Projects per year
Personal profile
Research interests
With ever increasing computational power it has become possible to solve physical problems of an unprecedented complexity. I am interested in numerical techniques for simulating systems at all length scales, from high resolution atmospheric models to subatomic particles. As a member of the Numerical Analysis group I work on the development of fast numerical algorithms and their implementation in efficient and parallel computer code.
In the past I contributed to several areas of Scientific Computing, most recently as a PostDoc (University of Bath, Sep 2011 - Jan 2015), where I developed and improved massively parallel solvers for the pressure correction in numerical weather- and climate forecast models; this work was carried out in collaboration with the Met Office as part of the GungHo! project. Prior to this I worked as a research scientist at the Met Office (Nov 2009 - Aug 2011). My main task was the improvement and OpenMP parallelisation of the NAME model code for the prediction of the transport of atmospheric pollutants, such as volcanic ash. I am a physicist by training and received a PhD in computational particle physics from the University of Edinburgh (Nov 2009), after studying in Germany and Scotland.
The focus of my current research is the development of fast solvers for PDEs, with particular focus on writing efficient, yet maintainable, code in suitable frameworks such as DUNE and firedrake/PyOP2. Together with external partners I apply those techniques to real-life problems such as numerical weather- and climate forecast models. In addition to implementations on massively parallel CPU clusters I am interested in modern manycore architectures (GPUs and Xeon Phis). I also work on the application of Multilevel Monte Carlo methods to atmospheric dispersion modelling and the development of a performance portable framework for atomistic simulations in physics and chemistry.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Collaborations and top research areas from the last five years
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MGHyPE: An ExaHyPE version with a multigrid solver
Mueller, E. (PI)
Engineering and Physical Sciences Research Council
1/12/22 → 31/03/25
Project: Research council
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Research and development of a multigrid preconditioner for the LFRic hybridized solver
Mueller, E. (PI) & Griffith, M. (Researcher)
1/12/21 → 31/03/22
Project: Central government, health and local authorities
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IAA – Accelerating climate- and weather-forecasts with faster multigrid solvers
Mueller, E. (PI) & Griffith, M. (Researcher)
Engineering and Physical Sciences Research Council
1/06/21 → 30/06/22
Project: Research council
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Research output
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Learning efficient and provably convergent splitting methods
Kreusser, L. M., Lockyer, H. E., Müller, E. H. & Singh, P., 14 Nov 2024.Research output: Working paper / Preprint › Preprint
File26 Downloads (Pure) -
Deep Surrogate Accelerated Delayed-Acceptance Hamiltonian Monte Carlo for Bayesian Inference of Spatio-Temporal Heat Fluxes in Rotating Disc Systems
Deveney, T., Mueller, E. H. & Shardlow, T., 1 Sept 2023, In: SIAM/ASA Journal on Uncertainty Quantification. 11, 3, p. 970-995 26 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (SciVal)27 Downloads (Pure) -
Exact conservation laws for neural network integrators of dynamical systems
Müller, E., 1 Sept 2023, In: Journal of Computational Physics. 488, 24 p., 112234.Research output: Contribution to journal › Article › peer-review
Open Access5 Citations (SciVal) -
Hybridised multigrid preconditioners for a compatible finite element dynamical core
Betteridge, J., Cotter, C., Gibson, T., Griffith, M., Melvin, T. & Müller, E., 1 Jul 2023, In: Journal of Computational Physics. 149, 755, p. 2454-2476 23 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (SciVal)1 Downloads (Pure) -
A new algorithm for electrostatic interactions in Monte Carlo simulations of charged particles
Saunders, W., Grant, J. & Müller, E., 1 Apr 2021, In: Journal of Computational Physics. 430, 22 p., 110099.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (SciVal)157 Downloads (Pure)