Mathematical Decision Support to Optimise Hospital Capacity and Utilisation. Hospital planners and executives regularly contend with challenging capacity related decisions. Decisions relating to prioritisation, allocation and sharing of resources have a profound impact on productivity, efficiency and patient outcomes. There is a lack of data-driven or quantitative decision support to make well-informed capacity related decisions of a strategic or tactical nature in a single hospital, or across a ....Mathematical Decision Support to Optimise Hospital Capacity and Utilisation. Hospital planners and executives regularly contend with challenging capacity related decisions. Decisions relating to prioritisation, allocation and sharing of resources have a profound impact on productivity, efficiency and patient outcomes. There is a lack of data-driven or quantitative decision support to make well-informed capacity related decisions of a strategic or tactical nature in a single hospital, or across a regional healthcare system. This project aims to deliver decision support for holistic hospital capacity assessment and planning optimisation. This will yield significant benefits for the health sector, providing a tool to optimise the allocation of resources and provision of infrastructure for regional hospital services.Read moreRead less
Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analyti ....Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analytical and numerical methods for optimal control in such scenarios. These methods will have application to fishery management, communication networks, power systems and social resource allocation scenarios.Read moreRead less
Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and ....Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and accelerating growth, imply that application of methods developed through this project may save billions of dollars and, more importantly, thousands of lives. An expected outcome of this project will be superior theoretical and practical methods for analysing productivity and efficiency of economic systems, to enhance understanding of the potential for improvements and of the necessary reforms.Read moreRead less
Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project ....Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project aims to provide theoretically sound frameworks for solving large Markov decision processes, and exploit them to solve important combinatorial optimisation problems. This timely project can promote Australia's position in the development of such novel frameworks for many scientific and industrial applications.Read moreRead less
Borderline Personality as Social Phenomena. Mental disorders attract social stigma and those diagnosed are widely misunderstood. This project aims to collect and analyse accounts of people living with Borderline Personality Disorder (BPD) - mainly women - and perspectives of social support practitioners. The intended outcome is to provide a sophisticated understanding of BPD as a social phenomenon, develop sociological evidence based on lived experiences and generate Australian digital resources ....Borderline Personality as Social Phenomena. Mental disorders attract social stigma and those diagnosed are widely misunderstood. This project aims to collect and analyse accounts of people living with Borderline Personality Disorder (BPD) - mainly women - and perspectives of social support practitioners. The intended outcome is to provide a sophisticated understanding of BPD as a social phenomenon, develop sociological evidence based on lived experiences and generate Australian digital resources including narratives of BPD, creative outputs and practitioner perspectives. The anticipated goal of this project is to inform policy and community responses addressing stigma and marginalisation, and the improvement of social support for those affected by BPD.Read moreRead less
Pathways to agri-food supply chains that co-benefit people and nature. This project aims to improve biodiversity outcomes of agricultural food production and consumption, and expects to generate new knowledge about impacts of interventions and shocks on the environment, human health and livelihoods in agri-food systems. This will be achieved using an interdisciplinary approach that accounts for uncertainties in links between farmers, suppliers, consumers and supply-chain outcomes. The expected o ....Pathways to agri-food supply chains that co-benefit people and nature. This project aims to improve biodiversity outcomes of agricultural food production and consumption, and expects to generate new knowledge about impacts of interventions and shocks on the environment, human health and livelihoods in agri-food systems. This will be achieved using an interdisciplinary approach that accounts for uncertainties in links between farmers, suppliers, consumers and supply-chain outcomes. The expected outcome is a value of information framework for identifying nature-friendly policies and actions with co-benefits for human well-being. Benefits include sustainability pathways with win-win outcomes for people and nature, and improved ways of meeting international commitments such as Sustainable Development Goals.Read moreRead less
Optimal Fundraising Design in a Competitive Market: A Unifying Framework. Increased competition from over 57,000 registered charities and a recent 6% decrease in individual donations, have increased the need for charities to improve their fundraising strategies. This project aims to develop a comprehensive framework – based on theories from marketing, psychology, economics, sociology, and philanthropy— and develop novel methodologies to determine effective charitable fundraising strategies in ....Optimal Fundraising Design in a Competitive Market: A Unifying Framework. Increased competition from over 57,000 registered charities and a recent 6% decrease in individual donations, have increased the need for charities to improve their fundraising strategies. This project aims to develop a comprehensive framework – based on theories from marketing, psychology, economics, sociology, and philanthropy— and develop novel methodologies to determine effective charitable fundraising strategies in a competitive marketplace. Key outcomes will include the theoretical model, and tests using conjoint choice-experiments, controlled field experiments and 10 years of giving data from 4 million Australian donors. These outcomes will enhance fundraising practice, ensuring charities can better serve the Australian public.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101791
Funder
Australian Research Council
Funding Amount
$427,082.00
Summary
Mathematically optimal R&D for coral reef conservation. This project aims to develop mathematical methodologies for optimising Research & Development (R&D) of technologies that will secure complex and uncertain ecosystems into the future. Current conventional management approaches will not prevent the degradation of threatened ecosystems like the Great Barrier Reef, so new technologies are needed. The biggest challenge in choosing these technologies is the long delay between development and depl ....Mathematically optimal R&D for coral reef conservation. This project aims to develop mathematical methodologies for optimising Research & Development (R&D) of technologies that will secure complex and uncertain ecosystems into the future. Current conventional management approaches will not prevent the degradation of threatened ecosystems like the Great Barrier Reef, so new technologies are needed. The biggest challenge in choosing these technologies is the long delay between development and deployment, in which time ecosystem function may collapse and complex, dynamic ecological and social systems will change. The mathematical methods and theory developed will inform a Great Barrier Reef case study, and will be ready for rapid application to other ecosystems as the urgent need arises.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC200100022
Funder
Australian Research Council
Funding Amount
$4,883,406.00
Summary
ARC Training Centre for Information Resilience. The proposed centre aims at building workforce capacity in Australian organisations to create, protect and sustain agile data pipelines, capable of detecting and responding to failures and risks across the information value chain in which the data is sourced, shared, transformed, analysed and consumed. Building on strong foundations of responsible data science, the centre will bring together end-users, technology providers, and cutting-edge researc ....ARC Training Centre for Information Resilience. The proposed centre aims at building workforce capacity in Australian organisations to create, protect and sustain agile data pipelines, capable of detecting and responding to failures and risks across the information value chain in which the data is sourced, shared, transformed, analysed and consumed. Building on strong foundations of responsible data science, the centre will bring together end-users, technology providers, and cutting-edge research, to lift the socio-technical barriers to data driven transformation and develop resilient data pipelines capable of delivering game-changing productivity gains that position Australian organisations at the forefront of technology leadership and value creation from data assets. Read moreRead less
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less