Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less
Crowd tracking and visual analytics for rapidly deployable imaging devices. Crowd tracking and visual analytics for rapidly deployable imaging devices. This project aims to develop visual analytics technology that adds machine intelligence to a rapidly deployable time-lapse imaging platform. Such devices can operate on solar and wind power, and be remotely programmed (via a cellular network) to take photos and send them to a server at given times. This project, which focuses on monitoring crowds ....Crowd tracking and visual analytics for rapidly deployable imaging devices. Crowd tracking and visual analytics for rapidly deployable imaging devices. This project aims to develop visual analytics technology that adds machine intelligence to a rapidly deployable time-lapse imaging platform. Such devices can operate on solar and wind power, and be remotely programmed (via a cellular network) to take photos and send them to a server at given times. This project, which focuses on monitoring crowds of objects of interest, is expected to introduce “smart” imaging platforms that could be triggered and shoot high-quality photographs when “events of interest” occur. This project could make Australia both a world leader in video analytics and secure through on-line threat detection, and improve traffic control and agriculture.Read moreRead less
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
Harmonic analysis of differential operators in Banach spaces. This proposal aims to develop harmonic analysis (the mathematical tools used in digital music and photography) in new contexts. It focuses on boundary value problems (the theory behind medical or geological imaging) and stochastic equations (which describe phenomena with random components such as the behaviour of financial markets).
Advanced Bayesian Inversion Algorithms for Wave Propagation. This project aims to improve algorithms for detecting hidden items by developing new computational mathematical techniques capable of reconstructing the shape and location of objects using electromagnetic waves. This project expects to generate new knowledge in the areas of Bayesian Inversion and computational wave propagation. Expected outcomes of this project are algorithms that can be developed for use in nonintrusive radio wave sec ....Advanced Bayesian Inversion Algorithms for Wave Propagation. This project aims to improve algorithms for detecting hidden items by developing new computational mathematical techniques capable of reconstructing the shape and location of objects using electromagnetic waves. This project expects to generate new knowledge in the areas of Bayesian Inversion and computational wave propagation. Expected outcomes of this project are algorithms that can be developed for use in nonintrusive radio wave security scanners. This should provide benefits such as the capability to scan a crowd without a checkpoint, which will have the potential to improve security in public places.Read moreRead less
Fundamental investigation of heat and mass transfer in nanofluids: a mechanistic approach. This project aims to develop a mathematical model in order to predict complex boiling in using nanofluids as new coolant for heat removal. Implementation and resultant computer codes thereafter will provide industries with significant benefits and reduce times and costs in their future design of ultra-high efficient heat removal systems.
Discovery Early Career Researcher Award - Grant ID: DE120100163
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Modelling and simulation of instabilities in unsaturated soils due to wetting. Ground instabilities due to wetting are a critical issue that will be investigated through this project via the development of risk assessment tools. A rational engineering approach and calculation framework will be developed in order to predict failures and facilitate the design of new safer structures.
Discovery Early Career Researcher Award - Grant ID: DE210101344
Funder
Australian Research Council
Funding Amount
$364,981.00
Summary
Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as t ....Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as they emerge and monitor levels of drug resistance.Read moreRead less
Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provi ....Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provide a new way of fitting a wide class of statistical models to evolutionary data, in a very general setting. Further, this project will unite current methodology in a broader framework so that the proposed new methods are a generalisation of currently accepted theory. The outcomes will include a freely-available software package that implements the methods in a user-friendly form.Read moreRead less
Congestion control of networks: a unified stochastic framework. Systems such as the internet, wireless networks and the power grid require efficient allocation of shared resources. This research will develop ways to reduce delays in the internet and allow for growth in the power grid, without requiring additional infrastructure.