Abdourahmane Diaw
About Abdourahmane Diaw
Abdourahmane Diaw is a computational physicist specializing in magnetohydrodynamics and particle methods for plasma accelerator concepts. He currently works at Oak Ridge National Laboratory and has previously held positions at Los Alamos National Laboratory and RadiaSoft LLC.
Work at Oak Ridge National Laboratory
Abdourahmane Diaw has been employed as a Computational Physicist at Oak Ridge National Laboratory since 2022. His role involves applying advanced computational techniques to various physics problems, particularly in the field of plasma physics. He utilizes high-performance computing methods to enhance research outcomes and improve experimental processes.
Previous Experience at Los Alamos National Laboratory
Prior to his current position, Abdourahmane Diaw worked at Los Alamos National Laboratory as a Postdoctoral Research Associate from 2017 to 2021. During his four years there, he specialized in magnetohydrodynamics and particle methods, contributing to research in plasma accelerator concepts. His work involved high-performance computing techniques, including OpenMP and MPI.
Experience at RadiaSoft LLC
Abdourahmane Diaw served as a Research Scientist at RadiaSoft LLC from 2021 to 2022. In this role, he focused on molecular dynamics modeling for high energy density plasmas. His expertise in this area contributed to the development of advanced computational models and simulations.
Education and Expertise in Physics
Abdourahmane Diaw holds a Doctor of Philosophy (PhD) in Physics from École Polytechnique, where he studied from 2010 to 2013. He also earned a Master of Science (MS) in Plasma and High-Temperature Physics from Université de Bordeaux, completing his studies from 2007 to 2009. His educational background provides a strong foundation for his research in computational physics.
Research Focus and Techniques
Abdourahmane Diaw specializes in several key areas within computational physics. His research includes magnetohydrodynamics, particle methods for plasma accelerator concepts, and laser-plasma interaction modeling. He also incorporates machine learning methods for beam alignment in neutron scattering experiments, enhancing the precision of experimental setups.