Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with thei ....Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with their environment, and the simulation of spatiotemporal deformations in anatomical organs. Benefits include a better understanding of growth processes, predictive models of how degenerative diseases progress and a computational framework that will assist in designing proper mitigation and intervention strategies.Read moreRead less
Pyruvate provision for mitochondrial respiration in plants. This project aims to generate new knowledge about pyruvate provision for respiration in plants as it is a major pathway of carbon loss from plants. It will address specific gaps in knowledge about how pyruvate is provided to mitochondria for respiration, how channelling of pyruvate is achieved between components in this pathway and it will seek to engineering a new pyruvate supply pathway to change respiratory processes in plants. It wi ....Pyruvate provision for mitochondrial respiration in plants. This project aims to generate new knowledge about pyruvate provision for respiration in plants as it is a major pathway of carbon loss from plants. It will address specific gaps in knowledge about how pyruvate is provided to mitochondria for respiration, how channelling of pyruvate is achieved between components in this pathway and it will seek to engineering a new pyruvate supply pathway to change respiratory processes in plants. It will develop techniques for analysis of metabolic processes in plants and genetic proof for assumptions of how plant respiration works. Benefits will be training of early career researchers, enhanced international reputation of Australian plant science and new approaches to engineer respiratory rate in plants.Read moreRead less
Tensor and Hypergraph Methods in Fitting Visual Data. This proposal will put an important class of clustering (extracting data that should fit a geometric model) on a more solid theoretical foundation. This will lead to better understanding of how to certify outcomes, efficiency, reliability etc. The type of clustering under consideration is relevant to many problems in machine learning and computer vision, as well as data mining and a wide variety of other settings.
Advancing plant synthetic gene circuit capability, robustness, and use. This project aims to advance our ability to control gene expression in plants using synthetic gene circuits. By expanding the toolkit and optimizing circuit components, we aim to achieve more complex capabilities and robust implementation. Furthermore, we will apply gene circuit technologies to enhance plant frost tolerance. The expected project outcomes include a significant advance in gene circuit capabilities, a better un ....Advancing plant synthetic gene circuit capability, robustness, and use. This project aims to advance our ability to control gene expression in plants using synthetic gene circuits. By expanding the toolkit and optimizing circuit components, we aim to achieve more complex capabilities and robust implementation. Furthermore, we will apply gene circuit technologies to enhance plant frost tolerance. The expected project outcomes include a significant advance in gene circuit capabilities, a better understanding of their behavior in plant cells, and the ability to use them to confer advantageous traits. The benefits of this research include new plant biotechnology tools that will underpin future crop yield improvements, and advances in plant-based pharmaceuticals and materials.Read moreRead less
Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area o ....Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area of remote sensing and to make Australia the leader in passive flying objects positioning and tracking. This should provide significant benefits, such as enabling new applications for future drone delivery systems or aerial taxi services, and benefiting the air transport industry, the defence industry, and bird conservation.Read moreRead less
Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learni ....Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learning architectures that are inherently robust. The outcomes of this project will increase the security and reliability of computer vision by detecting, reporting and nullifying such attacks and will benefit the general public and industry on many fronts.Read moreRead less
Investigating a novel genetic strategy for insect resistance in crops. Plants are in a constant battle with insect pests and there is an increasing reliance on chemical inputs for control. However there are incoming bans on some pesticides, and new approaches are required for pest management. The aim of this project is to develop a new strategy which exploits the dependence of herbivorous insects on phytosterols. Here, we will apply the latest genomics technologies in plants to produce non-utili ....Investigating a novel genetic strategy for insect resistance in crops. Plants are in a constant battle with insect pests and there is an increasing reliance on chemical inputs for control. However there are incoming bans on some pesticides, and new approaches are required for pest management. The aim of this project is to develop a new strategy which exploits the dependence of herbivorous insects on phytosterols. Here, we will apply the latest genomics technologies in plants to produce non-utilizable sterols which will not support insect growth and reproduction, but will still allow the plant to function normally. We will demonstrate this in the important crop canola. Translation of this knowledge will support breeding for crop resilience, leading to durable resistance and more sustainable crop production.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less
3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D ....3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D measurements with resolution and coverage unachievable before, paving the way for innovative water relevant applications such as hydrology and agriculture, and new findings in atmospheric research.Read moreRead less