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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.

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Research Output 2013 2018

1 Citations
Molecular dynamics
molecular dynamics
Computer systems
Parallel architectures

Multilevel Monte Carlo and Improved Time Stepping Methods in Atmospheric Dispersion Modelling

Katsiolides, G., Mueller, E., Scheichl, R., Shardlow, T., Giles, M. B. & Thomson, D. J. 1 Feb 2018 In : Journal of Computational Physics. 354, p. 320-343 23 p.

Research output: Contribution to journalArticle

Numerical methods
Monte Carlo method
Differential equations
Monte Carlo methods
2 Citations
Open Access
Flow simulation
Flow Simulation
Aspect Ratio
Aspect ratio
Open Access
Partial differential equations
partial differential equations
elliptic differential equations
1 Citations
Open Access
Langevin Equation
Stochastic Equations
Differential equation
Discrete random variable
Strong Approximation