Allan P. Engsig-Karup
Assistant Professor Allan P. Engsig-Karup recieved an M.Sc. in Coastal engineering and applied math from the Technical University of Denmark (DTU) in January 2003. During the studies, 6 months of 2001 was spend as an international student at Adelaide University, Adelaide, Australia. Following graduation he was awarded a three year fellowship to begin work towards a Ph.D. at DTU at Coastal, Maritime and Structural Engineering Section in the Department of Mechanical Engineering, DTU.
During the three years of study on the development of a novel solution strategy of the so-called high-order Boussinessq-type equations using the Discontinous Galerking Finite Elemenent Methods, a seven month visit abroad was spend in the period 2004-2005 in the Division of Applied Mathematics at Brown University, Providence, USA, and a one month visit a Rice University, Texas, USA. In August 2006, he recieved a Ph.D. in Coastal engineering and applied math from the Department of Mechanical Engineering, DTU, Denmark.
Following graduation in August 2006, he was awarded a Postdoctoral Fellowship from the Danish Technical Research Council (STVF) for research in coastal engineering and applied math. A new state-of-the-art efficient and robust multigrid preconditioned solution strategy was developed for the development of a new numerical model for nonlinear wave problems in three dimensions. During this work a new state-of-the-art strategy for the efficient and scalable modelling of nonlinear water waves in 3D wave tanks was developed using the classical finite difference method. Currently, I am collaborating with the Computational Hydraulics Group at DTU Mechnics on improving and extending these models further.
As of mid August 2008, he was appointed Assistant Professor of Scientific Computing at Section for Scientific Computing, Department of Informatics and Mathematical Modeling, DTU, Denmark. In this position the teaching and research focus will be on numerical solution techniques for solving ordinary and partial differential equations for time-dependent problems on high-performance computing ressources.