Multiobjective Memetic Algorithms for Multi-task Symbolic Regression. This project aims at developing the new generation of symbolic regression methods using a yet unexplored way to represent mathematical functions. We will use memetic algorithms to create mathematical models for symbolic regression. Our memetic computing approach will be data-driven and will use multi-objective optimization and multi-task evolutionary computation for symbolic regression, addressing a core need of many areas of ....Multiobjective Memetic Algorithms for Multi-task Symbolic Regression. This project aims at developing the new generation of symbolic regression methods using a yet unexplored way to represent mathematical functions. We will use memetic algorithms to create mathematical models for symbolic regression. Our memetic computing approach will be data-driven and will use multi-objective optimization and multi-task evolutionary computation for symbolic regression, addressing a core need of many areas of science and technology. A large number of datasets will be investigated to benchmark the new methods. The expected outcomes will help support our national priorities with new data analytic capabilities. With a strong and interdisciplinary team in three continents, the project will attract international collaboration. Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC170100030
Funder
Australian Research Council
Funding Amount
$4,133,659.00
Summary
ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students ....ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students and postdoctoral researchers. These researchers will lead the medical technology industry into a new era of data-driven personalised and precision medical devices and applications. The Centre will result in the development of capabilities in the core technologies of machine learning and the practical application of cognitive computing in the area of health.Read moreRead less
Immersive analytics: interactive data analysis using surfaces and spaces. This project aims to explore the potential for new immersive display and interaction technologies to greatly enhance the field of visual data analytics. Humans struggle to understand the masses of complex data they now accumulate. Visual data analytics offers a solution. The project expects to provide practical and theoretical frameworks for immersive data analysis and valuable intellectual property on the first practical ....Immersive analytics: interactive data analysis using surfaces and spaces. This project aims to explore the potential for new immersive display and interaction technologies to greatly enhance the field of visual data analytics. Humans struggle to understand the masses of complex data they now accumulate. Visual data analytics offers a solution. The project expects to provide practical and theoretical frameworks for immersive data analysis and valuable intellectual property on the first practical tools for immersive data analytics. This will provide significant benefits, such as allowing those across government and industry to make more informed decisions from data.Read moreRead less
Active Visual Navigation in an Unexplored Environment. This project will develop a new method for robotic navigation in which goals can be specified at a much higher level of abstraction than has previously been possible. This will be achieved using deep learning to make informed predictions about a scene layout, and navigating as an active observer in which the predictions informs actions. The outcome will be robotic agents capable of effective and efficient navigation and operation in previous ....Active Visual Navigation in an Unexplored Environment. This project will develop a new method for robotic navigation in which goals can be specified at a much higher level of abstraction than has previously been possible. This will be achieved using deep learning to make informed predictions about a scene layout, and navigating as an active observer in which the predictions informs actions. The outcome will be robotic agents capable of effective and efficient navigation and operation in previously unseen environments, and the ability to control such agents with more human-like instructions. Such capabilities are desirable, and in some cases essential, for autonomous robots in a variety of important application areas including automated warehousing and high-level control of autonomous vehicles. 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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100137
Funder
Australian Research Council
Funding Amount
$881,758.00
Summary
Australian Environmental Specimen Bank: advancing specimen bank capability. The aim of this LIEF is to advance Australia’s specimen banking capabilities through a new, enhanced national facility, the Australian Environmental Specimen Bank (AESB). The AESB would be founded on a unique current archive of human and environmental samples established by the partners to the LIEF. Importantly, the AESB would be managed as a nationally available (to all public sector researchers), operationally self-fun ....Australian Environmental Specimen Bank: advancing specimen bank capability. The aim of this LIEF is to advance Australia’s specimen banking capabilities through a new, enhanced national facility, the Australian Environmental Specimen Bank (AESB). The AESB would be founded on a unique current archive of human and environmental samples established by the partners to the LIEF. Importantly, the AESB would be managed as a nationally available (to all public sector researchers), operationally self-funded resource for integrated exposure research into the future. The archive is expected to support longitudinal and cross-sectional studies to assess trends in exposure to chemical and biological hazards in the Australian population, identify emerging hazards, and provide a scientific basis for policy and regulatory actions.Read moreRead less
Estimating use of tobacco and nicotine products through wastewater analysis. This project aims to equip the Australian public health and security sector with a tool to accurately measure tobacco consumption in the general population. Specific human biomarkers in urine will be identified using non-target approaches and their pharmacokinetics quantified. The new data will address critical gaps in our knowledge on the population-level excretion of biomarkers for the consumption of tobacco and alter ....Estimating use of tobacco and nicotine products through wastewater analysis. This project aims to equip the Australian public health and security sector with a tool to accurately measure tobacco consumption in the general population. Specific human biomarkers in urine will be identified using non-target approaches and their pharmacokinetics quantified. The new data will address critical gaps in our knowledge on the population-level excretion of biomarkers for the consumption of tobacco and alternative nicotine products. The outcomes of this project will provide reliable, cost-effective estimates of tobacco consumption for use with wastewater-based epidemiology assessments. This will enable changes in tobacco use to be accurately evaluated for the first time and improve the efficacy of tobacco control measures.Read moreRead less
Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Paramet ....Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Parametric VR, a system of VR tools to support parametric design. Key outcomes include software tools and demonstrators to support parametric algorithms and processes in VR. This will have significant benefits for design industries, allowing designers to directly edit parametric design entirely in VR across the project lifecycle.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