Validating And Optimising The Analysis Of Magnetic Resonance Physiology Data
Funder
National Health and Medical Research Council
Funding Amount
$91,725.00
Summary
Combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is used to detect the anatomical areas in the brain that show electrical activity. Several centres worldwide use this technique to localise the seizure focus in patients with epilepsy. However, there is a lack of validation of the currently applied techniques. Current analysis methods have been developed and validated for other fMRI paradigms, such as motor tasks. It is not known whether the same principles ar ....Combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is used to detect the anatomical areas in the brain that show electrical activity. Several centres worldwide use this technique to localise the seizure focus in patients with epilepsy. However, there is a lack of validation of the currently applied techniques. Current analysis methods have been developed and validated for other fMRI paradigms, such as motor tasks. It is not known whether the same principles are applicable and optimal for fMRI-EEG data. The proposed project aims at validating and optimising the analysis strategies for fMRI-EEG data.Read moreRead less
A Multi-national Trial To Predict Treatment Response In Subtypes Of Depression
Funder
National Health and Medical Research Council
Funding Amount
$387,489.00
Summary
Treatment of MDD using trial and error can have serious consequences. It can prolong the patient’s suffering (depression is associated with substantial morbidity, and mortality), prolong their absence from work and other productive activity and increase the burden on their family-carers. This multi-national study will collect genetics, brain function and behavioural data from a large number of participants, allowing for sensitive predictors of response to be determined.
Improving The Prevention And Outcomes Of Knee And Hip Osteoarthritis
Funder
National Health and Medical Research Council
Funding Amount
$421,747.00
Summary
Osteoarthritis is a major public health problem. No current treatment slows disease progression with end-stage osteoarthritis treated by joint replacement surgery. This project will identify new approaches for the prevention and treatment of osteoarthritis and the improvement of patients’ outcomes after total joint replacement surgery. The findings will have both public health and clinical impact, informing clinical practice of strategies to improve the prevention and outcomes of osteoarthritis.
Ultra-sensitive 3D molecular assays using total body PET and deep learning. Recent advances in biomedical engineering have led to the development of Total Body Positron Emission Tomography (TB-PET), the most sensitive imaging device to date. Despite these impressive engineering advances, computational methods lag far behind and model-based approaches cannot deal with the complexity or volume of data these systems produce. We will develop new computational methods based on deep learning and stati ....Ultra-sensitive 3D molecular assays using total body PET and deep learning. Recent advances in biomedical engineering have led to the development of Total Body Positron Emission Tomography (TB-PET), the most sensitive imaging device to date. Despite these impressive engineering advances, computational methods lag far behind and model-based approaches cannot deal with the complexity or volume of data these systems produce. We will develop new computational methods based on deep learning and statistical methods that fully exploit the richness and complexity of the data generated by TB-PET, enabling 3D quantitative assays of molecular processes throughout the entire human body with unparalleled sensitivity. The technology we create will open up new capability for the study of complex physiological systems.Read moreRead less
Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes ....Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes, optimise the value of changes, and extract insights from changes for diverse downstream applications of video-sharing platforms. The expected outcomes will create new-generation representation learning techniques, and provide practical tools to amplify the socioeconomic values of video-sharing platforms.Read moreRead less
Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolut ....Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolution algorithms, and cooperative co-evolutionary strategies. The outcome results will be demonstrated by practical evaluations over public datasets and comparisons to related works. The project is beneficial to the nation in both theory of artificial intelligence techniques and applications of real transport systems.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100131
Funder
Australian Research Council
Funding Amount
$539,000.00
Summary
Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boo ....Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boost Australia’s pivotal research leadership and business competitiveness in nurturing new-generation, collaborative and transformative digital R&D and talent pipeline. It will enable large-scale strategic business innovation and transformation including smart manufacturing and Industry 4.0.Read moreRead less
Development Of A New Surgical-guidance Tool For Intra-operative Tumour Margin Assessment In Breast Cancer
Funder
National Health and Medical Research Council
Funding Amount
$557,982.00
Summary
One third of breast cancer patients undergoing breast conserving surgery have insufficient tissue removed, resulting in an increased risk of recurrence. We have developed a high resolution optical imaging probe with the potential to detect small areas of cancer. It could be used to help guide the surgeon to remove all cancerous tissue from the patient. This grant will allow us to develop the probe to a stage that it can be used during surgery, and perform the world’s first clinical scans.
A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise th ....A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise the mobile edge computing platform from the computation, storage, and network aspects. The invented mobile edge computing platform will enable more intelligent business applications for various industries, e.g., IT, manufacturing, and media, to appear, thus benefiting both the economy of Australia.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