Discovery Early Career Researcher Award - Grant ID: DE190101151
Funder
Australian Research Council
Funding Amount
$398,000.00
Summary
Designing augmented eating interfaces to promote mindful eating. This project aims to develop and test novel augmented eating interfaces in order to address the contradiction between the concept of mindful eating (no distractions) and the reality of screen cultures (eating with screens). Eating while watching screens can be problematic because it can cause overeating, which can manifest into bigger health concerns such as obesity and heart disease. This project expects to generate new knowledge ....Designing augmented eating interfaces to promote mindful eating. This project aims to develop and test novel augmented eating interfaces in order to address the contradiction between the concept of mindful eating (no distractions) and the reality of screen cultures (eating with screens). Eating while watching screens can be problematic because it can cause overeating, which can manifest into bigger health concerns such as obesity and heart disease. This project expects to generate new knowledge in the field of human-food interaction. It presents two new augmented eating systems and a socio-technological study of these systems in use within Australian households. The expected outcomes include a framework on how to design interactive systems that encourage mindful eating without compromising the pleasures of screen-based media and the eating experience, and a greater theoretical understanding of how to support mindful eating in everyday practice.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100160
Funder
Australian Research Council
Funding Amount
$423,000.00
Summary
Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expe ....Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expected outcomes include a set of collective, contextualised, and temporal-aware algorithms for information extraction and integration, built on top of effective indexing and in-parallel processing. This project is anticipated to benefit a considerable number of data-driven intelligence-based applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120100776
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Designing process models to support communication and decision-making. This project will develop guidelines to assist analysts in describing business processes by identifying theoretical factors of process model quality. The outcomes will make it easier to make informed decisions about process re-design, business innovation or software development, thus contributing to project cost savings and better processes.
Discovery Early Career Researcher Award - Grant ID: DE130101002
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Efficiently querying uncertain spatial space. Location-based services are becoming increasingly popular due to exponentially increased usage of smartphones and cheap wireless network. This project aims to provide efficient solutions for various location-based queries applicable to different travelling domains such as road networks, Euclidean space with obstacles and indoor space.
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
Discovery Early Career Researcher Award - Grant ID: DE120102144
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Continuously monitoring uncertain objects in a multi-dimensional space. The project aims to develop novel, advanced techniques to continuously monitor uncertain objects. The success of the project not only brings breakthroughs in technology development but also provides training for high quality personnel in this important and growing area, and brings considerable economic and social benefits to Australia.
Discovery Early Career Researcher Award - Grant ID: DE130101061
Funder
Australian Research Council
Funding Amount
$373,697.00
Summary
Personal safety in the city: design solutions for after dark. The research will provide insights into the potential for mobile technology to be designed to enhance personal safety in urban environments at night. It will do so by identifying individual personal harm reduction and safety strategies, and examining the opportunities to use technology to amplify these strategies.
Discovery Early Career Researcher Award - Grant ID: DE180100315
Funder
Australian Research Council
Funding Amount
$368,446.00
Summary
Social attentive user interfaces for the age of interruption. This proposal aims to enable the development of social attentive user interfaces—those that employ sensors such as eye trackers and thermal cameras to monitor the locus and level of users' attention and adapt their behaviour accordingly. The project lies in the field of Human-Computer Interaction, drawing from machine learning methods to design novel user experiences. Expected outcomes include insights into how people manage their att ....Social attentive user interfaces for the age of interruption. This proposal aims to enable the development of social attentive user interfaces—those that employ sensors such as eye trackers and thermal cameras to monitor the locus and level of users' attention and adapt their behaviour accordingly. The project lies in the field of Human-Computer Interaction, drawing from machine learning methods to design novel user experiences. Expected outcomes include insights into how people manage their attention, new methods for attention estimation and classification, and novel systems for e-learning and work productivity that demonstrate these new capabilities. As a result, this project will provide the benefit of enabling system to no longer be blind to users’ attentional, social, and cognitive contexts.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100679
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and effic ....Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and efficiently support a set of primitive queries including rank-based queries, dominance-based queries and proximity-based queries. The results of this project will be an important complement to the development of data stream systems and will bring considerable social, economic and technological benefits to Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less