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
Discovery Early Career Researcher Award - Grant ID: DE140100088
Funder
Australian Research Council
Funding Amount
$378,628.00
Summary
Computing with matrix groups and Lie algebras: new concepts and applications. Computational algebra combines symbolic computation and pure research in algebra, and is concerned with the design of algorithms for solving mathematical problems endowed with algebraic structure. Matrix groups and Lie algebras are prominent algebraic objects describing the natural concept of symmetry. Despite being very common and important in science, there is a paucity of algorithms to study their structure. This pr ....Computing with matrix groups and Lie algebras: new concepts and applications. Computational algebra combines symbolic computation and pure research in algebra, and is concerned with the design of algorithms for solving mathematical problems endowed with algebraic structure. Matrix groups and Lie algebras are prominent algebraic objects describing the natural concept of symmetry. Despite being very common and important in science, there is a paucity of algorithms to study their structure. This project will develop deep new mathematical theories for computing with these objects, leading to ground-breaking advances in computational algebra, and providing powerful tools facilitating new research, including in other sciences. The new functionality will be used to solve two classification problems in group and Lie theory.Read moreRead less
Making software more reliable using a new model for entropies of computers' internal state. A new mathematical analysis of the way computer systems exchange data between their components has led to novel design approaches for the programs implementing those systems. This reduces their cost and increases their reliability, with improvements ranging from small-scale smart devices to widely distributed internet protocols.
Composition tree algorithms for large matrix groups. This project aims to develop new algorithms for analysing groups. A group is a rather simple mathematical structure – an example is the set of all integers considering only the operations of addition and subtraction. Since the symmetries of an object form a group, groups are ubiquitous throughout mathematics and elsewhere in science. Because it is frequently necessary to determine a group's properties, there is great interest in finding effici ....Composition tree algorithms for large matrix groups. This project aims to develop new algorithms for analysing groups. A group is a rather simple mathematical structure – an example is the set of all integers considering only the operations of addition and subtraction. Since the symmetries of an object form a group, groups are ubiquitous throughout mathematics and elsewhere in science. Because it is frequently necessary to determine a group's properties, there is great interest in finding efficient algorithms for analysing groups. A matrix group is a common type of group whose elements are square matrices. This project plans to employ a novel approach to designing algorithms for analysing large matrix groups, a task which is currently impossible using existing algorithms.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101137
Funder
Australian Research Council
Funding Amount
$312,000.00
Summary
Two-scale numerical modelling of coupled transport in heterogeneous media. Groundwater constitutes a vital part of water resources in Australia, however, the quality of this water is susceptible to contamination. This project aims to develop an innovative two-scale mathematical model for contaminant transport that accounts for small-scale heterogeneities found in the unsaturated zone of an aquifer located between the ground surface and the underlying groundwater. The project aims to develop valu ....Two-scale numerical modelling of coupled transport in heterogeneous media. Groundwater constitutes a vital part of water resources in Australia, however, the quality of this water is susceptible to contamination. This project aims to develop an innovative two-scale mathematical model for contaminant transport that accounts for small-scale heterogeneities found in the unsaturated zone of an aquifer located between the ground surface and the underlying groundwater. The project aims to develop valuable environmental insights, a simulation tool that will help in making decisions regarding the future management of Australian groundwater resources, and a general two-scale modelling and simulation framework for other important environmental and industrial problems involving coupled transport in heterogeneous media.Read moreRead less
Symmetry and computation. The overall objective of the project is to explore connections between symmetry and computation, especially the theory and algorithms that facilitate the use of groups in computational science. The main outcome will be theoretically fast algorithms and implementations to drive applications in the sciences and for secure communication.
Phylodynamics for Single Cell Genomics . This project generates the mathematical framework required to look at single cell data in developmental systems and tissues. All cells in a multi-cellular organism derive from a single ancestral cell, generally the fertilised egg cell. Phylodynamics provides a framework to analyse and model this data, by connecting the shared ancestry of cells in an organism to the cell population and tissue dynamics. By developing the mathematical and statistical foundat ....Phylodynamics for Single Cell Genomics . This project generates the mathematical framework required to look at single cell data in developmental systems and tissues. All cells in a multi-cellular organism derive from a single ancestral cell, generally the fertilised egg cell. Phylodynamics provides a framework to analyse and model this data, by connecting the shared ancestry of cells in an organism to the cell population and tissue dynamics. By developing the mathematical and statistical foundations for the analysis of single cell data in a phylodynamic framework we will establish a powerful new computational tools for the analysis of tissues and developmental processes. Read moreRead less
Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In partic ....Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In particular, it plans to work on the problem of security of statistical databases and privacy of streaming data. This would be underpinned by a study of anonymisation and homomorphic encryption. The expected outcomes are new theoretical results, new algorithms and protocols applicable to at least some of the current significant problems in information security.Read moreRead less
Visualisation of multidimensional physics data. This project aims to link multi-parameter models used in physics to explore experimental data, and statistical tools for multivariate analysis and visualisation. It addresses an important gap in the understanding of phenomenological physics analyses containing many simultaneously important parameters. This is expected to improve the understanding of results in multi-parameter models.
Effective computational methods for nonlinear cone optimisation with industrial applications. This project brings together a number of national and international researchers whose combined expertise will focus on solving optimisation problems arising in a range of industries. The work will result in new cutting edge optimisation technology that can benefit industry and the community.