About Mohammad Motamed Mohammad Motamed Postdoctoral Research Fellow, Stochastic Numerics Research Group numerical analysis scientific computing Mohammad Motamed worked as a Postdoctoral Fellow at Professor Raul F. Tempone's Stochastic Numerics Research Group (STOCHNUM) at King Abdullah University of Science and Technology (KAUST). Mohammad is a visiting researcher at ICES, The University of Texas at Austin, USA. Research Interests Mohammad's research interests included Numerical Analysis and Scientific Computing, Deterministic and stochastic partial differential equations, Multiscale problems, modeling and simulation, and high-frequency wave propagation problems. Selected Publications M. Motamed and F. Nobile and R. Tempone. A Projects Related Projects 2010 Earthquake Source Validation Tue, Jun 1 2010 - Sun, Nov 1 2015 We are developing a new method based on the Bayesian inference technique for the ground motion computations. The ultimate goal of this project is to have a better understanding of earthquake distribution. Stochastic Partial Differential Equations (SPDEs) Tue, Jun 1 2010 - Sat, Jun 1 2013 SPDEs are partial differential equations with random terms which are due to uncertainty in the models. They arise in many multidimensional physical problems. Examples for the source of uncertainty include the variability of soil permeability in subsurface aquifers and heterogeneity of materials with microstructure. We work on the analysis and computation of elliptic, parabolic and hyperbolic equations with random data.
Earthquake Source Validation Tue, Jun 1 2010 - Sun, Nov 1 2015 We are developing a new method based on the Bayesian inference technique for the ground motion computations. The ultimate goal of this project is to have a better understanding of earthquake distribution.
Stochastic Partial Differential Equations (SPDEs) Tue, Jun 1 2010 - Sat, Jun 1 2013 SPDEs are partial differential equations with random terms which are due to uncertainty in the models. They arise in many multidimensional physical problems. Examples for the source of uncertainty include the variability of soil permeability in subsurface aquifers and heterogeneity of materials with microstructure. We work on the analysis and computation of elliptic, parabolic and hyperbolic equations with random data.
