelling assumptions, by developing new mathematical techniques and applying them to real-world data. This will be in the context of assessing the accuracy of tracking coherently moving structures (e.g., hurricanes, oceanic biodiversity hotspots, pollutant patches, insect swarms) from experimental/observational data sets. Novel, data-tested, mathematical methods for uncertainty quantification of coherent structures will be developed as Project outcomes. Project benefits include new insights into protecting the environment, improved uncertainty quantification in climate modelling, and the generation of interdisciplinary knowledge and training.Read moreRead less