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
2D Multiferroics: From Materials Design to Device Conceptualization. This project aims to design new transistors with high efficiency and low energy costing for the storage applications based on two-dimensional multifunctional heterostructures. Extensive computational simulations and joint experiments will be employed to develop fundamental knowledge essential to understanding the phenomena of magnetoelectric coupling, which is used to guide rational device design and implementation. The designe ....2D Multiferroics: From Materials Design to Device Conceptualization. This project aims to design new transistors with high efficiency and low energy costing for the storage applications based on two-dimensional multifunctional heterostructures. Extensive computational simulations and joint experiments will be employed to develop fundamental knowledge essential to understanding the phenomena of magnetoelectric coupling, which is used to guide rational device design and implementation. The designed magnetoelectric heterostructures and the multiferroic devices are expected to provide strong foundations for technological innovations resulting in devices with superior functionality and efficiency. The outcome of the project will significantly benefit high-tech electronics.Read moreRead less
Ultra-high mobility Dirac semimetal nanostructures for solid state devices. This project aims to develop novel Dirac semimetal nanostructures and determine their structural and chemical characteristics to ultimately assemble high-performance devices. The growth of band-engineered nanostructures and understanding their evolution, fine structure and unique properties are key steps for developing high-performance nanostructure-based devices. The new knowledge and skills developed in this project wi ....Ultra-high mobility Dirac semimetal nanostructures for solid state devices. This project aims to develop novel Dirac semimetal nanostructures and determine their structural and chemical characteristics to ultimately assemble high-performance devices. The growth of band-engineered nanostructures and understanding their evolution, fine structure and unique properties are key steps for developing high-performance nanostructure-based devices. The new knowledge and skills developed in this project will greatly enhance the knowledge base of nanoscience and nanotechnology, and will have a significant impact on practical applications of nanostructure-based devices. This project will underpin the development of next-generation electronic nanomaterials that will enhance the long-term viability of Australia’s high-technology industries.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180101579
Funder
Australian Research Council
Funding Amount
$346,446.00
Summary
Searching when the stakes are high: better health decisions from search engines. This project aims to help people make better health decisions from search engines by improving the information that search queries return. Google is utilised by 80 per cent of Australians to search health symptoms, despite evidence showing that many often find incorrect and unreliable health information. This project expects to provide new understanding about why and how people fail to find useful health information ....Searching when the stakes are high: better health decisions from search engines. This project aims to help people make better health decisions from search engines by improving the information that search queries return. Google is utilised by 80 per cent of Australians to search health symptoms, despite evidence showing that many often find incorrect and unreliable health information. This project expects to provide new understanding about why and how people fail to find useful health information. Expected outcomes of this project include new models and methods for evaluating high-stakes search and new search technologies to help people find and recognise high quality information to make better health decisions. This should provide significant benefits to Australian health consumers and the healthcare system.Read moreRead less
AI-driven Effective Query Formulation for Better Systematic Reviews. This project aims to develop novel AI-based search engine methods to make the creation of systematic reviews cheaper, faster and unbiased. Systematic reviews are the cornerstone for evidence-based decisions in clinical practice and government policy making. Given the pace new research is published at, it is unsustainable to manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and be ....AI-driven Effective Query Formulation for Better Systematic Reviews. This project aims to develop novel AI-based search engine methods to make the creation of systematic reviews cheaper, faster and unbiased. Systematic reviews are the cornerstone for evidence-based decisions in clinical practice and government policy making. Given the pace new research is published at, it is unsustainable to manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and becoming already outdated when published. The outcomes of this project will lead to systematic reviews of higher quality, while reducing their financial and temporal costs, providing significant benefits to organisations performing reviews and their funders, and to people impacted by decisions made from the reviews.Read moreRead less
Government web portals as government actors. This project aims to examine the architectures, rationales, effectiveness and power effects of government web portals, which are conceptualised as spaces of administrative, policy and power contestation. They are the formal public face of online government, but their effectiveness and contribution to government is largely unknown. The project uses digital research methods (hyperlink network analysis and web experiments) to comparatively assess 10 hi-t ....Government web portals as government actors. This project aims to examine the architectures, rationales, effectiveness and power effects of government web portals, which are conceptualised as spaces of administrative, policy and power contestation. They are the formal public face of online government, but their effectiveness and contribution to government is largely unknown. The project uses digital research methods (hyperlink network analysis and web experiments) to comparatively assess 10 hi-tech countries. It expects to contribute to understanding the structure and governance of the state in the 21st century, and provide foundational knowledge to underpin the next generation of government online service strategy.Read moreRead less
Defining the Impact of Regionalism on Aboriginal Housing and Settlements. This project aims to analyse, quantify and improve our understanding of Aboriginal and Torres Strait Islander housing needs. It will develop an innovative regional approach to needs assessment and housing procurement that considers cultural protocols, access to services, sustainable design and regional governance. By integrating qualitative and quantitative data, and comparing case studies from remote, rural and urban regi ....Defining the Impact of Regionalism on Aboriginal Housing and Settlements. This project aims to analyse, quantify and improve our understanding of Aboriginal and Torres Strait Islander housing needs. It will develop an innovative regional approach to needs assessment and housing procurement that considers cultural protocols, access to services, sustainable design and regional governance. By integrating qualitative and quantitative data, and comparing case studies from remote, rural and urban regions, this project will identify the most significant factors in different contexts and tailor solutions to optimise Indigenous housing outcomes. Expected outcomes include improved housing management, housing design, health and well-being of Indigenous communities and a reduction in crowding and homelessness.Read moreRead less
Digital noticeboards for remote Aboriginal communities: bringing web 2.0 participation to non-western cultures with low English and technical literacy. Remote Aboriginal communities suffer from geographic and cultural isolation. Web 2.0 offers a solution yet is ill-suited to traditional collective cultures, those with low English and technical literacy, and the poor. This project will produce novel public web-enabled touchscreen noticeboards and table tops suited to traditional cultures.
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: DE240100105
Funder
Australian Research Council
Funding Amount
$458,823.00
Summary
Towards Evolvable and Sustainable Multimodal Machine Learning. Machine learning is commonly limited to a single operational modality. To enable image, sound and language comprehension simultaneously would require machines to reuse knowledge and understand concepts from multimodal data. The project aims to build a sparse model and present a set of innovative algorithms to enhance model generalisation for addressing distributional and semantic shifts and minimise the computational and labelling co ....Towards Evolvable and Sustainable Multimodal Machine Learning. Machine learning is commonly limited to a single operational modality. To enable image, sound and language comprehension simultaneously would require machines to reuse knowledge and understand concepts from multimodal data. The project aims to build a sparse model and present a set of innovative algorithms to enhance model generalisation for addressing distributional and semantic shifts and minimise the computational and labelling costs for training multimodal systems. Its outcomes will enable evolvable learning of models to suit varying testing scenarios after deployment and whilst reducing energy consumption and carbon emission. The application of these techniques could benefit sectors such as E-commerce, agriculture and transport.Read moreRead less