Discovery Early Career Researcher Award - Grant ID: DE240100477
Funder
Australian Research Council
Funding Amount
$449,592.00
Summary
Quantifying climate change impacts for wetlands in agricultural landscapes. This project aims to quantify the impacts of changed water availability on wetland biodiversity. Research will focus on high conservation value wetlands in agricultural regions, which face significant climatic risk. Novel integration of biodiversity theory with hydroecological and spatial modelling is expected to generate new understanding of how water availability drives wetland diversity. Intended outcomes include new ....Quantifying climate change impacts for wetlands in agricultural landscapes. This project aims to quantify the impacts of changed water availability on wetland biodiversity. Research will focus on high conservation value wetlands in agricultural regions, which face significant climatic risk. Novel integration of biodiversity theory with hydroecological and spatial modelling is expected to generate new understanding of how water availability drives wetland diversity. Intended outcomes include new techniques to model wetland biodiversity, building of international collaborations and enhanced ability to support policy development to ameliorate climate-related wetland impacts. This should promote sustainable management of water and biodiversity in farmlands, benefitting productive capacity and environmental amenity.Read moreRead less
Congestion control in complex networks with higher-order interactions. Traffic congestion significantly costs the Australian economy and environment. This project aims to develop ground-breaking network models of urban traffic systems to build a new congestion control framework. The purpose of network modelling is to capture the interdependence between different parts of traffic systems, which facilitates studying congestion cascade within the network. The project expects to generate next genera ....Congestion control in complex networks with higher-order interactions. Traffic congestion significantly costs the Australian economy and environment. This project aims to develop ground-breaking network models of urban traffic systems to build a new congestion control framework. The purpose of network modelling is to capture the interdependence between different parts of traffic systems, which facilitates studying congestion cascade within the network. The project expects to generate next generation of network models for more effective congestion control. Expected outcomes include novel congestion control technologies that adjust traffic signals in real-time to optimally utilise the available road space. This should provide significant economic and environmental benefits to Australians by easing traffic jams.Read moreRead less
Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in w ....Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in which they persist. Anticipated outcomes include enhanced capacity to apply mechanistic models to conservation problems, methods for communicating uncertainties and models for tens of species of immediate conservation interest. This will enable more reliable biodiversity forecasts, supporting better decision-making.
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Brain-skull interface: discovering the missing piece of head biomechanics. Overall objective of this project is to measure, mathematically describe and implement in software mechanical properties of brain-skull interface – a critical component of current large and sophisticated computational models of the brain and the last missing piece of brain biomechanics knowledge. This will allow increased reliability of comprehensive biomechanical models used to simulate realistic injury and surgery scena ....Brain-skull interface: discovering the missing piece of head biomechanics. Overall objective of this project is to measure, mathematically describe and implement in software mechanical properties of brain-skull interface – a critical component of current large and sophisticated computational models of the brain and the last missing piece of brain biomechanics knowledge. This will allow increased reliability of comprehensive biomechanical models used to simulate realistic injury and surgery scenarios.
The problem is significant and urgent. Every year in Australia, there are over 22,000 cases of traumatic brain injury, some of which could be prevented by better passive and active countermeasures; and over 12,000 neurosurgical procedures that surgical simulation could make more accurate and therefore safer.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101174
Funder
Australian Research Council
Funding Amount
$443,154.00
Summary
Harnessing life-course transitions to optimise time-use behaviour habits. At every stage of life, how we use our time is one of the greatest determinants of our happiness, productivity, social wellbeing and quality of life. Time-use habits, for better or worse, are entrenched in daily routines that are difficult to break. This project aims to use existing population datasets to identify when during their life people are most likely to change their time-use habits, and to describe who may be at g ....Harnessing life-course transitions to optimise time-use behaviour habits. At every stage of life, how we use our time is one of the greatest determinants of our happiness, productivity, social wellbeing and quality of life. Time-use habits, for better or worse, are entrenched in daily routines that are difficult to break. This project aims to use existing population datasets to identify when during their life people are most likely to change their time-use habits, and to describe who may be at greatest risk of making unfavourable changes (e.g., replacing physical activity with sedentary time, not getting enough sleep). Expected outcomes include new analytical methods to understand time-use routines and new knowledge to inform future time-use improvement strategies to enable Australians to live their best life.Read moreRead less
Data Complexity and Uncertainty-Resilient Deep Variational Learning. Enterprise data present increasingly significant characteristics and complexities, such as multi-aspect, heterogeneous and hierarchical features and interactions, and evolving dependencies and multi-distributions. They continue to significantly challenge the state-of-the-art probabilistic and neural learning systems with limited to insufficient capabilities and capacity. This research aims to develop a theory of flexible deep v ....Data Complexity and Uncertainty-Resilient Deep Variational Learning. Enterprise data present increasingly significant characteristics and complexities, such as multi-aspect, heterogeneous and hierarchical features and interactions, and evolving dependencies and multi-distributions. They continue to significantly challenge the state-of-the-art probabilistic and neural learning systems with limited to insufficient capabilities and capacity. This research aims to develop a theory of flexible deep variational learning transforming new deep probabilistic models with flexible variational neural mechanisms for analytically explainable, complexity-resilient analytics of real-life data. The outcomes are expected to fill important knowledge gaps and lift critical innovation competencies in wide domains.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240101049
Funder
Australian Research Council
Funding Amount
$432,485.00
Summary
Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumou ....Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumour, (2) novel models for the diffusion of an evolving rumour, and (3) techniques for detecting the diffusion sources of the original rumour and its mutations. This not only will constitute a major advancement in the theory and application of rumour study but also lead the decision-makers in debunking rumours.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100131
Funder
Australian Research Council
Funding Amount
$539,000.00
Summary
Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boo ....Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boost Australia’s pivotal research leadership and business competitiveness in nurturing new-generation, collaborative and transformative digital R&D and talent pipeline. It will enable large-scale strategic business innovation and transformation including smart manufacturing and Industry 4.0.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100422
Funder
Australian Research Council
Funding Amount
$386,637.00
Summary
Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field work ....Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field works to develop and validate a new feasible quantification method. This project will also advance knowledge on GHG emissions to guide quantification design. The outcomes will be translated into industry protocols and disseminated into industry. The outcomes provide timely support to water sector on its pathway to net-zero.Read moreRead less