Arash Bakhtiari
About Arash Bakhtiari
Arash Bakhtiari is a Staff Software Engineer with expertise in parallel algorithms and high-performance computing. He has a strong academic background in computational science and has worked at several notable companies, including Blaize, Intel Corporation, and ReliaTec GmbH.
Work at Blaize
Arash Bakhtiari has been employed at Blaize as a Staff Software Engineer since 2022. In this role, he contributes to the development of high-performance computing solutions, specifically focusing on deep learning applications. Prior to his current position, he served as a Senior Software Engineer at Blaize from 2020 to 2022. His work involves utilizing advanced programming skills to optimize software performance.
Education and Expertise
Arash Bakhtiari holds a Doctor of Philosophy (PhD) in High Performance Computing from the Technical University of Munich, where he studied from 2013 to 2017. He also earned a Master of Science (M.Sc. with honors) in Computational Science and Engineering from the same institution between 2011 and 2013. Additionally, he completed two Bachelor of Science (B.Sc.) degrees in Physics, one from Karlsruhe Institute of Technology (KIT) and another from Ludwig-Maximilians-Universität München. His academic background includes a focus on parallel algorithms, computational fluid dynamics, and high-performance computing.
Professional Experience
Before joining Blaize, Arash Bakhtiari worked at several notable companies. He was a Software Developer at ReliaTec GmbH from 2009 to 2014 in the Munich Area, Germany. He then worked as a Software Engineer at Intel Corporation from 2018 to 2019. Following that, he served as a Deep Learning Software Engineer at Plumerai from 2019 to 2020 in London, United Kingdom. His diverse experience spans various roles in software development and engineering.
Technical Skills
Arash Bakhtiari possesses advanced programming skills in CUDA and OpenCL, which he utilizes to optimize software performance for deep learning tasks. His expertise in parallel algorithms is a significant aspect of his work in high-performance computing. He has a strong background in both academic and industrial research, particularly in computational fluid dynamics, and has collaborated on interdisciplinary projects that integrate physics and computational science.