Hussam Al Daas is a researcher in the Computational Mathematics Group at the STFC Rutherford Appleton Laboratory. He completed his PhD with Laura Grigori at Inria-Paris and the Sobonne University (previously University of Pierre and Marie Curie) on Solving linear systems arising from reservoirs modeling. Prior to joining RAL he spent eighteen months as a postdoctoral fellow at the Computational methods in Systems and Control Theory group at the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
His research interests lie in the fields of numerical linear and multilinear algebra as well as high performance and parallel computing. In particular, he is interested in developing numerical methods for low rank tensor computations as a model order reduction technique as well as the development of iterative methods to solve large sparse systems of equations. In addition to theoretical issues surrounding these methods he is also interested in using them to efficiently solve problems from applications with a particular interest in the systems arising from PDEs.