Discovery Early Career Researcher Award - Grant ID: DE190101174
Funder
Australian Research Council
Funding Amount
$395,000.00
Summary
Building a mechanical quantum memory from superfluid helium. This project aims to implement a quantum computer memory module which can be integrated in a future hybrid quantum computer, where the advantages of different quantum platforms are combined. The memory module will be achieved by coupling a superconducting qubit to the surface vibrations of superfluid helium and exchanging quantum information between the qubit and helium. By simulating chemical reactions, the project expects to find cle ....Building a mechanical quantum memory from superfluid helium. This project aims to implement a quantum computer memory module which can be integrated in a future hybrid quantum computer, where the advantages of different quantum platforms are combined. The memory module will be achieved by coupling a superconducting qubit to the surface vibrations of superfluid helium and exchanging quantum information between the qubit and helium. By simulating chemical reactions, the project expects to find cleaner alternatives of current industrial processes, reducing environmental impact. The outcomes should provide significant benefits for testing the validity of quantum mechanics, and by contributing to the realisation of a quantum computer, contribute to broad socio-economic benefits.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototy ....Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototype of the proposed imaging system with 77 GHz millimetre wave will be developed to demonstrate its feasibility and performance. The expected outcomes include Australia’s scientific and technological leadership in radar imaging and enhanced capability in emergency response, defence, public safety, and healthcare industries.Read moreRead less
Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic ....Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic noisy speech signals and the ‘cocktail party problem’ using innovative binaural feedback systems. This work should provide significant benefits, including improved voice biometrics and selective auditory attention capabilities in machines.Read moreRead less
Drone-based Communications for High-speed Beyond 5G Wireless Systems. Drone-based communication is a revolutionised wireless paradigm for the development of highly flexible and cost-effective beyond fifth-generation (B5G) wireless systems. This project aims to develop novel communication theories and practical techniques to realise truly high-speed and ubiquitous communication required in B5G networks. The project intends to deliver resource allocation designs, robust transceiver designs and a s ....Drone-based Communications for High-speed Beyond 5G Wireless Systems. Drone-based communication is a revolutionised wireless paradigm for the development of highly flexible and cost-effective beyond fifth-generation (B5G) wireless systems. This project aims to develop novel communication theories and practical techniques to realise truly high-speed and ubiquitous communication required in B5G networks. The project intends to deliver resource allocation designs, robust transceiver designs and a system-level analysis as the foundations and tools to unlock the potential of this promising paradigm. The outcomes of this project are expected to fundamentally advance the knowledge of drone-based communications with significant economic values to service providers and benefits to mobile users over the world.Read moreRead less
Ultra-reliable and low-latency mission critical communications. This project aims to develop enabling technologies for ultra-reliable and low-latency communications. While the evolution of wireless communication technologies to date has focused on data rate improvement, very little is known on how to achieve ultra-reliability and almost-zero latency which is urgently required for mission critical applications such as smart manufacturing and intelligent vehicles. The outcomes of the project will ....Ultra-reliable and low-latency mission critical communications. This project aims to develop enabling technologies for ultra-reliable and low-latency communications. While the evolution of wireless communication technologies to date has focused on data rate improvement, very little is known on how to achieve ultra-reliability and almost-zero latency which is urgently required for mission critical applications such as smart manufacturing and intelligent vehicles. The outcomes of the project will be new analytical tools and practical guidelines for designing trusted communication platforms to realise these applications, with benefits ranging from improved safety in intelligent transportation systems to digital transformation of the manufacturing industry.Read moreRead less
A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, th ....A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, this project seeks to develop new distributed solutions for statistical estimation, which are specifically designed for dynamic systems with multiple object states, and are inherently scalable and robust. The potential benefits include new technologies for smart cities, autonomous infrastructure, and digital productivity.Read moreRead less
Privately owned public space: noise cancellation over multiple regions. This project aims to advance fundamental research in active noise control over spatial regions. It has a broad range of industry applications, such as eliminating road and engine noise for multiple passengers inside car/airplane cabins, and creating individual quiet zones in a public environment. It will focus on developing new theories and techniques to generate multiple quiet zones in indoor/outdoor noisy environments with ....Privately owned public space: noise cancellation over multiple regions. This project aims to advance fundamental research in active noise control over spatial regions. It has a broad range of industry applications, such as eliminating road and engine noise for multiple passengers inside car/airplane cabins, and creating individual quiet zones in a public environment. It will focus on developing new theories and techniques to generate multiple quiet zones in indoor/outdoor noisy environments with performance prediction, robust control, and effective implementation. In many practical applications, especially in consumer electronics and medical instruments, the creation of quiet zones is desirable so that in a shared environment people can have their own audio space without physical isolation or using headphones, creating a healthy living and working environment.Read moreRead less
Parameter estimation for genetic time-series data: Theory and methods. This project aims to develop a novel computational framework for solving parameter estimation problems in evolutionary modelling by leveraging genetic time-series data measured by Next-Generation Sequencing technologies. It will foster international collaboration, cutting across disciplines. By introducing new techniques from signal processing and tools from random matrix theory commonly employed for mobile wireless communica ....Parameter estimation for genetic time-series data: Theory and methods. This project aims to develop a novel computational framework for solving parameter estimation problems in evolutionary modelling by leveraging genetic time-series data measured by Next-Generation Sequencing technologies. It will foster international collaboration, cutting across disciplines. By introducing new techniques from signal processing and tools from random matrix theory commonly employed for mobile wireless communications, it seeks to design scalable inference methods for resolving mutational fitness effects from genetic time-series measurements of complex evolving populations. This would enable new understanding of complex adaptive systems, such as pathogen evolution, host-immune dynamics, and acquisition of drug resistance. Read moreRead less