Discovery Early Career Researcher Award - Grant ID: DE240100006
Funder
Australian Research Council
Funding Amount
$444,847.00
Summary
Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techn ....Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techniques and create world-leading and publicly available software. These new techniques and software may ultimately be able to solve some of the most complex optimisation problems in research and industry, such as improving long-term climate predictions and designing 3D-printed medical implants.Read moreRead less
Tractable topological computing: Escaping the hardness trap. Computational topology is a young and energetic field that uses computers to solve complex geometric problems driven by pure mathematics, and with diverse applications in biology, signal processing and data mining. A major barrier is that many of these problems are thought to be fundamentally and intractably hard. This project aims to defy such barriers for typical real-world inputs by fusing geometric techniques with technologies from ....Tractable topological computing: Escaping the hardness trap. Computational topology is a young and energetic field that uses computers to solve complex geometric problems driven by pure mathematics, and with diverse applications in biology, signal processing and data mining. A major barrier is that many of these problems are thought to be fundamentally and intractably hard. This project aims to defy such barriers for typical real-world inputs by fusing geometric techniques with technologies from the field of parameterised complexity, creating powerful, practical solutions for these problems. It is expected to shed much-needed light on the vast and puzzling gap between theory and practice, and give researchers fast new software tools for large-scale experimentation and cutting-edge computer proofs.Read moreRead less
Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to bu ....Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to build practical mathematical models for droplet impaction, spreading and evaporation on leaf surfaces, and experimentally calibrate and validate the models. The software is expected to drive the development of agrichemical products that increase retention, minimise environmental impacts, and reduce costs for end-users.Read moreRead less
Complexity of group algorithms and statistical fingerprints of groups. This project aims to shape the next generation of efficient randomised algorithms in the field of group theory, the mathematics of symmetry. Fundamental mathematics underpins modern technological tasks such as web searches, sorting and data compression. This project aims to determine characteristic statistical fingerprints of key building-block groups. These group statistics lead to much faster procedures to essentially facto ....Complexity of group algorithms and statistical fingerprints of groups. This project aims to shape the next generation of efficient randomised algorithms in the field of group theory, the mathematics of symmetry. Fundamental mathematics underpins modern technological tasks such as web searches, sorting and data compression. This project aims to determine characteristic statistical fingerprints of key building-block groups. These group statistics lead to much faster procedures to essentially factor huge groups into smaller building-block groups in a manner akin to factoring an integer into its prime factors. The anticipated goal is to include the outcomes in publicly available symbolic algebra computer packages. As the theory of symmetry has broad applications in the mathematical and physical sciences, there is the potential for far reaching benefits.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100473
Funder
Australian Research Council
Funding Amount
$410,154.00
Summary
Effective integration of human and automated analyses for security testing. This DECRA project aims to significantly improve the performance of current state-of-the-art automated security testing approaches, enabling them to discover more security bugs in strict time constraints. The key innovation of the project is its novel way to embrace human element to leverage the ingenuity of the developers. This project will help companies improve the security and reliability of their products, thwarting ....Effective integration of human and automated analyses for security testing. This DECRA project aims to significantly improve the performance of current state-of-the-art automated security testing approaches, enabling them to discover more security bugs in strict time constraints. The key innovation of the project is its novel way to embrace human element to leverage the ingenuity of the developers. This project will help companies improve the security and reliability of their products, thwarting cyberattacks that cost Australian business $29 billion each year. The knowledge from this project will be transferred and integrated into higher education subjects to train the next generations of software developers, who are responsible to build security-critical systems that we all rely on now and in the future.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100040
Funder
Australian Research Council
Funding Amount
$442,302.00
Summary
Quality Assurance of Mobile Applications by Effective Testing and Repair. This project aims to create advanced techniques that will enable software engineers to effectively develop quality assured and robust software systems. This project expects to generate new and innovative approaches that automate software testing and repair. The expected outcomes of this project include new knowledge of software engineering, development of an automated and cost-effective testing system with improved coverag ....Quality Assurance of Mobile Applications by Effective Testing and Repair. This project aims to create advanced techniques that will enable software engineers to effectively develop quality assured and robust software systems. This project expects to generate new and innovative approaches that automate software testing and repair. The expected outcomes of this project include new knowledge of software engineering, development of an automated and cost-effective testing system with improved coverage, greater bug detection and repair, and faster testing protocols. This should provide significant benefits to software users by providing reliable and user-friendly systems and to software companies to position Australia as a global leader in software development and technological advancement.Read moreRead less
Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Mapping the Effectiveness of Automated Software Testing. This project aims to help software engineers build complex software systems in far more reliable and cost-effective ways. It takes an interdisciplinary approach by applying machine learning techniques to automatically test complex software systems. Expected outcomes include a novel methodology for assessing the strengths and weaknesses of test suites generated by automated software testing techniques and the approaches required for generat ....Mapping the Effectiveness of Automated Software Testing. This project aims to help software engineers build complex software systems in far more reliable and cost-effective ways. It takes an interdisciplinary approach by applying machine learning techniques to automatically test complex software systems. Expected outcomes include a novel methodology for assessing the strengths and weaknesses of test suites generated by automated software testing techniques and the approaches required for generating high-quality test cases. Such advances are urgently needed to avoid disasters when deploying software systems in the real world.Read moreRead less
Ownership-based Alias Analysis for Securing Unsafe Rust Programs. This project aims to develop an ownership-based alias analysis as a complement to Rust's ownership type system for improving Rust's memory safety. This project, therefore, expects to deliver an alias analysis foundation that can provide stronger memory safety guarantees than the state-of-the-art in detecting memory-safety violations and security vulnerabilities in real-world Rust programs that use unsafe language features. The exp ....Ownership-based Alias Analysis for Securing Unsafe Rust Programs. This project aims to develop an ownership-based alias analysis as a complement to Rust's ownership type system for improving Rust's memory safety. This project, therefore, expects to deliver an alias analysis foundation that can provide stronger memory safety guarantees than the state-of-the-art in detecting memory-safety violations and security vulnerabilities in real-world Rust programs that use unsafe language features. The expected outcomes are a deployable ownership-based alias analysis in the Rust compiler and an industrial-strength open-source framework. These outcomes are expected to provide significant benefits in improving software quality and security in Rust, an emerging language that offers both performance and safety.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100035
Funder
Australian Research Council
Funding Amount
$3,009,457.00
Summary
Human-centric Model-driven Software Engineering. This project aims to find fundamentally new ways to capture and use human-centric software requirements during model-driven software engineering and verifying that systems meet these requirements. There are major issues with misaligned software applications in terms of accessibility, usability, emotions, personality, age, gender, and culture. This project aims to address these through new conceptual foundations and modelling techniques for their s ....Human-centric Model-driven Software Engineering. This project aims to find fundamentally new ways to capture and use human-centric software requirements during model-driven software engineering and verifying that systems meet these requirements. There are major issues with misaligned software applications in terms of accessibility, usability, emotions, personality, age, gender, and culture. This project aims to address these through new conceptual foundations and modelling techniques for their support during software engineering. The intended outcomes are enhanced theory, models, tools and capability for next-generation software engineering with these critical elements. Significant benefits are expected to include greatly improved software quality, developer productivity and cost savings.Read moreRead less