Monitoring health and wellbeing of seniors using unintrusive sensors. This project addresses concerns regarding the wellbeing of seniors living at home by modelling their daily routines to detect significant changes due to functional decline or the onset of illness. These models are planned to be integrated into a personalised in-home monitoring system that also detects instantaneous adverse events, such as falls. This system will include a novel inexpensive sensor bundle comprising unintrusive ....Monitoring health and wellbeing of seniors using unintrusive sensors. This project addresses concerns regarding the wellbeing of seniors living at home by modelling their daily routines to detect significant changes due to functional decline or the onset of illness. These models are planned to be integrated into a personalised in-home monitoring system that also detects instantaneous adverse events, such as falls. This system will include a novel inexpensive sensor bundle comprising unintrusive sensors and decision procedures that determine whether and how to communicate with seniors and carers to deliver information and alerts. The effectiveness and acceptance of these technologies will be evaluated on a diverse population of seniors and carers.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100630
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Relating function of complex networks to structure using information theory. This project aims to investigate networks in order to translate network function to a universal language of information flows. Network science has used common tools to reveal universal connection structures within various biological and man-made networks – our brains, social networks and power grids are all networks of interacting components. Yet there is no common method to study the function of these networks and how ....Relating function of complex networks to structure using information theory. This project aims to investigate networks in order to translate network function to a universal language of information flows. Network science has used common tools to reveal universal connection structures within various biological and man-made networks – our brains, social networks and power grids are all networks of interacting components. Yet there is no common method to study the function of these networks and how such function is coupled with structure. This project aims to relate network structure to function by using measures of information processing as a generally-applicable framework. This will deliver a theory of how structure gives rise to dynamics and how structure can be optimised for desired dynamics.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
Search strategy optimisation by theory, functional analysis and simulation. This project aims to develop a novel computational platform, based on mathematical, statistical and physical theory, as well as advanced simulations, enabling the quantitative prediction of the optimal search strategy to be adopted by populations of agents searching for scarce targets in any given environment. This could lead to significant impacts on breakthrough developments in cancer immunotherapy, search and rescue r ....Search strategy optimisation by theory, functional analysis and simulation. This project aims to develop a novel computational platform, based on mathematical, statistical and physical theory, as well as advanced simulations, enabling the quantitative prediction of the optimal search strategy to be adopted by populations of agents searching for scarce targets in any given environment. This could lead to significant impacts on breakthrough developments in cancer immunotherapy, search and rescue robotics, ecological and environmental management, and developmental biology.Read moreRead less
Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what spe ....Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what specific changes led to the evolutionary success of a protein, and to re-run evolution to generate proteins that perform in conditions suitable for industrial and agricultural applications, in particular the production of hydroxylated fatty acids for bioplastics. By examining proteins from many life forms, the project plans to develop a novel bioinformatics strategy to understand their evolution and engineer new proteins for use in production of chemical commodities.Read moreRead less
Next-generation Protein Structural comparison using Information Theory. Progress in protein structural biology relies heavily on key computational technologies, structural alignment being an indispensable one. Despite its importance the structural alignment problem has not been formulated, much less solved, in a consistent and reliable way. This project aims to rectify this by combining novel information-theoretic inference with advances in constraint optimisation and visualisation. State-of-the ....Next-generation Protein Structural comparison using Information Theory. Progress in protein structural biology relies heavily on key computational technologies, structural alignment being an indispensable one. Despite its importance the structural alignment problem has not been formulated, much less solved, in a consistent and reliable way. This project aims to rectify this by combining novel information-theoretic inference with advances in constraint optimisation and visualisation. State-of-the-art alignment methods aim to be produced for biologists to generate statistically-rigorous and biologically-trustworthy alignments, and allow them to visualise structural relationships in unprecedented ways. This project is expected to provide direct payoffs to the fields of protein science, crystallography and bioinformatics.Read moreRead less
A technology platform for multiple body site image-omics. The project aim is to derive a technology platform comprising new image processing and machine learning algorithms to integrate imaging and biological data across multiple body sites. The relationships between image features and biological data across multiple sites has not been discovered before. We propose the use of biological information from one sampled site to investigate other unsampled sites based on imaging-omics correspondences. ....A technology platform for multiple body site image-omics. The project aim is to derive a technology platform comprising new image processing and machine learning algorithms to integrate imaging and biological data across multiple body sites. The relationships between image features and biological data across multiple sites has not been discovered before. We propose the use of biological information from one sampled site to investigate other unsampled sites based on imaging-omics correspondences. We will use a data-driven, searchable graph model approach for knowledge discovery within the population data. The project will provide new insights into systems biology and bioinformatics that will then inform and promote benefits in life sciences, with potential future benefits in healthcare.Read moreRead less
Brain-based sensor fusion for navigating robots. This project uses new findings in neuroscience to create robots that can self-determine which of their sensors will best help them learn to navigate in an environment. This technology enables robot systems to be flexibly deployed without prior calibration for wide ranging applications in environments from office buildings to outdoor ecosystems.
Discovery Early Career Researcher Award - Grant ID: DE170100037
Funder
Australian Research Council
Funding Amount
$329,287.00
Summary
Time series classification for new-generation Earth observation satellites. This project aims to develop time series classification methods for satellite images, to produce accurate temporal land-cover maps. Latest generation satellites have just begun imaging Earth frequently, completely, in high-resolution, and at no charge to end-users – an unprecedented opportunity to monitor the flux of our planet's systems. However, time series classification techniques do not scale to handle such wealth o ....Time series classification for new-generation Earth observation satellites. This project aims to develop time series classification methods for satellite images, to produce accurate temporal land-cover maps. Latest generation satellites have just begun imaging Earth frequently, completely, in high-resolution, and at no charge to end-users – an unprecedented opportunity to monitor the flux of our planet's systems. However, time series classification techniques do not scale to handle such wealth of data. The project anticipates its time series technologies will be applicable in agriculture planning, fire prevention, and disaster mapping, and that substantially greater value can be derived from significant investments into Earth Observation programmes.Read moreRead less
Novel decomposition methods for large scale optimisation. This project will develop more effective problem decomposition methods that are critical for handling large scale problems (problems with up to several thousands of variables). The project will benefit practitioners from many different fields, and will put Australia at the very forefront of international research for large scale optimization.