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The Scientific computation group
In the Scientific Computation group we apply advanced modelling techniques and numerical algorithms to represent and solve complex, real-world problems in industry and nature, with an emphasis on overall performance and efficient scaling when deployed on massively parallel architectures. We collaborate broadly across the University and beyond, with many successful multi-disciplinary projects spanning mechanical engineering to microbiology.
Seminars
SPH with Physically Consistent Contact Angles: Simulating Droplet Bouncing on Partial Wetting Surface
Numerical simulation of microfluidics on complex surfaces holds significant industrial and scientific value. However, existing numerical methods still face challenges...
On a Shrink-and-Expand Technique for Symmetric Block Eigensolvers
In symmetric block eigenvalue algorithms, such as the subspace iteration algorithm and the locally optimal block preconditioned conjugate gradient (LOBPCG)...
From the Classical Sherman–Morrison Formula to Iterative Refinement and a Self-Correcting Modification for Improved Stability
Owing to its simplicity and efficiency, the Sherman-Morrison (SM) formula has seen widespread use across various scientific and engineering applications...
Posts
Members of the Scientific Computation group organise a minisymposium within SIAM PP 2026
Author: Mantas Mikaitis SIAM Conference on Parallel Processing for Scientific Computing (PP26) took place on March 3-6, 2026, in Berlin, Germany, at the Zuse Institute...
New Preprint: Accurate Models of NVIDIA Tensor Cores
Author: Faizan A. Khattak Introduction Recent TOP500 supercomputers show a clear architectural trend: over half of the systems in the TOP500 support mixed-precision matrix multiplication...
ENUMATH 2025 Minisymposium on Probabilistic Rounding
Author: Mantas Mikaitis The European Conference on Numerical Mathematics and Advanced Applications (ENUMATH) took place on September 1-5, 2025, in Heidelberg, Germany, on the Heidelberg...