Discovery Early Career Researcher Award - Grant ID: DE240101033
Funder
Australian Research Council
Funding Amount
$449,744.00
Summary
Superconducting Circuits for Error-Resilient Quantum Computers . This project aims to build a new class of intrinsically error-resilient quantum bits, harnessing the power of superconducting and hybrid superconducting circuits. The core goal of this research is to improve the performance of modern quantum processors, in order to reap the benefits of their vast computational power in real world applications like cryptography, chemistry, machine learning and finance. The outcomes of this project a ....Superconducting Circuits for Error-Resilient Quantum Computers . This project aims to build a new class of intrinsically error-resilient quantum bits, harnessing the power of superconducting and hybrid superconducting circuits. The core goal of this research is to improve the performance of modern quantum processors, in order to reap the benefits of their vast computational power in real world applications like cryptography, chemistry, machine learning and finance. The outcomes of this project are expected to accelerate quantum computing efforts globally and generate critical insights into quantum circuit technology, thus expanding Australia’s capabilities in nanotechnology, superconducting quantum systems and quantum processing. Read moreRead less
Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and buil ....Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and build capability in the area of approximate computing. It is also expected to lead to commercial products, licences and revenue, which will enable new job creation.
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Foundations of Nonmonotonic Logic Programming for Complex Knowledge Systems. This project will fundamentally provide a new paradigm of nonmonotonic logic programming. As such, it will significantly contribute towards Australia's leading role in the cutting edge research of intelligent systems development. The new nonmonotonic logic programming can be used as an effecive platform by many Australian computer companies for building complex knowledge systems in real world domains. Hence this projec ....Foundations of Nonmonotonic Logic Programming for Complex Knowledge Systems. This project will fundamentally provide a new paradigm of nonmonotonic logic programming. As such, it will significantly contribute towards Australia's leading role in the cutting edge research of intelligent systems development. The new nonmonotonic logic programming can be used as an effecive platform by many Australian computer companies for building complex knowledge systems in real world domains. Hence this project has potential economic and social benefits for Australia. With a very strong research team across different universities and a collaborative research training environment, this project will further enhance Australia's international reputation as a leader in computing & IT research.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
Reconciliation strategies for continuous variable quantum key distribution. This project aims to advance a novel key distribution method, called quantum key distribution, which distributes secure keys using the quantum state of optical channels. Key distribution is a foundational part of data security, allowing digital keys to be securely exchanged between two or more parties, before they are used to protect and share information. The expected outcome is new rateless error correction codes desi ....Reconciliation strategies for continuous variable quantum key distribution. This project aims to advance a novel key distribution method, called quantum key distribution, which distributes secure keys using the quantum state of optical channels. Key distribution is a foundational part of data security, allowing digital keys to be securely exchanged between two or more parties, before they are used to protect and share information. The expected outcome is new rateless error correction codes designed specifically to implement quantum key distribution over long distances. Quantum key distribution is beneficial for ultra-secure communications as it avoids the vulnerability to weak random numbers and quantum-computing brute force attacks that currently threated the security of data protected by existing methods. Read moreRead less
Quantum computation: through the algorithm and complexity theory lens. This project aims to advance our knowledge of quantum computation through the lens of algorithm and complexity theory. Three core areas of the theory will be examined: interactive computing models, query complexity, and circuit lower bounds. The expected outcomes include: revealing the quantum advantages of interactive computing models; techniques for verifying quantum devices in the cloud and quantum cloud computing in gener ....Quantum computation: through the algorithm and complexity theory lens. This project aims to advance our knowledge of quantum computation through the lens of algorithm and complexity theory. Three core areas of the theory will be examined: interactive computing models, query complexity, and circuit lower bounds. The expected outcomes include: revealing the quantum advantages of interactive computing models; techniques for verifying quantum devices in the cloud and quantum cloud computing in general; sharpening the separation between algorithm performance in quantum and classical query models; establishing both unconditional and conditional hardness results for quantum circuits. This comprehensive understanding will enhance Australia's research portfolio in the theory of quantum computing.Read moreRead less
Visual interaction methods for clustered graphs. This project aims to improve human understanding of huge network data sets, such as those arising in social networks, biological networks, and very large software structures. The project will enable analysts to explore and interact with such data sets, leading to better understanding.
Multivariate Algorithmics: Meeting the Challenge of Real World computational complexity. This Project will result in better methods for designing the algorithms that all computer applications depend on. Algorithms are the instruction sets that tell computers how to process information. Some information processing tasks are intrinsically difficult, even for computers working at enormous speeds. This Project will deliver new mathematical approaches to overcome these difficulties. More efficient al ....Multivariate Algorithmics: Meeting the Challenge of Real World computational complexity. This Project will result in better methods for designing the algorithms that all computer applications depend on. Algorithms are the instruction sets that tell computers how to process information. Some information processing tasks are intrinsically difficult, even for computers working at enormous speeds. This Project will deliver new mathematical approaches to overcome these difficulties. More efficient algorithmic approaches for difficult problems enable advances in all areas of computer applications such as medical diagnosis and health prediction, national security, communications efficiency, industrial productivity and all fields of science and engineering.Read moreRead less
Local reoptimization for turbocharging heuristics. Theoretical computer science has up until now had little impact on the design of effective heuristics. While data sets may be large, significant structure is almost always present and important to take into account when designing algorithms. Parameterised complexity considers the underlying structure by parameterising not only on the size of the input but also on structural parameters. This project aims to take advantage of the many opportunitie ....Local reoptimization for turbocharging heuristics. Theoretical computer science has up until now had little impact on the design of effective heuristics. While data sets may be large, significant structure is almost always present and important to take into account when designing algorithms. Parameterised complexity considers the underlying structure by parameterising not only on the size of the input but also on structural parameters. This project aims to take advantage of the many opportunities for new theories in the design of new heuristics and in turbocharging existing heuristics for computationally hard problems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101664
Funder
Australian Research Council
Funding Amount
$357,084.00
Summary
Universal solution for scheduling problems. The aim of this project is to design efficient algorithms that compute universal solutions for scheduling on an unreliable machine. Such solutions are specially suitable for situations where machines can behave unpredictably, such as scheduling in cloud computing.