Dr. Ben Mather

Computational Geophysicist

EarthByte Group


I am a Postdoc in the EarthByte Group at the University of Sydney. I am interested in the inversion of thermochemical properties of the lithosphere subject to available geophysical data and their uncertainties. Inversions that couple multiple datasets ultimately improve the precision and understanding of the thermochemical evolution of the Earth.

I am passionate about open source software! On this website you will find links to repositories where source code is available with examples of how to reproduce peer-reviewed benchmarks and published results. You will also find code snippets that I have found useful - and maybe you will too!


  • Data assimilation
  • Bayesian inversion
  • Thermochemical evolution
  • Geothermal heat flux


  • PhD in Earth Science, 2016

    The University of Melbourne

  • Bachelor of Science (Hons), 2011

    Monash University



Computational Geophysicist

Sydney Informatics Hub

November 2018 – Present Sydney
Coupling of geodynamic codes with surface processes and groundwater flow.

  • Applied to the Sydney Basin.
  • Parallel computing frameworks built on PETSc.
  • Optimisation using deep learning algorithms.

Postdoctoral Research Scientist

Dublin Institute for Advanced Studies

June 2017 – October 2018 Dublin
3D integrated geothermal modelling of Ireland.

  • Forward and inverse modelling of geothermal heat flux.
  • Assimilate Curie depth, seismic velocity, gravity anomly, surface heat flow data.

Research assistant

University of Melbourne

February 2016 – June 2017 Melbourne
Developer of Quagmire, a code for parallel surface processes modelling

  • Multiple meshing algorithms for unstructured, regular, and orthogonal meshes.
  • Mesh decomposition and solving routines built on PETSc.
  • Landscape evolution using stream flow algorithms.

Recent Posts

Turning up the heat on Earth temperature modelling

Dr Ben Mather and Prof Louis Moresi from AuScope’s Simulation, Analysis and Modelling (SAM) program have recently developed a novel, speedy and data-driven way to model the temperature of Earth’s crust in southeastern Australia. Their work has since attracted a grant from the International Association of Mathematical Geosciences (IAMG) to refine the new method and investigate earth temperatures further afield in Alaska.

Introducing Stripy

Geodynamicists from Sydney and Australian National universities have developed Stripy, a software module that allows scientists to efficiently place GIS ‘wrapping paper’ around the spherical Earth ‘present’. This is the first module to be built for a common scientific programming language like Python, that supports such ‘wrapping’, or mapping features. Here, developer Dr Ben Mather explains Stripy’s key functions for the AuScope Earth modelling community.

Continuous Integration with Travis CI

A bit of a late-comer to this game, I’ve just discovered the merits of so-called “continuous integration”. In a Journal of Open Source Software (JOSS) review for stripy, one of the reviewers suggested Travis CI as a way to test if the code is working correctly.

May the 4th be with you...

In an Underworld release far, far away… Geodynamicists struggle to model planetary dynamics due to the Cartesian Empire. Physical observations suffer inappropriate meshing and projections bend minds. The Underworld team builds the ultimate weapon to erase the Cartesian nightmare based on the ancient practice of the Cubed-Sphere mesh.

Multiprocessing in Python

Most of the codes I develop run in parallel using MPI (Message Passing Interface) using the python wrapper, mpi4py. There is a reason why highly scalable programs use this approach, and that is because each processor handles its own chunk of memory and communicates with other processors only when it’s needed.

Recent Publications

Adjoint inversion of the thermal structure of Southeastern Australia

An efficient inversion framework that gives improved estimates of the thermal state of the crust in Victoria using heat flow measurements and Curie depth in a joint inversion using 3D geological models, and numerical models of thermal diffusion. The outcome of this work is an estimation of the basal heat flux, thermal properties and the heat production rates for the various domains in the model together with uncertainty information.

PyCurious: A Python module for computing the Curie depth from the magnetic anomaly

PyCurious is a Python package for computing the depth to 580°C from maps of the Earth’s magnetic anomaly using a Bayesian …

Stripy: A Python module for (constrained) triangulation in Cartesian coordinates and on a sphere.

The triangulation of scattered points is a common problem in science and engineering when local neighbourhood information is required …

Constraining the geotherm beneath the British Isles from Bayesian inversion of Curie depth: Integrated modelling of magnetic, geothermal and seismic data

The temperature distribution in the crust, and associated uncertainty, was simulated from the ensemble of Curie depth realisations assigned to a lower thermal boundary condition of a crustal model (inc. sedimentary thickness, Moho depth, heat production, thermal conductivity), constructed from various geophysical and geochemical data sets.

Probabilistic surface heat flow estimates assimilating palaeoclimate history: new implications for the thermochemical structure of Ireland

Regions where surface temperature has increased since past glaciation events, such as Ireland, underestimate the heat output of the …

Recent & Upcoming Talks



Basin Genesis Hub

Coupling the evolution of mantle flow, crustal deformation, erosion and sedimentary processes using open-source modelling tools.


To develop a robust and unique model of temperature within Ireland’s crust and to produce a 3D temperature atlas of the country.


Computational tools for the geodynamics community. Built in Australia, used all over (and under) the world