Industrial Transformation Training Centres - Grant ID: IC170100016
Funder
Australian Research Council
Funding Amount
$3,123,492.00
Summary
ARC Training Centre for Personalised Therapeutics Technologies. The ARC Training Centre for Personalised Therapeutics Technologies aims to create and develop the skills and technology to benefit from the transformative impacts that cell/organ-on-a-chip technology will have on the medtech/pharma industries. By combining microfluidics-based/real-time technologies with personalised medicine the Training Centre will provide industry growth opportunities through improved screening of potential therap ....ARC Training Centre for Personalised Therapeutics Technologies. The ARC Training Centre for Personalised Therapeutics Technologies aims to create and develop the skills and technology to benefit from the transformative impacts that cell/organ-on-a-chip technology will have on the medtech/pharma industries. By combining microfluidics-based/real-time technologies with personalised medicine the Training Centre will provide industry growth opportunities through improved screening of potential therapeutics. The use of an individual patient’s cellular and molecular research findings will ultimately enable personalised diagnostic and therapeutic decisions.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100026
Funder
Australian Research Council
Funding Amount
$4,969,663.00
Summary
ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway an ....ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway and barriers faced by the sector, namely improving process efficiencies, enabling early-stage scale-up (cell/tissue) and development of the sector's supply chain. The knowledge created and research undertaken would help to accelerate commercialisation in regenerative medicine, tissue engineering and cell therapies.Read moreRead less
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
Democratisation of Deep Learning: Neural Architecture Search at Low Cost. The need to manually design Deep Learning-based Neural Networks (DNNs) limits their usage to AI experts and hinders the exploitation of their true potential more broadly, e.g., in farming, humanities. We aim to replace this tedious process through novel AI methods capable of generating DNNs that can perform significantly better and at a lower computational cost than manually designed DNNs. We further expand this idea to so ....Democratisation of Deep Learning: Neural Architecture Search at Low Cost. The need to manually design Deep Learning-based Neural Networks (DNNs) limits their usage to AI experts and hinders the exploitation of their true potential more broadly, e.g., in farming, humanities. We aim to replace this tedious process through novel AI methods capable of generating DNNs that can perform significantly better and at a lower computational cost than manually designed DNNs. We further expand this idea to solve complex real-world problems with both labelled and unlabelled data found in various applications including energy and climate change. The expected outcomes include the novel AI methods, highly trained AI researchers and a number of critical applications that will bring significant benefits to Australia and the world.Read moreRead less
Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, commun ....Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, community the ability to contribute to growing our knowledge-based society in a safe, transparent and trustworthy manner. Outcomes will include innovative instruments to teach machines, novel knowledge creation, trusted and transparent AI systems, and a new generation of human teachers specialised in educating AI systems.Read moreRead less
Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental ....Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental policy formulation, network design, engineering, defence and cybersecurity; offering significant benefits to the researchers and practitioners in these fields. In addition to research outputs, it will strengthen international collaboration and build research capacity to put Australia at the forefront of this research.
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Discovery Early Career Researcher Award - Grant ID: DE240101129
Funder
Australian Research Council
Funding Amount
$442,000.00
Summary
Synergy between future 21-cm experiments and physical cosmology. The nature of dark matter and formation of the first galaxies are both unsolved mysteries. During the first 500 million years, our universe was filled with hydrogen atoms illuminated by the first galaxies. The 21-cm radiation from this gas encodes properties of unseen galaxies and dark matter during this so-called cosmic dawn. This project aims to build an innovative framework to leverage future 21-cm experiments using The Square K ....Synergy between future 21-cm experiments and physical cosmology. The nature of dark matter and formation of the first galaxies are both unsolved mysteries. During the first 500 million years, our universe was filled with hydrogen atoms illuminated by the first galaxies. The 21-cm radiation from this gas encodes properties of unseen galaxies and dark matter during this so-called cosmic dawn. This project aims to build an innovative framework to leverage future 21-cm experiments using The Square Kilometre Array to observe cosmic dawn, and to forecast the optimal constraints on dark matter physics. Additional outcomes include the largest cosmological simulation of the first galaxies powered by neural networks and improved knowledge of their properties using Bayes' theorem and The James Webb Space Telescope.Read moreRead less
Engineering stable, efficient perovskite solar cells. This project aims to address and resolve a critical issue facing perovskite solar cells which have enormous potential as a future technology for the large-scale generation of cheap, clean electricity: their instability under actual operating conditions. The project is expected to make significant fundamental advances in compositional, structural and interface engineering. This project will benefit the environment by paving the way for the wi ....Engineering stable, efficient perovskite solar cells. This project aims to address and resolve a critical issue facing perovskite solar cells which have enormous potential as a future technology for the large-scale generation of cheap, clean electricity: their instability under actual operating conditions. The project is expected to make significant fundamental advances in compositional, structural and interface engineering. This project will benefit the environment by paving the way for the widespread adoption of cheaper and more efficient solar cells.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
A novel and efficient approach for optimisation involving iterative solvers. Computationally expensive simulations involving iterative solvers are increasingly being used in industry to assess performance of products and processes. Repeated use of such simulations is necessary to identify optimum solutions. Even with today's computing power, many such tasks remain computationally prohibitive. This project presents a novel approach to solve optimisation problems involving iterative solvers with l ....A novel and efficient approach for optimisation involving iterative solvers. Computationally expensive simulations involving iterative solvers are increasingly being used in industry to assess performance of products and processes. Repeated use of such simulations is necessary to identify optimum solutions. Even with today's computing power, many such tasks remain computationally prohibitive. This project presents a novel approach to solve optimisation problems involving iterative solvers with limited computing budget. A wide range of industries involved in product and process design would gain a significant competitive advantage from this unique technical innovation. In addition, this technology will be invaluable to uncover and understand complex natural phenomena.Read moreRead less