Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Modelling and simulation of self-organised behaviour in biological and bio-inspired systems. Understanding self-organised systems is fundamental in biology and bio-inspired engineering. The project develops sophisticated mathematical modelling techniques and high performance simulation methods for such systems. This will increase our capacity to explain complex biological behaviour and to produce reliable bio-inspired engineering solutions
An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through th ....An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of pioneering natural language processing components and novel custom-made machine-readable knowledge bases. The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.Read moreRead less
Subject-specific computational models for accurate evaluation of muscle function in human locomotion. The purpose of this project is to advance current understanding of muscle function during human locomotion. The most significant outcome will be the development of novel computational tools that can play a pivotal role in the healthcare industry through the prevention, diagnosis and treatment of movement disorders.
Large-scale computational modelling of epidemics in Australia. The project aims to develop novel computational epidemiological models to contribute to guidelines for optimal prophylaxis, vaccination and case management. Emerging threats posed by infectious diseases and bioterrorism could have dramatic effects on the Australian population, productivity and economy. The project aims to improve the accuracy and scope of modern computational epidemiological models by integrating large-scale Census d ....Large-scale computational modelling of epidemics in Australia. The project aims to develop novel computational epidemiological models to contribute to guidelines for optimal prophylaxis, vaccination and case management. Emerging threats posed by infectious diseases and bioterrorism could have dramatic effects on the Australian population, productivity and economy. The project aims to improve the accuracy and scope of modern computational epidemiological models by integrating large-scale Census datasets and explicitly simulating the entire population down to the level of single individuals, coupled with complex network-based and information flow analysis. The intended outcomes include a more precise and efficient forecasting of critical epidemic dynamics, and increased effectiveness of prevention, mitigation and management of socio-economic, socio-ecological and national security crises.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101549
Funder
Australian Research Council
Funding Amount
$395,775.00
Summary
A virtual platform for animal–human inhalation toxicity extrapolation. This project aims to remove the long-lasting barrier in extrapolating data from animals to humans by developing an integrated virtual platform. This project expects to fully resolve inhalation exposure differences in nasal airways between commonly used animal surrogates and humans, which could lay scientific underpinnings in developing rigorous interspecies data conversion schemes. Expected outcomes include a versatile inhala ....A virtual platform for animal–human inhalation toxicity extrapolation. This project aims to remove the long-lasting barrier in extrapolating data from animals to humans by developing an integrated virtual platform. This project expects to fully resolve inhalation exposure differences in nasal airways between commonly used animal surrogates and humans, which could lay scientific underpinnings in developing rigorous interspecies data conversion schemes. Expected outcomes include a versatile inhalation exposure risk assessment tool that can be implemented for any airway compartment, enhanced reliability of animal tests, reduced number of animals for testing. This should provide significant benefits in improving occupational health and safety and promoting National/International regulatory changes. Read moreRead less
Integration of high-speed dynamic x-ray imaging and patient-specific computational modelling for non-invasive assessment of knee-joint function. The project will establish a new capability for the prevention and treatment of osteoarthritis (joint disease) that will place Australia at the forefront of biomedical engineering research internationally. The ability to integrate high-speed, mobile, x-ray imaging of joint motion with patient-specific computer modelling is unique globally.
Industrial Transformation Research Hubs - Grant ID: IH210100051
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models th ....The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models that can predict and optimise manufacturing processes, resulting in greater yields, faster and more flexible processes and enhanced product stability. The Hub will transform biopharmaceutical manufacturing and unlock growth opportunities to forge an internationally competitive Australian Biopharma sector.Read moreRead less
Uncertainty quantification using type-2 fuzzy systems. This project will develop new interval type-2 fuzzy logic system-based tools for quantifying uncertainties present in complex systems. The outcome of this project will greatly help all Australian industries and organisations that directly or indirectly use model-based estimation for prediction and forecasting purposes.