Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes ....Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes, optimise the value of changes, and extract insights from changes for diverse downstream applications of video-sharing platforms. The expected outcomes will create new-generation representation learning techniques, and provide practical tools to amplify the socioeconomic values of video-sharing platforms.Read moreRead less
Multimodal biomedical imaging probes: development of advanced polymer nanocomposite devices for oncology. Despite significant research being directed toward cancer treatment, 7.6 million people died world wide in 2007. Early detection and treatment is widely recognised as being effective in significantly reducing mortality rates. Biomedical imaging techniques are routinely used for detection and staging of many cancers. However, greater sensitivity is required so that these techniques can be app ....Multimodal biomedical imaging probes: development of advanced polymer nanocomposite devices for oncology. Despite significant research being directed toward cancer treatment, 7.6 million people died world wide in 2007. Early detection and treatment is widely recognised as being effective in significantly reducing mortality rates. Biomedical imaging techniques are routinely used for detection and staging of many cancers. However, greater sensitivity is required so that these techniques can be applied to very early detection of tumours. To overcome this short-coming the next generation of imaging probes will be developed, which will require fundamental investigations in polymer and nanomaterials science to maximise imaging sensitivity and extend probe functionality. Successful outcomes will lead to significant benefits to healthcare in Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100105
Funder
Australian Research Council
Funding Amount
$458,823.00
Summary
Towards Evolvable and Sustainable Multimodal Machine Learning. Machine learning is commonly limited to a single operational modality. To enable image, sound and language comprehension simultaneously would require machines to reuse knowledge and understand concepts from multimodal data. The project aims to build a sparse model and present a set of innovative algorithms to enhance model generalisation for addressing distributional and semantic shifts and minimise the computational and labelling co ....Towards Evolvable and Sustainable Multimodal Machine Learning. Machine learning is commonly limited to a single operational modality. To enable image, sound and language comprehension simultaneously would require machines to reuse knowledge and understand concepts from multimodal data. The project aims to build a sparse model and present a set of innovative algorithms to enhance model generalisation for addressing distributional and semantic shifts and minimise the computational and labelling costs for training multimodal systems. Its outcomes will enable evolvable learning of models to suit varying testing scenarios after deployment and whilst reducing energy consumption and carbon emission. The application of these techniques could benefit sectors such as E-commerce, agriculture and transport.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100800
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Polymer micropatches applied to the skin for integrated capture and detection of circulating biomarkers. The purpose of this project is to develop a rapid and integrated technology for user-friendly biomarker detection at the point-of-care. We expect the device to rapidly detect proteins and/or antibodies, without the need for highly trained health workers or access to scientific laboratories.
Rethinking Topological Persistence. This project aims to address the lack of transferability and uncertainty-awareness in AI models. Despite their success, AI models are met with bias and uncertainty when deployed in the real world. As a result, they are rarely used in high-risk industries like cybersecurity or transport. This project expects to build uncertainty-awareness into models by teaching them to return UNKNOWN when they encounter a previously unseen thing, instead of misclassifying it. ....Rethinking Topological Persistence. This project aims to address the lack of transferability and uncertainty-awareness in AI models. Despite their success, AI models are met with bias and uncertainty when deployed in the real world. As a result, they are rarely used in high-risk industries like cybersecurity or transport. This project expects to build uncertainty-awareness into models by teaching them to return UNKNOWN when they encounter a previously unseen thing, instead of misclassifying it. Further, the evaluation methods to be developed will not rely on access to test data, allowing cost-effective, private, and safe AI for high-stakes decision support. The outcomes will benefit Australia by accelerating economic investment and fostering greater social acceptance of AI.Read moreRead less
Cryptographic Protocols: Proofs and Designs. Cryptographic protocols are the foundation for protection of the critical electronic communications infrastructure on which much of commerce and industry rely. They will increasingly be required in emerging technologies such as ad-hoc wireless networks and sensor networks. This project will provide the ability to design new and efficient protocols with a mathematical guarantee of security. The resulting practical protocols will benefit all users of el ....Cryptographic Protocols: Proofs and Designs. Cryptographic protocols are the foundation for protection of the critical electronic communications infrastructure on which much of commerce and industry rely. They will increasingly be required in emerging technologies such as ad-hoc wireless networks and sensor networks. This project will provide the ability to design new and efficient protocols with a mathematical guarantee of security. The resulting practical protocols will benefit all users of electronic communications who require security for their information. This includes the financial industries, government, commerce and domestic users.Read moreRead less
Cryptographic Protocols from Pairings: Proofs and Designs. Modern society has become critically dependent on information and communications infrastructures. At the same time, the development of e-commerce is being slowed by lack of confidence in its security. By providing increased assurance and enhanced cryptographic security protocols this research will improve the dependability of the nation's information and communications infrastructure, as well as encourage the growth of e-commerce. Throu ....Cryptographic Protocols from Pairings: Proofs and Designs. Modern society has become critically dependent on information and communications infrastructures. At the same time, the development of e-commerce is being slowed by lack of confidence in its security. By providing increased assurance and enhanced cryptographic security protocols this research will improve the dependability of the nation's information and communications infrastructure, as well as encourage the growth of e-commerce. Through the expertise and experience gained with this project, Australia's excellence in information security research will be reinforced. The training of PhD and Honours students will provide a much needed source of highly trained information security professionals.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101056
Funder
Australian Research Council
Funding Amount
$380,156.00
Summary
Rational Design of Plasmonic Nanoassemblies for Rapid and Multiplexed Point-of-Care Diagnosis by Surface-enhanced Raman Spectroscopy (SERS). The central aim of this project is to develop a novel technology/sensor platform for rapid, quantitative, multiplexed and highly sensitive point-of-care diagnostics using surface-enhanced Raman spectroscopy (SERS) as the read-out approach. Three-dimensional plasmonic superstructures as novel SERS labels will be synthesised and characterised at single-partic ....Rational Design of Plasmonic Nanoassemblies for Rapid and Multiplexed Point-of-Care Diagnosis by Surface-enhanced Raman Spectroscopy (SERS). The central aim of this project is to develop a novel technology/sensor platform for rapid, quantitative, multiplexed and highly sensitive point-of-care diagnostics using surface-enhanced Raman spectroscopy (SERS) as the read-out approach. Three-dimensional plasmonic superstructures as novel SERS labels will be synthesised and characterised at single-particle level and the choice of optimal SERS-active three-dimensional superstructures for use will be guided by empirical structure-activity correlations in combination with computer simulations. Tumour biomarkers for breast cancer will be employed as the model target for establishing the detection platform in a portable configuration for point-of-care diagnostics.Read moreRead less
Temporal Graph Mining for Anomaly Detection. This project aims to develop new technologies to detect anomalous patterns from dynamic networked data. Anomalies in networked data are commonly seen but are often hidden within the complex interconnections of large-scale, heterogeneous, and dynamic data, rendering existing detection methods ineffective. This project expects to design novel temporal graph mining techniques to compress large-scale networks, unify heterogeneous information, and enable l ....Temporal Graph Mining for Anomaly Detection. This project aims to develop new technologies to detect anomalous patterns from dynamic networked data. Anomalies in networked data are commonly seen but are often hidden within the complex interconnections of large-scale, heterogeneous, and dynamic data, rendering existing detection methods ineffective. This project expects to design novel temporal graph mining techniques to compress large-scale networks, unify heterogeneous information, and enable label-efficient anomaly detection. The performance will be assessed in social and business networks, with significant benefits to governments and businesses in many critical applications, including cyberbullying detection, malicious account detection, and cyber-attack detection.Read moreRead less
Responsible modelling respecting privacy, data quality, and green computing. With the unprecedented growing impact of data on science, the economy and society, there comes the need for responsible data science practices which are accountable for the social good. This project aims to investigate the challenging problem of how to provide responsible data management, spanning across privacy-aware data exploration, resilient modelling to cope with imperfect data, and efficient model architectures fo ....Responsible modelling respecting privacy, data quality, and green computing. With the unprecedented growing impact of data on science, the economy and society, there comes the need for responsible data science practices which are accountable for the social good. This project aims to investigate the challenging problem of how to provide responsible data management, spanning across privacy-aware data exploration, resilient modelling to cope with imperfect data, and efficient model architectures for resource-constrained environments. This will be achieved by developing theories and techniques for complex real-world multi-modal data retrieval throughout the data life-cycle. The expected outcomes will significantly contribute to building capability in emerging technologies in the context of responsible data science. Read moreRead less