Pooya Movahed
About Pooya Movahed
Pooya Movahed is a Computational Scientist at ExxonMobil with extensive experience in fluid dynamics and high-performance computing.
Current Position at ExxonMobil
Pooya Movahed currently holds the position of Computational Scientist at ExxonMobil in the United States. He began this role in 2019, bringing extensive experience in computational fluid dynamics and high-performance computing to the company. His work focuses on high-speed turbulent multi-phase flows relevant to energy sciences.
Previous Experience at Siemens PLM Software
Before joining ExxonMobil, Pooya Movahed worked as an Application Support Engineer at Siemens PLM Software in Plano, Texas, United States. His tenure lasted from 2018 to 2019 for 7 months. During this period, he provided critical support and solutions for software applications, leveraging his computational and engineering background.
Research Roles at Major Universities
Pooya Movahed has held several research and teaching positions at prestigious institutions. He served as Postdoctoral Research Associate at the University of Illinois at Urbana-Champaign from 2014 to 2018 and as a Graduate Student Research Assistant at the University of Michigan from 2010 to 2014. He also gained teaching experience as a Graduate Teaching Assistant for Fluid Mechanics at the University of Michigan in 2011 and as an Undergraduate Teaching Assistant for Heat Transfer at the University of Tehran in 2008.
Educational Background in Mechanical Engineering
Pooya Movahed holds a Doctor of Philosophy in Mechanical Engineering from the University of Michigan, achieved between 2011 and 2014. He also earned his Master's degree in Mechanical Engineering from the same institution from 2009 to 2011. His foundational studies in Mechanical Engineering were completed at the University of Tehran, where he obtained a Bachelor of Science from 2004 to 2009.
Expertise in Computational Fluid Dynamics
Pooya Movahed specializes in computational fluid dynamics, particularly in shock-capturing schemes and turbulence modeling for high-speed compressible flows. His research includes the application of these techniques to biomedical engineering, such as studying cavitation in soft materials. He employs direct numerical simulation (DNS) and implicit large eddy simulation (ILES) techniques and is experienced in developing codes for high-performance computing environments.