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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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and deployment of these models into automation scenarios. We seek to develop a human-centred AI solution, a suite of visual tools for integrating and understanding various AI techniques in application
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Immersive Visualization of Protein Structures in Food Science Using VR/AR Primary supervisor Wai Peng
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software tasks (bug fixing, refactoring, unit test creation) for empirical evaluation. Measure human-AI collaboration efficiency. Investigate Trust and Explainability Explore how developers interact with
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. "Automatic generation of grounded visual questions." in IJCAI, pages 4235--4243, 2017. E. Andre and C. Pelachaud. Interacting with embodied conversational agents. In F. Chen and K. Jokinen, editors, Speech
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. The project utilises social-visual stimuli (social videos of people interactions), and aims to detect socio-cognitive disorders early in preterm infants. The program will focus on correlations between
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, there remains a lack of fundamental human-computer interaction research and usability design principles to realise practical and effective applications, particularly concerning how data visual analytics
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ecosystem interactions. If used wisely for decision-support, these technologies can help select and implement effective policies. This PhD project, jointly offered by Monash University (Australia) and