Computational mathematics

Computational mathematics

The Computational Mathematics research program actively studies theoretical aspects of computational algorithms.

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About

Our group has 6 continuing and 6 contract staff. The group members have wide range of research interests in developing numerical methods for solving various application problems. We focus on algorithm designs, numerical implementation and theoretical analysis.

Capabilities

The group members have long term experience with their research areas. In particular the research of our group addresses the following aspects of computational and applied mathematics:

  • Computational PDEs
  • Computational topology and algebraic geometry
  • Environmental science
  • Inverse problems
  • Modelling
  • Numerical linear algebra
  • Optimisation
  • Plasma physics
  • Theoretical astrophysics

Reasons to work with us

  • Our group members have long term experience with their research areas which typically tie with practical applications and government or industrial partners. Examples include fluid dynamics and the River Darling Basin Authority, inverse problems and the Australian Signals Directorate, fusion energy and the Australian Nuclear and Science and Technology Organisation, and seismology and GeoSciences Australia.
  • Completed HDR students routinely find employment in top international research agencies (e.g. US Department of Energy), or pursue higher degree studies in world leading universities in US and UK (e.g. Oxford).
  • Exposure to broader research challenges through the Mathematics and Computational Sciences Seminar Series, a joint initiative between MSI and Computational Science.

Projects

As we move into exascale computing, and beyond, the chance of a fault occurring in the system increases. Traditional approaches to building resilience into the system, such as check-pointing, may become too expensive.

Student intake

Open for Honours, Masters, PhD students

Status

Potential

People

Approximation of High Dimensional Data Sets using Sparse Grid Techniques.

Student intake

Open for Honours, Masters, PhD students

Status

Potential

People

Investigate representation theorems for lattice operators based on mathematical morphology and develop efficient machine learning methods based on them for applications in signal and image processing.

Student intake

Open for Bachelor, Honours, Masters, PhD students

Status

Potential

People

Mimetic and stable numerical methods for nonlinear shallow water equations

Student intake

Open for students

Status

Potential

The efficient solution of the Navier Stokes equation provides many challenges. Of particular interest is the efficient description and implementation of free boundaries.

Student intake

Open for Honours, Masters, PhD students

Status

Potential

People

The modelling of high dimensional data sets pose a particular challenge both for approximation and the parallel implementation. In this project we investigate the parallelization of sparse grid methods.

Student intake

Open for Honours students

Status

Potential

People

Members

Convenor

Qinian Jin

Associate Professor

Emeritus

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Emeritus Professor

Researcher

Barry Croke

Senior Fellow / Associate Professor

Markus Hegland

Emeritus Professor

Professor

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MSI-Google Fellow

Steve Roberts

Emeritus Professor

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Associate Professor / Director of Research ANU-ASD Co-Lab

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Associate Professor and Director, Mathematical Data Science Centre

Student

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