Androgen receptor: A master regulator of lipid metabolism. This project aims to understand how male sex hormones, or androgens, affect the amount and metabolism of fats in normal body tissues. By integrating our multi-disciplinary expertise in androgen action, molecular biology, metabolism and bioinformatics with novel techniques and instrumentation, this collaboration expects to generate the first detailed picture of how fat metabolism is controlled by androgens in humans, and how closely this ....Androgen receptor: A master regulator of lipid metabolism. This project aims to understand how male sex hormones, or androgens, affect the amount and metabolism of fats in normal body tissues. By integrating our multi-disciplinary expertise in androgen action, molecular biology, metabolism and bioinformatics with novel techniques and instrumentation, this collaboration expects to generate the first detailed picture of how fat metabolism is controlled by androgens in humans, and how closely this relates to mice. Expected outcomes and benefits will be a new understanding of which aspects of fat metabolism are most influenced by androgens, and an ability to anticipate potential metabolic impacts of natural or pharmacological fluctuations in androgen levels in humans, laboratory animals and livestock.Read moreRead less
Benchmarking the neurophysiology of human cortex models in vitro. This project aims to improve human brain models in vitro by developing an analytical tool benchmarking biophysical similarities to the adult human cortex. This project expects to generate new knowledge by testing for the first time the theory that integrating sensory-like inputs and awake/sleep-like cycles of electrical activity in vitro may complete the maturation of human brain organoid models. It will also generate new methods ....Benchmarking the neurophysiology of human cortex models in vitro. This project aims to improve human brain models in vitro by developing an analytical tool benchmarking biophysical similarities to the adult human cortex. This project expects to generate new knowledge by testing for the first time the theory that integrating sensory-like inputs and awake/sleep-like cycles of electrical activity in vitro may complete the maturation of human brain organoid models. It will also generate new methods to simplify the analysis of multimodal path-clamping data (Patch-seq). Expected outcomes will facilitate research collaboration and the reproducibility of accurate experimental replicates of the human brain. This will provide significant benefits in the global race to understand human brain computation mechanisms.Read moreRead less
Low-energy electro-photonics: novel materials, devices and systems. This project aims to develop low-power technologies for programming and tuning photonic integrated circuits (PICs). By replacing thermal tuning, the project will reduce power consumption from watts to milliwatts, which also eliminates the thermal crosstalk that limits the complexity of today's PICs. The expected outcome will be the basis for a generic field-programmable photonic chip, which can be used to rapidly prototype desig ....Low-energy electro-photonics: novel materials, devices and systems. This project aims to develop low-power technologies for programming and tuning photonic integrated circuits (PICs). By replacing thermal tuning, the project will reduce power consumption from watts to milliwatts, which also eliminates the thermal crosstalk that limits the complexity of today's PICs. The expected outcome will be the basis for a generic field-programmable photonic chip, which can be used to rapidly prototype designs for production as full custom chips as part of a new Australian industry capability. The expected benefits will be a faster innovation cycle, greater adoption of photonic technologies, and support of research into, for example, neuromorphic optical processing, and advanced communications and sensing systems.Read moreRead less
Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high ....Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.Read moreRead less
Evolutionary diversity optimisation. This project aims to build up and establish the area of evolutionary diversity optimisation. The project will cover the design and application of evolutionary diversity optimisation methods to complex problems of significance and high national economic benefit and build up the theoretical foundations of these methods. The project is expected benefit decision makers by providing them a diverse set of high quality alternatives to choose from. This project will ....Evolutionary diversity optimisation. This project aims to build up and establish the area of evolutionary diversity optimisation. The project will cover the design and application of evolutionary diversity optimisation methods to complex problems of significance and high national economic benefit and build up the theoretical foundations of these methods. The project is expected benefit decision makers by providing them a diverse set of high quality alternatives to choose from. This project will allow them to make highly informed decisions and lead to more reliable solutions for optimisation problems, in areas of high economic impact such as manufacturing and supply chain management.Read moreRead less
Organic Bionics: Soft Materials to Solve Hard Problems in Neuroengineering. This project aims to combine innovations in organic conductors, nanotechnology, 3D biofabrication and neuroengineering to develop a bioelectronic system capable of wireless neuromodulation with unprecedented stability and precision. This project expects to generate new knowledge regarding the properties of materials that promote optical neuromodulation and new strategies to obtain long-term material stability in biologic ....Organic Bionics: Soft Materials to Solve Hard Problems in Neuroengineering. This project aims to combine innovations in organic conductors, nanotechnology, 3D biofabrication and neuroengineering to develop a bioelectronic system capable of wireless neuromodulation with unprecedented stability and precision. This project expects to generate new knowledge regarding the properties of materials that promote optical neuromodulation and new strategies to obtain long-term material stability in biological environments. The expected outcome is to generate new material design rules to facilitate wireless neuromodulation technologies in biomedical engineering. The project will position Australia as a leader in bionic devices by creating a new 3D bioprinting hub for low-cost fabrication of bioelectronic systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Next generation photonic waveguide sensors enabled by machine learning. This project aims to establish the next frontier in photonic waveguide sensing, by using machine learning to shift the complexity out of conventional photonic-waveguide/optical-fibre sensors and into smart detection algorithms. The complexity and instability of multimode photonic waveguides, traditionally a hinderance to sensing, will be advantageously employed to train deep learning models for sensing. Expected outcomes inc ....Next generation photonic waveguide sensors enabled by machine learning. This project aims to establish the next frontier in photonic waveguide sensing, by using machine learning to shift the complexity out of conventional photonic-waveguide/optical-fibre sensors and into smart detection algorithms. The complexity and instability of multimode photonic waveguides, traditionally a hinderance to sensing, will be advantageously employed to train deep learning models for sensing. Expected outcomes include the creation of intelligent photonic sensors that can, in principle, measure any environmental parameter using any optical waveguide material. It will create new critically needed measurement capabilities for challenging harsh environments, such as extreme temperature and in-vivo biochemical sensing.Read moreRead less
Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation syste ....Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation systems and novel approaches to continuous collaborative learning from multi-spectral media. In addition to the emerging partnership between participants, the project will advance sovereign capability to develop maritime intelligence gathering technology for the Royal Australian Navy to underpin stability in our region. Read moreRead less
Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart g ....Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart grids and optimal charging and discharging tasks in a large network of electric vehicles, helping Australian power industry improve efficiency and security, as well as training the next generation scientists and engineers for Australia in this emerging field.Read moreRead less