Domokos Sármány has more than ten years of academic and industrial experience in scientific computing and numerical modelling. Domokos is currently responsible for improving I/O scalability in ECMWF's weather forecasting system. His work forms part of the externally-funded MAESTRO project.
- Numerical methods
- Scientific computing
- Galerkin methods
- High-resolution (shock-capturing) schemes
- Systems of mixed partial differential and algebraic equations
- Time-stepping schemes for differential equations
- High-performance computing
- C++ code modernisation (C++11/14/17)
- Object-oriented programming
Domokos received his MSc degree in meteorology form Eötvös Loránd University, Budapest, Hungary. His thesis work was on numerical weather prediction, in which he investigated the computation treatment of boundary conditions for limited-area models. He went on to obtain a PhD degree in numerical analysis from the University of Twente, the Netherlands. As part of his research there, he developed and analysed discontinuous Galerkin finite-element methods (DG-FEM) for the effective simulation of electromagnetic wave propagation.
Domokos continued his career as a post-doctoral researcher at the University of Leeds. His area of interest was to create and analyse a novel numerical finite-element-type modelling technique -- called residual distribution -- for the simulation of fluid dynamics, in particular for applications that involve shock capturing and/or atmospheric effects.
Domokos moved to the private sector in 2013 and joined Process Systems Enterprise. Initially as a software developer then as a senior software developer, he was part of a team that oversaw the numerical engine that underlay the company's flagship gPROMS platform. The engine solves mathematical problems that arise from scientific computing: large sparse systems of differential equations, mathematical optimisation, parameter estimation and sensitivity analysis.
Domokos joined the Scalability Team at ECMWF in April 2018. His current work includes I/O scalability as well as memory and data awareness in data-handling workflows.
Member of the Institute of Mathematics and its Applications
Peer-reviewed journal articles
- D. Sármány and M.E. Hubbard and M. Ricchiuto. A moving mesh implementation of upwind residual distribution. Comput. Math. Appl., submitted.
- D. Sármány and M.E. Hubbard. Upwind residual distribution for shallow-water ocean modelling. Ocean Model., 64:1–11.
- D. Sármány, M.E. Hubbard and M. Ricchiuto. Unconditionally stable space-time discontinuous residual distribution for shallow-water flows. J. Comput. Phys., 253:86–113.
- D. Sármány, M.A. Botchev, and J.J.W. van der Vegt. Time-integration methods for finite element discretisations of the second-order Maxwell equation. Comput. Math. Appl., 3:528–543.
- D. Sármány, F. Izsák, and J.J.W. van der Vegt. Optimal penalty parameters for symmetric discontinuous Galerkin discretisations of the time-harmonic Maxwell equations. J. Sci. Comput., 44(3):219–254.
- D. Sármány, M.A. Botchev, and J.J.W. van der Vegt. Dispersion and dissipation error in high-order Runge-Kutta discontinuous Galerkin discretisations of the Maxwell equations. J. Sci. Comput., 33(1):47–74.
Technical reports
- D. Sármány, M.A. Botchev, J.J.W. van der Vegt and J.G. Verwer. Comparing DG and Nédélec finite element discretisations of the second-order time-domain Maxwell equation. Technical Report 1912, Department of Applied Mathematics, University of Twente, Enschede, December 2009.
- D. Sármány, F. Izsák, and J.J.W. van der Vegt. High-order accurate discontinuous Galerkin method for the indefinite time-harmonic Maxwell equations. Technical Report 1889, Department of Applied Mathematics, University of Twente, Enschede, January 2009.
