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Research Topic : Ubiquitous Computing
Field of Research : Computer-Human Interaction
Australian State/Territory : ACT
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  • Funded Activity

    Discovery Projects - Grant ID: DP130101094

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Affective sensing technology for the detection and monitoring of depression and melancholia. This project will develop reliable and affective sensing technology and evaluate it as an objective measure of depressive disorders; a leading cause of disability worldwide. Outcomes will significantly support and aid clinicians in their diagnosis and treatment, thus providing a major breakthrough with significant research, healthcare and commercial possibilities.
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    Funded Activity

    Discovery Projects - Grant ID: DP160100601

    Funder
    Australian Research Council
    Funding Amount
    $299,031.00
    Summary
    Automated internet warnings to prevent viewing of minor-adult sex images. Since the advent of the internet and digital cameras, the market for child exploitation material (CEM) has boomed. This project aims to explore how the visual appearance of warning messages influences internet users. It plans to conduct a randomised controlled experiment with naïve participants on a real-life website to test the effectiveness of messages designed to discourage viewers of legal ‘barely legal’ pornography. I .... Automated internet warnings to prevent viewing of minor-adult sex images. Since the advent of the internet and digital cameras, the market for child exploitation material (CEM) has boomed. This project aims to explore how the visual appearance of warning messages influences internet users. It plans to conduct a randomised controlled experiment with naïve participants on a real-life website to test the effectiveness of messages designed to discourage viewers of legal ‘barely legal’ pornography. It is anticipated that results will assist policing efforts by indicating whether warnings can be used to dissuade first-time CEM viewers and whether differences exist between harm or deterrent-focused messages.
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    Active Funded Activity

    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190101294

    Funder
    Australian Research Council
    Funding Amount
    $380,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP160104195

    Funder
    Australian Research Council
    Funding Amount
    $315,000.00
    Summary
    Probabilistic modeling of human responses in complex interaction. The project aims to develop computational ability to reliably detect and hence act on implicit user preferences. It aims to develop techniques combining advanced non-intrusive sensor measures of conscious and non-conscious behaviour during interaction tasks to enable very high-level computerised support for human goal-seeking in complex data and design environments. It plans to use a user’s physiology and preference evaluation to .... Probabilistic modeling of human responses in complex interaction. The project aims to develop computational ability to reliably detect and hence act on implicit user preferences. It aims to develop techniques combining advanced non-intrusive sensor measures of conscious and non-conscious behaviour during interaction tasks to enable very high-level computerised support for human goal-seeking in complex data and design environments. It plans to use a user’s physiology and preference evaluation to capture their complex interaction with the data they view, probability models to accumulate information to identify their underlying preferences and extract relationships to find possible ‘hidden variables’ which may help explain and leverage the user's choices.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190102919

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use to .... Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use tools normally requiring extensive training in settings where the user can 'see' when they get something they like but do not know how to instruct a computer system to show or do it. Applications of the project will include visualisation for bespoke manufacturing or for high dimensional data, generating abstract art, or improving teleconferencing systems.
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