Discovery Early Career Researcher Award - Grant ID: DE240101049
Funder
Australian Research Council
Funding Amount
$432,485.00
Summary
Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumou ....Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumour, (2) novel models for the diffusion of an evolving rumour, and (3) techniques for detecting the diffusion sources of the original rumour and its mutations. This not only will constitute a major advancement in the theory and application of rumour study but also lead the decision-makers in debunking rumours.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100550
Funder
Australian Research Council
Funding Amount
$358,248.00
Summary
Quantum refinement of DNA X-ray structures. DNA carries the genetic map of life and refinement of its x-ray structures is a key tool to understand its functions. Standard refinement, however, relies strongly on empirical geometry constraints, and it is known that these can induce unphysical features. Quantum mechanical (QM) methods have now evolved to a level that offers an intriguing way out of this dilemma. In this project, state-of-the-art QM methods will be applied to DNA x-ray structures, a ....Quantum refinement of DNA X-ray structures. DNA carries the genetic map of life and refinement of its x-ray structures is a key tool to understand its functions. Standard refinement, however, relies strongly on empirical geometry constraints, and it is known that these can induce unphysical features. Quantum mechanical (QM) methods have now evolved to a level that offers an intriguing way out of this dilemma. In this project, state-of-the-art QM methods will be applied to DNA x-ray structures, and a unique quantum refinement scheme will be developed. Such a scheme will provide crystallographers with a new tool to determine DNA structures with greater accuracy and it will offer benefits to many areas of the life sciences that depend on such accurate structures.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100999
Funder
Australian Research Council
Funding Amount
$295,020.00
Summary
Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-maki ....Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-making processes require intensive consideration of all possible outcomes in the modelled environment. In comparison to previous optimisation methods, the FBSDE approach is easier to work with and much more informative. The project's main potential applications are multiplayer games with mean-field interaction and financial markets with partial information.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101467
Funder
Australian Research Council
Funding Amount
$419,778.00
Summary
The geometric structure of spatial noise. Spatial noise is ubiquitous in nature and science: as interference in medical imaging, in oceanography, in the modelling of telecommunication networks etc. Despite this diversity of sources, spatial noise can be studied in a unified way by considering mathematical models that capture its essential features. This project aims to study spatial noise by analysing its geometric structure, for instance by considering the number of contour lines of the noise, ....The geometric structure of spatial noise. Spatial noise is ubiquitous in nature and science: as interference in medical imaging, in oceanography, in the modelling of telecommunication networks etc. Despite this diversity of sources, spatial noise can be studied in a unified way by considering mathematical models that capture its essential features. This project aims to study spatial noise by analysing its geometric structure, for instance by considering the number of contour lines of the noise, and the way these lines connect different regions of space. The project further aims to apply this analysis to construct statistical tests that can distinguish different classes of spatial noise, with potential applications across all of the disciplines mentioned above.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101196
Funder
Australian Research Council
Funding Amount
$439,012.00
Summary
Data-Driven Design for 3D Printed Materials with Tailored Fracture Response. Fracture is the main source of material failure and may cause serious engineering disasters and even death. This project aims to develop a Data-Driven Design System that intelligently optimizes local materials and architectures for heterogeneous structures with desired fracture response, and enhancing their mechanical fracture properties including stiffness, strength, toughness, and failure displacement. It will open up ....Data-Driven Design for 3D Printed Materials with Tailored Fracture Response. Fracture is the main source of material failure and may cause serious engineering disasters and even death. This project aims to develop a Data-Driven Design System that intelligently optimizes local materials and architectures for heterogeneous structures with desired fracture response, and enhancing their mechanical fracture properties including stiffness, strength, toughness, and failure displacement. It will open up a new and promising research field in mechanics and data-driven science that deals with intractable inverse problems in broad engineering fields. Economic, high-performance, and customized 3D printed structural materials will be generated to benefit national corporations and enterprises and meet the high-end industry needs.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100993
Funder
Australian Research Council
Funding Amount
$293,520.00
Summary
Mathematics of importance: The optimal importance sampling algorithm for estimating the probability of a black swan event. Rare event simulation and modelling is critical to our understanding of high-cost hard-to-predict events such as nuclear accidents, natural disasters, and financial crises. Quantitative analysis of such high-impact events demands the accurate estimation of the probability of occurrence of such rare events. In realistic models this probability is very difficult to estimate, ....Mathematics of importance: The optimal importance sampling algorithm for estimating the probability of a black swan event. Rare event simulation and modelling is critical to our understanding of high-cost hard-to-predict events such as nuclear accidents, natural disasters, and financial crises. Quantitative analysis of such high-impact events demands the accurate estimation of the probability of occurrence of such rare events. In realistic models this probability is very difficult to estimate, because exact simple analytical formulas are not available and the existing estimation methods fail spectacularly. There is an urgent need for new efficient methodology. This project develops a new Monte Carlo method that will be able to estimate reliably and accurately rare-event probabilities. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101683
Funder
Australian Research Council
Funding Amount
$448,354.00
Summary
Computational Design of Defect-Free Additive Manufactured Ceramic Structure. Despite its importance and potential, ceramic additive manufacturing (AM) is facing significant challenge for its inherent material characteristics prone to shrinkage and fracture during fabrication process. This project aims to fill a knowledge gap by developing a new computational design framework for a commonly-used indirect AM process. It will address a range of AM issues, such as residual stress/distortion, cracks, ....Computational Design of Defect-Free Additive Manufactured Ceramic Structure. Despite its importance and potential, ceramic additive manufacturing (AM) is facing significant challenge for its inherent material characteristics prone to shrinkage and fracture during fabrication process. This project aims to fill a knowledge gap by developing a new computational design framework for a commonly-used indirect AM process. It will address a range of AM issues, such as residual stress/distortion, cracks, and uncertainty in a nondeterministic context. The study is expected to establish novel design methodologies for ceramic AM with process modelling, robust/reliable optimisation, and fracture-based design. It will provide ceramic industry with a new framework for biomedical, aerospace and mechanical applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101147
Funder
Australian Research Council
Funding Amount
$294,336.00
Summary
Predicting extremes when events occur in bursts. This project seeks to advance knowledge in extreme value theory. Extreme value theory is essential to quantify risks in complex systems, such as the risk of network failures. Current statistical models for the occurrence of extremes assume that events happen regularly. This assumption, however, is at odds with human actions and many biological and physical events, which occur in bursts. There is a strong need to understand the effect of such ‘burs ....Predicting extremes when events occur in bursts. This project seeks to advance knowledge in extreme value theory. Extreme value theory is essential to quantify risks in complex systems, such as the risk of network failures. Current statistical models for the occurrence of extremes assume that events happen regularly. This assumption, however, is at odds with human actions and many biological and physical events, which occur in bursts. There is a strong need to understand the effect of such ‘bursty dynamics’ on the frequency and magnitude of extreme events. This project aims to develop extreme value theory for bursty events and thus lay the mathematical groundwork for the estimation and prediction of extremes in a variety of scientific contexts.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100053
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Quantitatively probing the nanoscale plasticity of a single grain boundary. This project aims to study grain boundaries, which are important in the mechanical behaviour of nanomaterials. However, the exact contribution of individual grain boundaries to mechanical properties is not well understood, affecting advanced materials design. This project will use in-situ deformation transmission electron microscopy techniques to reveal how individual grain boundaries deform and interact with dislocation ....Quantitatively probing the nanoscale plasticity of a single grain boundary. This project aims to study grain boundaries, which are important in the mechanical behaviour of nanomaterials. However, the exact contribution of individual grain boundaries to mechanical properties is not well understood, affecting advanced materials design. This project will use in-situ deformation transmission electron microscopy techniques to reveal how individual grain boundaries deform and interact with dislocations, and to link directly the structures and orientation of individual grain boundaries with mechanical behaviours. Expected results are better structural design of advanced metallic nanomaterials with superior mechanical performance.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100887
Funder
Australian Research Council
Funding Amount
$409,398.00
Summary
Robust Designs Inspired by Biological Chiral Structures. This project aims to understand the mechanics of biological chiral structures in order to create novel engineering designs. The project expects to gain new insights into mechanisms which enable these structures to accommodate complex and random loads through experimental, analytical and numerical approaches. Expected outcomes include a computational platform for designing highly efficient and mechanically robust products, and new designs s ....Robust Designs Inspired by Biological Chiral Structures. This project aims to understand the mechanics of biological chiral structures in order to create novel engineering designs. The project expects to gain new insights into mechanisms which enable these structures to accommodate complex and random loads through experimental, analytical and numerical approaches. Expected outcomes include a computational platform for designing highly efficient and mechanically robust products, and new designs such as wind turbine blades and hypodermic needles as applications of the platform. The products should have great potential in energy harvesting and biomedical engineering. The platform should provide significant benefits to engineering through performance improvement and robustness enhancement.Read moreRead less