Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computatio ....Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computational advances in both areas in recent years. The research will stimulate the design of microscopic and macroscopic complex spatial structures with superior properties, such as composite materials, solar cells, telecommunication networks, mining operations, and road systems.Read moreRead less
Constrained and Stable Solutions of Nonlinear and Semismooth Equations. In this project, comprehensive models for designing safe power system parameters will be proposed, efficient algorthms for solving these models will be constructed. The new models and algorithms in this project will provide efficient tools to prevent catastrophic events in power systems, which is related with national security. This project will also strengthen collaboration of Australian applied
mathematians with inter ....Constrained and Stable Solutions of Nonlinear and Semismooth Equations. In this project, comprehensive models for designing safe power system parameters will be proposed, efficient algorthms for solving these models will be constructed. The new models and algorithms in this project will provide efficient tools to prevent catastrophic events in power systems, which is related with national security. This project will also strengthen collaboration of Australian applied
mathematians with international researchers and engineering scientists. This is important for the advance of science and technology in
Australia.Read moreRead less
Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101761
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Solving intractable problems: from practice to theory and back. By analysing how theoretically intractable problems are solved in practice by highly optimised software solvers, this project aims at a better theoretical understanding of these problems. The gained mathematical insights will then be used to stimulate the development of new and improved software solvers.
Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks ....Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks to address both difficulties by using rigorous statistical signal processing methods to optimally fuse information from a network of low-cost cameras.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Doubly Stochastic Matrices & The Hamiltonian Cycle Problem. The classical hard problem of determining whether a given graph possesses a Hamiltonian cycle contains the essential difficulty of the famous 'Travelling Salesman Problem'. A characterisation of this difficulty in terms of variability of returns (to the initial state) in a controlled stochastic process will be a significant conceptual advance with repercussions in a number of fields including optimisation and theoretical computer scien ....Doubly Stochastic Matrices & The Hamiltonian Cycle Problem. The classical hard problem of determining whether a given graph possesses a Hamiltonian cycle contains the essential difficulty of the famous 'Travelling Salesman Problem'. A characterisation of this difficulty in terms of variability of returns (to the initial state) in a controlled stochastic process will be a significant conceptual advance with repercussions in a number of fields including optimisation and theoretical computer science. Algorithmic advances exploiting such a characterisation will significantly contribute to existing technologies for solving problems in applications ranging from logistics to cryptography. Since TSP describes certain efficient ways of routing its applicability to information networks is clear.Read moreRead less
Simulation Technology for Modelling Extreme Bushfire Behaviour. Extreme fires cause immeasurable damage to communities through destruction of homes and damage to infrastructure. Large, highly intense fires reduce biodiversity, take decades for recovery, increase greenhouse gas emissions and reduce carbon storage capacity. Climate change is likely to increase the frequency of extreme fire weather increasing the need for reliable fire spread prediction under extreme conditions and to reduce impa ....Simulation Technology for Modelling Extreme Bushfire Behaviour. Extreme fires cause immeasurable damage to communities through destruction of homes and damage to infrastructure. Large, highly intense fires reduce biodiversity, take decades for recovery, increase greenhouse gas emissions and reduce carbon storage capacity. Climate change is likely to increase the frequency of extreme fire weather increasing the need for reliable fire spread prediction under extreme conditions and to reduce impact by preparedness and suppression. Incorporating an evidence-based fire spread model into a fire location forecasting system will give fire agencies early warning of potentially disastrous fires, enable early response to prevent fires and mitigate the consequence to life, property and the environment. Read moreRead less
Approximation, Cubature and Point Designs on Spheres. The sphere is important in fields ranging from geophysics to global climate modelling to chemistry to codes for modern communications. This project aims to strengthen and unify key areas of mathematics on the sphere and at the same time provide methods and constructiions of practical significance. The areas of focus are constructive approximation of functions on the sphere, numerical integration on the sphere, and well distributed sets of poi ....Approximation, Cubature and Point Designs on Spheres. The sphere is important in fields ranging from geophysics to global climate modelling to chemistry to codes for modern communications. This project aims to strengthen and unify key areas of mathematics on the sphere and at the same time provide methods and constructiions of practical significance. The areas of focus are constructive approximation of functions on the sphere, numerical integration on the sphere, and well distributed sets of points on the sphere, including spherical designs.Read moreRead less
Next-Generation OFDM Communication Systems: Analysis and Design for the Physical Layer. Next-generation orthogonal frequency-division multiplexed (OFDM) systems represent the future of broadband wireless access technology. Such systems are vital to Australia's future infrastructure and growing economy by providing more bandwidth with greater flexibility for new broadband applications. The research outcomes from this project will help enable future OFDM systems, and thus directly benefit Austra ....Next-Generation OFDM Communication Systems: Analysis and Design for the Physical Layer. Next-generation orthogonal frequency-division multiplexed (OFDM) systems represent the future of broadband wireless access technology. Such systems are vital to Australia's future infrastructure and growing economy by providing more bandwidth with greater flexibility for new broadband applications. The research outcomes from this project will help enable future OFDM systems, and thus directly benefit Australia. Development of cutting-edge information technology know-how will enhance Australia's international ICT reputation. Valuable research training of highly-skilled Australian students is another important benefit.Read moreRead less