Cross-Entropy Methods in Complex Biological Systems. The Cross-Entropy method provides a powerful new way to find superior solutions to complicated optimisation problems in biology, ranging from better design and implementation of medical treatments to an increased understanding of complex ecosystems.
Biotransformation and biodegradation of organic nitrogen compounds from wastewater in bio-electrochemical systems. The rapid emergence of water recycling in Australia requires more vigilant control of pollutants that are discharged to sewers. This project will develop a novel, cost-effective process to remove organic nitrogen compounds (and likely other organics) present in many industrial wastewaters. It could provide an excellent solution for the pre-treatment of such industrial wastewaters at ....Biotransformation and biodegradation of organic nitrogen compounds from wastewater in bio-electrochemical systems. The rapid emergence of water recycling in Australia requires more vigilant control of pollutants that are discharged to sewers. This project will develop a novel, cost-effective process to remove organic nitrogen compounds (and likely other organics) present in many industrial wastewaters. It could provide an excellent solution for the pre-treatment of such industrial wastewaters at the source without any chemical addition, hence reducing the challenge and risks facing the water recycling plants. This innovative technology will further expand the growing research capacity and know-how in water recycling in Australia.Read moreRead less
Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelec ....Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelectric sensor technology. Expected outcomes include manufactured proof-of-concept sensors that enable measurement of local stress fields. This should provide significant benefits, such as improved future robot capability and reliability, and research training for next-generation Australian computational mathematicians. Read moreRead less
Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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Porous beta-titanium bone implants optimised for strength and bio-compatibility: design and fabrication. The project aims to develop the scaffold-design and manufacturing techniques that will underpin the next generation of bone implants. The scaffolds will be specifically designed to match the key biomechanical properties of bone, and fabricated from novel titanium alloys using the latest generation of advanced manufacturing technologies.
Unlocking the potential for linear and discrete optimisation in knot theory and computational topology. Computational topology is a young, energetic field that uses computers to solve complex geometric problems, such as whether a loop of string is tangled. Such computations are becoming increasingly important in mathematics, and applications span biology, physics and information sciences, however many core problems in the field remain intractable for all but the simplest cases. This project unit ....Unlocking the potential for linear and discrete optimisation in knot theory and computational topology. Computational topology is a young, energetic field that uses computers to solve complex geometric problems, such as whether a loop of string is tangled. Such computations are becoming increasingly important in mathematics, and applications span biology, physics and information sciences, however many core problems in the field remain intractable for all but the simplest cases. This project unites geometric techniques with powerful methods from operations research, such as linear and discrete optimisation, to build fast, powerful tools that can for the first time systematically solve large topological problems. Theoretically, this project has significant impact on the famous open problem of detecting knottedness in fast polynomial time.Read moreRead less
Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computatio ....Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computational advances in both areas in recent years. The research will stimulate the design of microscopic and macroscopic complex spatial structures with superior properties, such as composite materials, solar cells, telecommunication networks, mining operations, and road systems.Read moreRead less
Sustainable Mathematical Foundations: STEM-enriched Modelling . This longitudinal project aims to generate new knowledge on how sustainable, innovative mathematics learning can be fostered through STEM-enriched mathematical modelling across the early grades. Featuring interdisciplinary processes, including engineering and science, novel modelling sequences will prompt children to adapt their existing ways of mathematical thinking to develop conceptual innovations in solving future-oriented pr ....Sustainable Mathematical Foundations: STEM-enriched Modelling . This longitudinal project aims to generate new knowledge on how sustainable, innovative mathematics learning can be fostered through STEM-enriched mathematical modelling across the early grades. Featuring interdisciplinary processes, including engineering and science, novel modelling sequences will prompt children to adapt their existing ways of mathematical thinking to develop conceptual innovations in solving future-oriented problems. New theoretical and empirical frameworks are expected to transform our outmoded problem experiences to ones that challenge all children to reach their mathematical potential. Professional learning, informed by international collaboration, is expected to transcend existing teacher development modes.Read moreRead less
Using mathematics to solve real world problems. This project aims to identify, apply and refine teaching approaches that help secondary students learn mathematical modelling, using mathematics to solve real world problems. The study will investigate the mathematical, cognitive, social and environmental factors that "enable" Year 10/11 students to develop mathematical representations of a real world problem. This project expects to generate theoretical and practical insights into how these enable ....Using mathematics to solve real world problems. This project aims to identify, apply and refine teaching approaches that help secondary students learn mathematical modelling, using mathematics to solve real world problems. The study will investigate the mathematical, cognitive, social and environmental factors that "enable" Year 10/11 students to develop mathematical representations of a real world problem. This project expects to generate theoretical and practical insights into how these enablers promote successful modelling, tasks that support students' development as modellers, and effective teaching approaches that promote student capability and interest in mathematics.Read moreRead less
Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the imp ....Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the important mathematical and statistical literacies needed for lifting student achievements. In advancing both theory and practice, the project aims to contribute to knowledge of primary students' capabilities for STEM problem solving and ways of enhancing implementation of the Australian Curriculum.Read moreRead less