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Controlling ultracold atomic gases. This project will develop ways to control the quantum state of ultracold atomic gases. These experimentally accessible systems will be used to investigate and understand a huge range of scientific phenomena from stars to superconductors, and enable critical quantum technologies that will revolutionise communications and precision measurement.
The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molec ....The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molecular atlas projects have successfully revealed rules of genome output and regulation, by mining patterns that are evident across multiple cell types and datasets. By applying this philosophy to relevant, well-curated stem cell experiments, this project aims to create new methods for the integration and interrogation of smaller individual datasets. These methods should have broad utility and enable new avenues in tissue engineering.Read moreRead less
Dynamic resource provisioning for autonomic management of cloud computing environments. In the next 20 years, service-oriented computing will play an important role in shaping the industry and will require cloud infrastructure hosting applications to deliver services at low cost. This project will develop technologies for self-managed cloud computing platforms that reduce usage and operational costs, thus transforming the Australian economy.
Information access through web-scale question-answer pair finding, ranking and matching. This project will aim to take web search to a new level of sophistication in accepting queries in the form of complex natural language questions, and returning a ranked list of natural language answers automatically extracted from a broad range of web user forums.
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
Exploiting Context in Multilingual Understanding and Generation. Automatic translation technologies produce incoherent and incorrect outputs in critical areas, such as health, finance, and law. This is due to translating sentences independently, without regard to the global extra-sentential context and rich linguistic structures inherent in the wider document context. This project aims to exploit global linguistic structures, capitalising on recent advances in deep neural networks, in order to g ....Exploiting Context in Multilingual Understanding and Generation. Automatic translation technologies produce incoherent and incorrect outputs in critical areas, such as health, finance, and law. This is due to translating sentences independently, without regard to the global extra-sentential context and rich linguistic structures inherent in the wider document context. This project aims to exploit global linguistic structures, capitalising on recent advances in deep neural networks, in order to generate coherent and faithful text. Expected outcome include next-generation computational technologies for language understanding and generation. This should significantly benefit document-based language technologies and increase their applications in a range of cultural, industrial, and health settings.Read moreRead less
Adaptive Context-Dependent Machine Translation for Heterogeneous Text. While automatic machine translation technologies are undoubtedly useful to a wide range of users, they often produce incoherent outputs for many types of input, for example, medical, literature, or even conversational text. This project will develop new adaptive machine translation systems to handle many domains and text styles, including heterogeneous mixed-domain inputs. It will develop multi-task machine learning methods f ....Adaptive Context-Dependent Machine Translation for Heterogeneous Text. While automatic machine translation technologies are undoubtedly useful to a wide range of users, they often produce incoherent outputs for many types of input, for example, medical, literature, or even conversational text. This project will develop new adaptive machine translation systems to handle many domains and text styles, including heterogeneous mixed-domain inputs. It will develop multi-task machine learning methods for training collections of domain-specific translation systems while leveraging correlations between domains. This approach will reduce the big data requirements of current translation systems, and improve translation quality across a wide range of different language pairs and application domains.Read moreRead less