Machine Learning and Optimisation


Trans-D Bayesian fitting of spectroscopic data

This project aims at improving geochemical observables from Raman and Infrared spectroscopic data through the use of Trans-Dimentional Bayesian approaches used in Seismology.



iEarth is a consortium of scientists from the university, government and industry sectors with interests in the development and application of inversion methodologies for the Earth Sciences.


TerraWulf is a networked ‘Beowulf’ cluster of computers set up at RSES to provide convenient high end computing power for a range of demanding geoscience problems.

Tomography in Irregular Cells

Seismic tomography with irregular parameterization.

Regionalized Upper Mantle seismic model of Earth

Global tomographic images correlate strongly with major tectonic features. The level of velocity variations is highly concentrated in the upper mantle and most globally recorded earthquakes occur in, or around, subducting slabs. This leads us to a new strategy in global tomography. We insert a-priori information by designing an irregular parameterisation which incorporates these observations.


Neighbourhood Algorithm

The neighbourhood algorithm is a two-stage numerical procedure for non-linear geophysical inverse problems. It also has applications as a direct search technique for global optimization.

Fast Marching Method

The Fast Marching Method (FMM) is a grid based numerical scheme for tracking the evolution of monotonically advancing interfaces via finite difference solution of the Eikonal equation.




A model linking the properties and structure of silicate melts