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
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
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less
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
Organising Intracellular Compartments by Formation of Transport Carriers. This project aims to investigate the cellular components which generate carriers that transport material between compartments within the cell. The process of sorting proteins and sending them to the right place is a fundamental mechanism critical to understand how individual proteins function as the move around within cells. The generated knowledge about how cells organise themselves through the movement of proteins betwee ....Organising Intracellular Compartments by Formation of Transport Carriers. This project aims to investigate the cellular components which generate carriers that transport material between compartments within the cell. The process of sorting proteins and sending them to the right place is a fundamental mechanism critical to understand how individual proteins function as the move around within cells. The generated knowledge about how cells organise themselves through the movement of proteins between endosomal intracellular compartments will provide significant benefits by enhancing our capacity to understand this conserved cellular pathway which ensures the integrity of all cellular processes including signalling, communication, homeostasis and development.Read moreRead less
Fyn-STEP-Tau axis: the nanoscale mechanisms of synaptic plasticity. This project investigates how brain cells use their molecular machinery to communicate with one another. At the heart of this process lies the synapses, the contact points that connect brain cells. This project will employ an innovative combination of quantitative microscopy techniques, gene knockout mouse models, and advanced computational and mathematical analyses to generate new knowledge on how a crucial set of proteins orga ....Fyn-STEP-Tau axis: the nanoscale mechanisms of synaptic plasticity. This project investigates how brain cells use their molecular machinery to communicate with one another. At the heart of this process lies the synapses, the contact points that connect brain cells. This project will employ an innovative combination of quantitative microscopy techniques, gene knockout mouse models, and advanced computational and mathematical analyses to generate new knowledge on how a crucial set of proteins organises in space and time to regulate synaptic connectivity. This will provide significant benefits, including molecular-level insight into the inner workings of the brain and interdisciplinary training for students. The expected outcomes include a deeper understanding of brain functions, such as learning and memory.Read moreRead less
Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection ....Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection accuracy and advances in deep learning network architecture for image parsing. The intended outcomes are deep learning network architecture, contextual feature extraction techniques and network parameter optimisation techniques for image parsing.Read moreRead less
Regulation of activity-induced glutamate receptor trafficking in neurons. Neurons communicate via synapses, where chemicals (such as glutamate) are released to transmit neuronal signals. This proposal is aimed at understanding the molecular mechanisms of neuronal communication and adaptive plasticity, which are essential for normal brain function. The proposed research will combine biophysical, biochemical, molecular and cell biological assays to elucidate the role of a calcium binding protein i ....Regulation of activity-induced glutamate receptor trafficking in neurons. Neurons communicate via synapses, where chemicals (such as glutamate) are released to transmit neuronal signals. This proposal is aimed at understanding the molecular mechanisms of neuronal communication and adaptive plasticity, which are essential for normal brain function. The proposed research will combine biophysical, biochemical, molecular and cell biological assays to elucidate the role of a calcium binding protein in controlling glutamate receptor trafficking in neurons. The outcomes will enhance our understanding of how neural plasticity is generated and maintained, knowledge that is critical for our understanding of cellular correlates of information, sensory and motor processing, as well as learning, memory and cognition. Read moreRead less
Unveiling the nanoscale organisation and dynamics of synaptic vesicle pools. This project aims to uncover the role of key molecules in allowing brain cells to actively communicate with each other. Communication between neurons relies on the fusion of synaptic vesicles containing neurotransmitters with the presynaptic plasma membrane. The addition of vesicular membrane is transient as the vesicles quickly reform from the plasma membrane and refill with neurotransmitter ready for subsequent rounds ....Unveiling the nanoscale organisation and dynamics of synaptic vesicle pools. This project aims to uncover the role of key molecules in allowing brain cells to actively communicate with each other. Communication between neurons relies on the fusion of synaptic vesicles containing neurotransmitters with the presynaptic plasma membrane. The addition of vesicular membrane is transient as the vesicles quickly reform from the plasma membrane and refill with neurotransmitter ready for subsequent rounds of fusion. This recycling process ensures that neurons communicate efficiently, however the underpinning mechanism is unknown. This project aims to use a recently developed single synaptic vesicle super-resolution tracking method to establish how Myosin-VI and Synapsin-IIa orchestrate this recycling in central and peripheral neurons. It will explain how neurons manage to preserve their ability to communicate.Read moreRead less
Linking human brain structure to function with ultra-high resolution fMRI. This project will examine the structure and function of the sensory cortex of the human brain using ultra-high resolution functional magnetic resonance imaging (7 Tesla MRI). The project pushes new boundaries for resolution with ultra-high field MRI (7 Tesla) and, as such, will advance techniques for the acquisition, analysis, and computational modelling of high-resolution fMRI brain imaging, providing detail of the funct ....Linking human brain structure to function with ultra-high resolution fMRI. This project will examine the structure and function of the sensory cortex of the human brain using ultra-high resolution functional magnetic resonance imaging (7 Tesla MRI). The project pushes new boundaries for resolution with ultra-high field MRI (7 Tesla) and, as such, will advance techniques for the acquisition, analysis, and computational modelling of high-resolution fMRI brain imaging, providing detail of the functional organisation of the sensory cortex at a level never previously possible in the living human brain. This will provide new understanding of the neural-level networks that underpin attention and touch perception in the human brain.Read moreRead less