Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and meth ....Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and methods and an efficient algorithm implemented in software, which would broadly benefit the field of complex trait genetics. Methods to estimate genotype–environment interaction effects at the genomic level would help elucidate complex biological systems, including human genetic response to changing environmental factors and the potential adaptation of animals to changing environmental conditions.Read moreRead less
Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key featur ....Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key feature in biology, which relates to dissecting the complex mechanism of association and interaction. The proposed statistical model implemented in a context of a novel design based on multiple GWAS data sets is a paradigm shifting-tool with applications to multiple industries.Read moreRead less
Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show h ....Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show how to design context-aware systems that are usable and whose autonomic decisions can be trusted. Additional benefits include increased scientific competitiveness of Australia, strengthened collaboration with international research institutions, and high quality graduates (PhDs, Masters, Honours).Read moreRead less
3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environmen ....3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environments and open up new possibilities for applications in fields such as virtual reality, architecture, and city planning. The proposed 3D diffusion models will also enhance the accuracy of computer vision tasks related to 3D scene understanding, such as object detection, tracking, and semantic segmentation.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not o ....Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not only practical solutions for protecting sensitive data recorded in blockchain but also crucial techniques to make the blockchain accountable for practical applications with enhanced security. This project provides significant benefits, such as building a trusted environment for sensitive transactions in the digital economy.Read moreRead less
Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – w ....Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – what the data means and what it can be used for – with sophisticated, scalable computational techniques to mine and present information from the huge volumes of raw data. This project is expected to improve productivity and quality of big data analytics and visualisation in critical domains.Read moreRead less
Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider a ....Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider attacks. The outcomes of the project will incorporate new security constraints and policies raised by emerging technologies to enable better protection of sensitive information. Read moreRead less
An Empirically Derived Experimentally Validated Framework for Interactions in Information Environments. This project will investigate and design ways of interacting with the information infrastructure that maintain natural social interactions, take advantage of physical space and utilise our extensive human abilities to recognise and manipulate physical objects.
Expected outcomes include:
? a theoretical framework that describes the range of possible interactions that mediate information b ....An Empirically Derived Experimentally Validated Framework for Interactions in Information Environments. This project will investigate and design ways of interacting with the information infrastructure that maintain natural social interactions, take advantage of physical space and utilise our extensive human abilities to recognise and manipulate physical objects.
Expected outcomes include:
? a theoretical framework that describes the range of possible interactions that mediate information between the physical and virtual worlds.
? a prototype instrumented information environment that demonstrates and validates naturalistic information transactions identified in the framework.
This research is highly innovative in its field. It will use an iterative cycle of video observation, interaction analysis, user-centred device design, deployment and evaluation.
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An Integrative and Interactive Approach for Co-estimation of Multiple Sequence Alignment and Phylogeny Reconstruction. In this project innovative IT methods will be developed to assist biologists to solve complex and important biological problems. Many important applications in computational biology need very accurate and reliable tools for multiple sequence alignment and phylogeny reconstruction. Unfortunately, current existing tools are unreliable and are prone to serious errors when applied t ....An Integrative and Interactive Approach for Co-estimation of Multiple Sequence Alignment and Phylogeny Reconstruction. In this project innovative IT methods will be developed to assist biologists to solve complex and important biological problems. Many important applications in computational biology need very accurate and reliable tools for multiple sequence alignment and phylogeny reconstruction. Unfortunately, current existing tools are unreliable and are prone to serious errors when applied to large and divergent biological sequences. The success of this project will not only make significant contribution to the relevant research fields, but also help achieve goals in certain real-life biological research projects which are unique and important to Australia.Read moreRead less