What is successful public art today?: exploring how contemporary public art and memorial design shapes public engagement, perceptions and behaviour. Much public money is invested in public art and memorials. The research explores critical questions of value: what the public enjoys about such artworks, if and how artworks contribute amenity to public spaces, and whether recent artworks engage effectively with social memory, identity and politics. The research situates local practice within intern ....What is successful public art today?: exploring how contemporary public art and memorial design shapes public engagement, perceptions and behaviour. Much public money is invested in public art and memorials. The research explores critical questions of value: what the public enjoys about such artworks, if and how artworks contribute amenity to public spaces, and whether recent artworks engage effectively with social memory, identity and politics. The research situates local practice within international trends, to inform Australian designers, policymakers, art patrons and public space managers about recent innovations in technology, craft, creativity and critique, so they can create and choose public artworks and memorials which engage with the potentials of contemporary arts practice, the complexities of contemporary culture, and the diversity of social behaviour in public spaces.Read moreRead less
Cinematic Ethics: Exploring Ethical Experience through Film. This project develops a new interdisciplinary framework for understanding cinema’s unique power to evoke ethical experience via audiovisual means. Combining philosophy with film analysis, it moves beyond the prevalent view that cinema merely illustrates moral situations, and challenges the long-held suspicion toward film’s manipulative aesthetic power. This project proposes instead a model of cinematic ethics: an investigation of how c ....Cinematic Ethics: Exploring Ethical Experience through Film. This project develops a new interdisciplinary framework for understanding cinema’s unique power to evoke ethical experience via audiovisual means. Combining philosophy with film analysis, it moves beyond the prevalent view that cinema merely illustrates moral situations, and challenges the long-held suspicion toward film’s manipulative aesthetic power. This project proposes instead a model of cinematic ethics: an investigation of how cinema evokes ethical experience through emotional, cognitive, and aesthetic engagement. This project will advance the emerging interdisciplinary field of film-philosophy by highlighting film’s under-recognised potential to enhance ethical understanding, and thus to promote greater social awareness and intercultural communication.Read moreRead less
Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected ....Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected outcomes include new-generation theories and methods for the unsupervised learning of complex interactions in real-life big data, which are anticipated to enable the intrinsic processing of big data complexities and substantially enhance Australia’s leadership in frontier data science research and applications. Read moreRead less
Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi ....Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.Read moreRead less
The reformulation of war art as a dialogical interactive narrative. This research uses visualisation technology to explore new ways to communicate and understand the collective experience and personal memories of war. It aims to strengthen Australia's leadership in media arts, facilitating the active participation of defence personnel in the creation of a world-first interactive archive of war stories.
In Public / In Focus: Photography, Testimony and the Public Sphere. Photography plays an important but little understood role in the public sphere. Photographs invite viewers to identify with stories, events and others, and the ease with which photographs circulate in print and online makes them ideal for fostering discourse and debate. However, the increasing focus on testimony and witness in contemporary culture has recently altered the way that photography operates in public and raised some s ....In Public / In Focus: Photography, Testimony and the Public Sphere. Photography plays an important but little understood role in the public sphere. Photographs invite viewers to identify with stories, events and others, and the ease with which photographs circulate in print and online makes them ideal for fostering discourse and debate. However, the increasing focus on testimony and witness in contemporary culture has recently altered the way that photography operates in public and raised some significant problems for photography historians regarding the representation of events, others and the past. This project will respond to these problems, and produce a new understanding of the historical, social, cultural and political links between photography and the public sphere today.Read moreRead less
Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-s ....Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-supervised learning that are robust to failures and provide explainable decisions for object detection and scene segmentation. The outcomes are expected to advance theory in robust deep learning and benefit 3D mapping, surveying, infrastructure monitoring, transport and robotics industries.Read moreRead less
Engineering Artificial Intelligence: A Spatial Representation and Reasoning Perspective. Spatial information is important in areas of national interest such as mining and exploration, environmental monitoring and planning, emergency response, and defence. Mission control centres, for instance, receive different forms of spatial data from satellites, radar, or people on the ground. They have to process the input data and make intelligent decisions in a very limited time. Intelligent systems that ....Engineering Artificial Intelligence: A Spatial Representation and Reasoning Perspective. Spatial information is important in areas of national interest such as mining and exploration, environmental monitoring and planning, emergency response, and defence. Mission control centres, for instance, receive different forms of spatial data from satellites, radar, or people on the ground. They have to process the input data and make intelligent decisions in a very limited time. Intelligent systems that are able to assist with processing different forms of spatial data efficiently and that offer reliable decision support are essential for improving the quality and reliability of such applications. This research enables future intelligent systems with these capabilities. This will directly benefit applications in areas of national interest.Read moreRead less
Declarative Networks: Towards Robust and Explainable Deep Learning. The aim of this project is to develop declarative machine learning techniques that exploit inherent structure and models of the world. Deep learning has become the dominant approach for machine learning with many products and promises built on this technology. But deep learning is expensive, opaque, brittle and relies solely on human labelled data. This project intends to make deep learning more reliable by establishing theory a ....Declarative Networks: Towards Robust and Explainable Deep Learning. The aim of this project is to develop declarative machine learning techniques that exploit inherent structure and models of the world. Deep learning has become the dominant approach for machine learning with many products and promises built on this technology. But deep learning is expensive, opaque, brittle and relies solely on human labelled data. This project intends to make deep learning more reliable by establishing theory and algorithms that allow physical and mathematical models to be embedded within a deep learning framework, providing performance guarantees and interpretability. This would likely benefit machine learning based products that can understand the world and interact with humans naturally through vision and language.Read moreRead less
Migration and mobility: the question of childhood in Chinese and European cinema since 1945. This project will produce a comparative account of the migrant and mobile child in postwar film, researched in China and Europe. It will contribute deeper knowledge of how childhood has been valued in key societies since 1945, and will bring new energy to international and domestic debates on the status, image and experience of migrant children.