Discovery Early Career Researcher Award - Grant ID: DE190101418
Funder
Australian Research Council
Funding Amount
$398,000.00
Summary
Extremely-high-speed and reliable coding for next generation communications. This project aims to develop fundamental coding theories and innovative coded-modulation techniques for the next generation backbone communication systems. The development of these techniques is expected to lead to dramatic increases of spectrum efficiency, data rate and reliability of communication systems. The techniques will enable extremely high speed and extremely reliable front-haul/back-haul communications, which ....Extremely-high-speed and reliable coding for next generation communications. This project aims to develop fundamental coding theories and innovative coded-modulation techniques for the next generation backbone communication systems. The development of these techniques is expected to lead to dramatic increases of spectrum efficiency, data rate and reliability of communication systems. The techniques will enable extremely high speed and extremely reliable front-haul/back-haul communications, which constitute the major building blocks of critical information and communications technology infrastructures for future digital society. This project is expected to support the sustainable development of the emerging digital society and new data-intensive applications, which are crucial for the long term economic growth for the Australian community.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100636
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Efficient Coding for Distributed-input Distributed-output Wireless Systems. Inter-user interference is becoming the dominant bottleneck in state-of-the-art wireless networks. This project aims to address this bottleneck problem by studying a new paradigm, referred to as a Distributed-Input Distributed-Output (DIDO) wireless system, which makes the best use of interference. Results from information theory and modern coding techniques will be advanced to develop new design principles and novel ph ....Efficient Coding for Distributed-input Distributed-output Wireless Systems. Inter-user interference is becoming the dominant bottleneck in state-of-the-art wireless networks. This project aims to address this bottleneck problem by studying a new paradigm, referred to as a Distributed-Input Distributed-Output (DIDO) wireless system, which makes the best use of interference. Results from information theory and modern coding techniques will be advanced to develop new design principles and novel physical-layer coding techniques of DIDO systems, leading to substantially improved throughput, reliability, energy efficiency and robustness. This project aims to develop fundamentally enhanced wireless infrastructure with targeted applications in cellular and wireless networks, satellite communications and wireless sensor networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101116
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Leakage-Resilient and Quantum-Secure Authenticated Key Exchange Protocols. Authenticated key exchange protocols allow multiple parties to establish a common secret key over a public network, and are a central component of network security. Key-leakage and quantum attacks are two primary threats against the existing protocols. This project aims to fill the gap by developing new authenticated key exchange protocols which are secure against both attacks. The new models, theories, and techniques dev ....Leakage-Resilient and Quantum-Secure Authenticated Key Exchange Protocols. Authenticated key exchange protocols allow multiple parties to establish a common secret key over a public network, and are a central component of network security. Key-leakage and quantum attacks are two primary threats against the existing protocols. This project aims to fill the gap by developing new authenticated key exchange protocols which are secure against both attacks. The new models, theories, and techniques developed in this project will produce technologies essential for securing data communications in current and future computer networks, and hence directly contribute to improving cybersecurity for all Australians.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100668
Funder
Australian Research Council
Funding Amount
$435,000.00
Summary
Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations ....Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big streaming temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and social analysis.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101329
Funder
Australian Research Council
Funding Amount
$432,355.00
Summary
Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven d ....Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven decision systems and rigorously analyse their performance and privacy guarantees. Privacy of individuals' information in data analytics pipelines is a key societal concern. This project should lead to significant benefits by strengthening privacy in these pipelines while also improving accuracy and cost-efficiency.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101266
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Low-complexity factor-graph-based receiver design for bandwidth-efficient communication systems over doubly selective channels. This project aims to solve challenging problems in future wireless communications using graph-based signal processing techniques. It will provide practical solutions for future broadband mobile communications to the bush and high-speed underwater acoustic communications in the oceans that are particularly important to Australia.
Discovery Early Career Researcher Award - Grant ID: DE230100001
Funder
Australian Research Council
Funding Amount
$424,064.00
Summary
Regulations in Privacy-Preserving Blockchain Systems. This project aims to develop an integrated regulatory paradigm for privacy-preserving blockchain. This project expects to reduce cybercrimes and illegal transactions in blockchain and provide solutions for the regulation concerns raised in the national blockchain roadmap, using interdisciplinary approaches and new primitives. Expected outcomes of this project include providing versatile regulation services covering the whole lifetime of trans ....Regulations in Privacy-Preserving Blockchain Systems. This project aims to develop an integrated regulatory paradigm for privacy-preserving blockchain. This project expects to reduce cybercrimes and illegal transactions in blockchain and provide solutions for the regulation concerns raised in the national blockchain roadmap, using interdisciplinary approaches and new primitives. Expected outcomes of this project include providing versatile regulation services covering the whole lifetime of transactions while maintaining transaction privacy and user anonymity. This should provide significant benefits to the economy by reducing the financial loss caused by blockchain abuse worldwide ($76 billion per year) and promoting Australia’s blockchain ecosystem (grow to AU$68.4 billion by 2030). Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100679
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and effic ....Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and efficiently support a set of primitive queries including rank-based queries, dominance-based queries and proximity-based queries. The results of this project will be an important complement to the development of data stream systems and will bring considerable social, economic and technological benefits to Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100495
Funder
Australian Research Council
Funding Amount
$422,154.00
Summary
Structured Federated Learning for Personalised Intelligence on Devices. The project aims to develop a new structured federated machine-learning framework to enhance the customisation of artificial intelligence across mobile and smart devices. It seeks to enable users to receive customised services on their devices without sending their sensitive personal data to a cloud service provider. Anticipated benefits include greater privacy, data security and device performance, as well as better end-use ....Structured Federated Learning for Personalised Intelligence on Devices. The project aims to develop a new structured federated machine-learning framework to enhance the customisation of artificial intelligence across mobile and smart devices. It seeks to enable users to receive customised services on their devices without sending their sensitive personal data to a cloud service provider. Anticipated benefits include greater privacy, data security and device performance, as well as better end-user experience. Expected outcomes of this research include new knowledge, toolkits and algorithms for use in developing machine-learning based secure, efficient and fault-tolerant technologies for software applications, mobile services, cloud computing, autonomous vehicles and advanced manufacturing processes.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100964
Funder
Australian Research Council
Funding Amount
$427,068.00
Summary
Early Prediction in Large-scale Time-variant Information Networks. This project aims to develop an early prediction system to predict possible outbreaks of malicious messages in time-variant information networks. The research will primarily leverage deep representations of time-variant subsequence and substructure patterns in large-scale social networks to signal malicious and malevolent messages before it has a chance to propagate. This project will lay the theoretical foundations of this emerg ....Early Prediction in Large-scale Time-variant Information Networks. This project aims to develop an early prediction system to predict possible outbreaks of malicious messages in time-variant information networks. The research will primarily leverage deep representations of time-variant subsequence and substructure patterns in large-scale social networks to signal malicious and malevolent messages before it has a chance to propagate. This project will lay the theoretical foundations of this emerging field to strengthen Australia’s world leadership role in data science. Practically, the novel theories and data analytics technologies developed will help to safeguard Australian business, industry, and society from cyberfraud, online rumour-mongering, and financial loss.Read moreRead less