Semiparametric Regression for Streaming Data. Semiparametric regression converts large and complex data-sets into interpretable summaries from which sound decisions can be made. This project tackles semiparametric regression analysis of streaming data - where the data are so voluminous that they may not be storable in standard computer memory and therefore need to be processed rapidly on arrival and then discarded. Effective solutions necessitate a rethinking of semi-parametric regression and ne ....Semiparametric Regression for Streaming Data. Semiparametric regression converts large and complex data-sets into interpretable summaries from which sound decisions can be made. This project tackles semiparametric regression analysis of streaming data - where the data are so voluminous that they may not be storable in standard computer memory and therefore need to be processed rapidly on arrival and then discarded. Effective solutions necessitate a rethinking of semi-parametric regression and new approaches will be developed. The project will also develop novel theory and methodology for robotics applications. It will allow analysis of streaming and massive data sets that would not be possible using currently available methods, opening up new applications.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
Discovery Early Career Researcher Award - Grant ID: DE130100819
Funder
Australian Research Council
Funding Amount
$281,600.00
Summary
Measuring the improbable: optimal Monte Carlo methods for rare event simulation of maxima of dependent random variables. Some events occurring with low frequency can have dramatic consequences: natural catastrophes, economic crises, system malfunctions. Estimating their probabilities is a very difficult problem. This project will develop new simulation methods capable of delivering the most precise and efficient estimators for the probabilities of such events.
Accelerated Molecular Simulations for Selective Carbon Nanotube Growth. Carbon nanotubes have remarkable electronic and optical properties that are determined precisely by their atomic structure, or ‘chirality’. Development of future carbon nanotube-based technologies is currently prevented by our inability to synthesise particular carbon nanotubes selectively, and this is because the factors that enable selective synthesis remain unknown. This project will develop and use accelerated molecular ....Accelerated Molecular Simulations for Selective Carbon Nanotube Growth. Carbon nanotubes have remarkable electronic and optical properties that are determined precisely by their atomic structure, or ‘chirality’. Development of future carbon nanotube-based technologies is currently prevented by our inability to synthesise particular carbon nanotubes selectively, and this is because the factors that enable selective synthesis remain unknown. This project will develop and use accelerated molecular simulations to determine the factors that enable selective synthesis of particular carbon nanotubes. These simulations will enable targeted carbon nanotube growth, and in doing so will pave the way for the future development of carbon nanotube-based technologies.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101854
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Exploring A New Family of 2D Heterogeneous Topological Insulator. The project aims to reveal a new family of two-dimensional heterostructure topological insulators by extensive theoretical simulations, and develop feasible approaches to control the topological phase, thus enabling their use in practical nanodevice applications. The project aims not only to advance knowledge in material chemistry and condensed matter physics, but also to lead to technology revolutions in information technology, c ....Exploring A New Family of 2D Heterogeneous Topological Insulator. The project aims to reveal a new family of two-dimensional heterostructure topological insulators by extensive theoretical simulations, and develop feasible approaches to control the topological phase, thus enabling their use in practical nanodevice applications. The project aims not only to advance knowledge in material chemistry and condensed matter physics, but also to lead to technology revolutions in information technology, clean energy generation and cooling devices based on topological insulators. The outcomes are expected to produce new technology applications in electronics, communications, information technology, data storage and transportation.Read moreRead less
A coupled finite volume method for viscoelastic flow problems on highly-skewed unstructured meshes: a computational rheology revolution. Commercial tools are unavailable for 21st century industry to analyse complex flow processes involving viscoelastic materials. Using fabrication of microstructured polymer optical fibre as a key case study, a coupled finite volume methodology holds the key for the next generation of computational rheology simulators.
Theoretical modelling study of thin film permeability. Loss of water from open storages through evaporation exceeds 40 per cent. This project will study the structure, stability and permeation properties of the protective ultra-thin layers. The knowledge will help design novel evaporation suppressants which will drastically reduce water losses and will be crucial for new membrane and drug delivery technologies.
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: DE190100876
Funder
Australian Research Council
Funding Amount
$390,000.00
Summary
Unifying chemical concepts for advanced molecular electronics applications. This project aims to build a physical-organic chemistry framework of transferable molecular descriptors for a relatively new but a rapidly developing area of unimolecular electronics (UE) using advanced computational chemistry tools. Established structure-property relationships will drive the cutting-edge applications of UE in sensing and catalysis and significantly expand our understanding of charge transport involving ....Unifying chemical concepts for advanced molecular electronics applications. This project aims to build a physical-organic chemistry framework of transferable molecular descriptors for a relatively new but a rapidly developing area of unimolecular electronics (UE) using advanced computational chemistry tools. Established structure-property relationships will drive the cutting-edge applications of UE in sensing and catalysis and significantly expand our understanding of charge transport involving free radicals and non-covalent assemblies. Expected outcomes of this project include new design guidelines and candidate molecular architectures for such practical applications as organocatalysis inside molecular junctions, molecular spintronics and molecular sensors for reactive oxygen species and nitroaromatic pollutants.Read moreRead less
Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore co ....Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore computers offer. This project aims to lay foundations for extending those benefits to applications where high reliability is a concern. It plans to do so by developing theoretical results about the correctness of algorithms on standard multicore computers, and practical tools and techniques to help programmers of multicore computers to better understand the behaviour of their code.Read moreRead less