Discovery Early Career Researcher Award - Grant ID: DE170100829
Funder
Australian Research Council
Funding Amount
$353,000.00
Summary
The effects of parental education on child health outcomes. This project aims to understand how public education policies can improve health. Common economic analysis of returns to education fails to capture the critical secondary beneficial effects of parental education on future generations’ health. These positive effects are systematically undercounted in the cost-benefit analysis of Australia’s investment in education. This project will use Australian datasets and natural experiments to iden ....The effects of parental education on child health outcomes. This project aims to understand how public education policies can improve health. Common economic analysis of returns to education fails to capture the critical secondary beneficial effects of parental education on future generations’ health. These positive effects are systematically undercounted in the cost-benefit analysis of Australia’s investment in education. This project will use Australian datasets and natural experiments to identify how parental education affects the health outcomes of the second generation. This project expects to provide policy recommendations to maximise health, wellbeing and economic outcomes for Australia.Read moreRead less
Mental health, job quality and workforce participation: evidence from population health research to address complex problems and conflicting policies. Mental disorders such as depression are a major cause of disability. Improving mental health can increase productivity and workforce participation. However, the psychosocial quality of work is a factor that overlays the relationship between work and health. Poor quality work (for example, unreasonable time pressure, insecurity) increases the risk ....Mental health, job quality and workforce participation: evidence from population health research to address complex problems and conflicting policies. Mental disorders such as depression are a major cause of disability. Improving mental health can increase productivity and workforce participation. However, the psychosocial quality of work is a factor that overlays the relationship between work and health. Poor quality work (for example, unreasonable time pressure, insecurity) increases the risk of poor mental health, absenteeism, and exit from the workforce. This project will analyse data following people over time to investigate the long-term health and employment consequences of poor psychosocial job quality, and consider the special case of mature age workers. It will identify those individuals at greatest risk, and factors that can buffer against the adverse effects of poor quality work.Read moreRead less
The impact of outdoor youth programs on positive adolescent development: an empirical evaluation. This project will seek to ensure that the nation's outdoor resources are fully utilised for the benefit of young people. Accordingly, this project will conduct the first comprehensive randomised controlled trial of a structured outdoor youth program in order to inform more strategic investment in outdoor programs to promote positive youth development.
Welfare receipt, demoralisation and mental health: how can welfare reform promote personal wellbeing and social inclusion? Welfare recipients are more likely to experience mental disorders and have poor wellbeing than non-recipients, and this can be a barrier to employment. This project examines the factors that may improve their mental health, promote employment outcomes, and help the Commonwealth Government develop effective welfare reform policies.
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less
Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in c ....Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in complex dynamic systems. The expected outcomes include an improved capacity for researchers, managers, and policy makers to understand complex organisational, economic, and health systems. This will provide immediate societal benefits by informing the development and deployment of targeted interventions in such systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101100
Funder
Australian Research Council
Funding Amount
$425,613.00
Summary
Towards Robotic Empathy: A human centred approach to future AI machines. The project aims to equip future robots with empathy by developing computational models which can leverage from verbal and non-verbal cues. With recent advances in artificial intelligence research, robots now have better cognitive and function skills, but they lack socio-emotional skills. Since these robots are expected to provide assistance to humans across different domains including rehabilitation, education and health c ....Towards Robotic Empathy: A human centred approach to future AI machines. The project aims to equip future robots with empathy by developing computational models which can leverage from verbal and non-verbal cues. With recent advances in artificial intelligence research, robots now have better cognitive and function skills, but they lack socio-emotional skills. Since these robots are expected to provide assistance to humans across different domains including rehabilitation, education and health care, empowering them with empathetic abilities is important for their success. The project will advance fundamental research in machine learning, affective computing and artificial intelligence to model human behavior, personality traits and emotions for an empathetic human-robot interaction.Read moreRead less
Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this i ....Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this issue through novel analyses of very subtle cues in facial and vocal expressions of affect embedded in a multimodal deep learning framework. Current approaches can successfully assist in binary classification tasks. This project will tackle the much more difficult problem of developing advanced affective sensing technology to simultaneously handle homogeneous and heterogeneous affect classes as well as continuous range estimates of affect intensity.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100128
Funder
Australian Research Council
Funding Amount
$395,000.00
Summary
Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts ....Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts research. This project is expected to advance our understanding of information processing in the brain by providing a mechanistic approach to functional integration.Read moreRead less