Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less
Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less
Reliable and accurate statistical solutions for modern complex data. This project aims to develop novel methods for reliable and accurate statistical modelling with modern, complex correlated and error-prone data. The project expects to make significant strides towards future-proofing statistical data analysis, equipping practitioners with a suite of robust and computationally efficient methods which provide confidence in the stability and reproducibility of results obtained, while offering guar ....Reliable and accurate statistical solutions for modern complex data. This project aims to develop novel methods for reliable and accurate statistical modelling with modern, complex correlated and error-prone data. The project expects to make significant strides towards future-proofing statistical data analysis, equipping practitioners with a suite of robust and computationally efficient methods which provide confidence in the stability and reproducibility of results obtained, while offering guarantees on their transferability over a range of populations. This will provide important benefits as they are applied in predicting endangered marine species for fisheries conservation, and in enhancing our national understanding of the relationship between education achievement and financial success. Read moreRead less
New methods in spectral geometry. This project aims to use methods from mathematical scattering theory to resolve problems in the spectral analysis and index theory of differential operators. Both areas underpin the theoretical understanding of physical materials at micro length scales where quantum phenomena dominate. The project will develop new mathematical results in spectral analysis and geometry, and apply its results to theoretical models of quantum phenomena whose spectral properties are ....New methods in spectral geometry. This project aims to use methods from mathematical scattering theory to resolve problems in the spectral analysis and index theory of differential operators. Both areas underpin the theoretical understanding of physical materials at micro length scales where quantum phenomena dominate. The project will develop new mathematical results in spectral analysis and geometry, and apply its results to theoretical models of quantum phenomena whose spectral properties are at the limit of the range of mathematical techniques. Solving these problems is expected to influence non-commutative analysis.Read moreRead less
Flipping the mattress: infinite polyurethane recycling by synthetic biology. Australia is covered in billions of tonnes of plastic and yet <10% is recycled today. Polyurethane (PU) is ubiquitous in our everyday lives, from lacquer coatings to elastane clothing to durable foam padding in car seats, cushions and mattresses. Currently, there are few avenues for PU recycling and much ends up in landfill e.g., a single mattress produces 15-20kg of PU foam waste. Luckily, biodegradation of PU can occu ....Flipping the mattress: infinite polyurethane recycling by synthetic biology. Australia is covered in billions of tonnes of plastic and yet <10% is recycled today. Polyurethane (PU) is ubiquitous in our everyday lives, from lacquer coatings to elastane clothing to durable foam padding in car seats, cushions and mattresses. Currently, there are few avenues for PU recycling and much ends up in landfill e.g., a single mattress produces 15-20kg of PU foam waste. Luckily, biodegradation of PU can occur naturally via various microbial means and from insects, like Galleria mellonella larvae. The overall aim of this research project is to understand plastic biodegradation and translate nature’s solutions into flexible and efficient synthetic enzyme technologies that can sustainably recycle commonly used PU foams. Read moreRead less
Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alter ....Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alteration occurring during gravity driven convection. Expected outcomes are the in-situ characterisation of solid-surface interactions and predictions of multi-phase fluid flow. The project benefits the Australian resources sector by improving injectivity, storage efficiency and security of supercritical CO2 storage projects.Read moreRead less
Optimising plant populations for ecological restoration and resilience. When choosing individual plants for restoration populations, there is potentially a trade-off between maximising genetic diversity (‘adaptability’) and selection for desirable properties (‘adaptation’). This project aims to develop pioneering methods to quantify this trade-off, and facilitate the design of optimised populations, with a focus on two Australian rainforest trees that are being impacted by myrtle rust infection: ....Optimising plant populations for ecological restoration and resilience. When choosing individual plants for restoration populations, there is potentially a trade-off between maximising genetic diversity (‘adaptability’) and selection for desirable properties (‘adaptation’). This project aims to develop pioneering methods to quantify this trade-off, and facilitate the design of optimised populations, with a focus on two Australian rainforest trees that are being impacted by myrtle rust infection: Rhodamnia argentea and Rhodamnia rubescens. By studying the genetic variation in each species, and how this relates to myrtle rust resistance and climate, this project aims to design populations that are genetically diverse, maximally resistant to myrtle rust, and adapted to future climate.Read moreRead less
The Epigenetics of Sex in the Dragon. Genetic codes do not directly translate to phenotypes -- environment acts through epigenetics to modify development. We use advanced molecular techniques to examine how epigenetics responds to temperature to reverse sex in our novel animal model, the dragon lizard. How does the cell sense temperature? Once the extrinsic signal is captured, how does it influence chromatin modification to release or suppress key genes in the sex differentiation pathway? Which ....The Epigenetics of Sex in the Dragon. Genetic codes do not directly translate to phenotypes -- environment acts through epigenetics to modify development. We use advanced molecular techniques to examine how epigenetics responds to temperature to reverse sex in our novel animal model, the dragon lizard. How does the cell sense temperature? Once the extrinsic signal is captured, how does it influence chromatin modification to release or suppress key genes in the sex differentiation pathway? Which sex genes are targets? Epigenetic enzymes are astonishingly conserved, providing exciting opportunities to draw from human systems to unravel novel signatures of temperature-induced sex switching in reptiles. This project will advance knowledge of developmental programming generally.Read moreRead less
Evolution and mechanisms of interactions in biofilm communities. This project aims to study the long-term experimental evolution of a mixed species bacterial biofilm community. This project expects to gain understanding of the genetic and physiological basis of community evolution. Expected outcomes of this project will be an understanding of how synthetic communities evolve. This will significantly benefit the use of synthetic communities relevant to fields such as antibiotic design, biotechnol ....Evolution and mechanisms of interactions in biofilm communities. This project aims to study the long-term experimental evolution of a mixed species bacterial biofilm community. This project expects to gain understanding of the genetic and physiological basis of community evolution. Expected outcomes of this project will be an understanding of how synthetic communities evolve. This will significantly benefit the use of synthetic communities relevant to fields such as antibiotic design, biotechnology, bioremediation, and synthetic biology where evolution can be inhibited or exploited, respectively.Read moreRead less