Dan joined the Statistical Science department in 2021 after obtaining his PhD in Applied and Computational Mathematics at University College Dublin, Ireland, where he received the “Knut Bertram Broberg Memorial Medal” (UCD's Best PhD in Mechanics – 2021). This medal is awarded annually to the best PhD thesis in the College of Engineering, Mathematical and Physical Sciences (EMPS) at UCD.
His research interests to date have focused on numerical solvers/high-performance computing (HPC) frameworks and the intersection with data-driven approaches. The applications of which have centred on ocean and atmospheric modelling. He has experience with developing highly efficient open source numerical approaches which utilise high performance computing frameworks and machine/statistical learning methods.
numerical solution of partial differential equations, data assimilation, statistical emulation, uncertainty quantification, high performance computing.
- Reguly IZ, Giles D, Gopinathan D, Quivy L, Beck JH, Giles MB, Guillas S & Dias F. (2018) The VOLNA-OP2 tsunami code (version 1.5), Geoscientific Model Development, 11, 4621-4635. https://doi.org/10.5194/gmd-11-4621-2018
- Giles D, Kashdan E, Salmanidou DM, Guillas S & Dias F. (2020) Performance analysis of Volna-OP2 – massively parallel code for tsunami modelling, Computers and Fluids, 209, 104649. https://doi.org/10.1016/j.compfluid.2020.104649
- Giles D, Gopinathan D, Guillas S & Dias F. (2021) Faster than real time tsunami warning with associated hazard uncertainties, Frontiers of Earth Science, 8, 560. https://doi.org/10.3389/feart.2020.597865