Algorithms for collaborative micro-navigation based on spatio-temporal data management and data mining. Traffic congestion coupled with greenhouse gas emissions is a major challenge for modern society. This project will tackle this challenge by developing computer-assisted smart vehicles that can access and exchange real-time information about traffic conditions, leading to improved driving experience, safety and environmental sustainability.
Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a sys ....Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing. Read moreRead less
Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques fo ....Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques for situation awareness in big media. We expect to develop a system to evaluate the proposed situation awareness framework. The outcomes of the project will benefit social media analysis and big data fields. It will also improve the government services by enabling the real time situation awareness in crisis.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
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assis ....Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assistants make recommendations that suit users’ needs accurately. It will benefit many service industry sectors of Australia by enabling virtual assistants to provide services proactively.Read moreRead less
Computational tools to analyse and exploit the social media revolution. We aim to create technologies to analyse social media communities, which are rapidly growing in reach, complexity, and content produced and shared. Powerful techniques to tap this resource will lead to commercial outcomes for marketing and search industries, alongside deeper insight into the cultural and social impact of this Internet revolution.
Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph ....Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph processing, pattern recognition in learning activities, learning performance assessment, and personalised study plan recommendations. The success of this project will significantly enhance the success of online education both in Australia and worldwide and; hence, will save time, money and resources for end users.Read moreRead less