Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficul ....Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project aims to systematically develop a logic-based framework to adequately capture and reason about evolving causal knowledge. This research is expected to form the basis for smart decision making, and be evaluated on practical applications.Read moreRead less
Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive ....Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.Read moreRead less
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Intelligent Image Processing Techniques for Novel Biomarker Discovery. This project will make an impact on Australia's international research profile by seeking a solution to a worldwide challenging problem in biomarker discovery for the detection of diseases at an early stage which requires the incorporation of the skills and knowledge from biology, medicine, engineering, computer science, and information technology. The successful outcomes of this research will make an impact on Australia's e ....Intelligent Image Processing Techniques for Novel Biomarker Discovery. This project will make an impact on Australia's international research profile by seeking a solution to a worldwide challenging problem in biomarker discovery for the detection of diseases at an early stage which requires the incorporation of the skills and knowledge from biology, medicine, engineering, computer science, and information technology. The successful outcomes of this research will make an impact on Australia's engagement in using advanced image analysis and intelligent methods for the emerging research and development of targeted drug discovery. Read moreRead less
An Automated Bioimaging System for High-Content Cell-Cycle Screening. 1) Providing a better understanding of the biological complexities
that will advance knowledge in life science research and facilitate the development of new anti-cancer drugs.
2) Supporting Australian academic institutions in a challenging field of innovative research through international, interdisciplinary collaborations, and publications in journals of high quality scientific research.
3) Providing research training ....An Automated Bioimaging System for High-Content Cell-Cycle Screening. 1) Providing a better understanding of the biological complexities
that will advance knowledge in life science research and facilitate the development of new anti-cancer drugs.
2) Supporting Australian academic institutions in a challenging field of innovative research through international, interdisciplinary collaborations, and publications in journals of high quality scientific research.
3) Providing research training in a research venture that requires expertise and collaboration in the disciplines of biology, engineering, computer science, and mathematics.
4) Bringing economic and social benefits for Australia by enhancing important industries and existing technologies in medicine, and biotechnology.
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Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Real-time high-level cognitive robotics controllers. Technological advances have seen the recent release of commercially affordable mobile robots. In the wake of Sony's immensely successful AIBO entertainment robot, it is anticipated that the market will be flooded with similar devices in short time. However, while traditional robotics focuses on problems like navigation and sensory perception, scant attention has been paid to the development of high-level cognitive robotics languages for coordi ....Real-time high-level cognitive robotics controllers. Technological advances have seen the recent release of commercially affordable mobile robots. In the wake of Sony's immensely successful AIBO entertainment robot, it is anticipated that the market will be flooded with similar devices in short time. However, while traditional robotics focuses on problems like navigation and sensory perception, scant attention has been paid to the development of high-level cognitive robotics languages for coordinating these lower-level "skills". Such languages allow development of sophisticated robot controllers. We aim to develop a cognitive robotics language capable of controlling robots in real-time and in a multi-agent setting requiring coordination among agents.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less