Navid A
About Navid A
Navid A is a Senior System Engineer with extensive experience in system optimization for autonomous driving projects. He has worked with several companies, including Komatsu Mining and TuSimple, and holds multiple degrees in engineering and optics from the University of Arizona and UC Irvine.
Work at TuSimple
Navid A has been employed at TuSimple as a Senior System Engineer since 2021. In this role, he focuses on optimizing system performance and cost for autonomous driving projects. He operates effectively within an Agile methodology environment, contributing to the engineering development process. His responsibilities include ensuring forward and backward traceability for every requirement using the corporate requirement management tool.
Previous Experience at Komatsu Mining
Navid A worked at Komatsu Mining from 2015 to 2021, initially serving as a System Engineer II - V&V for three years in Tucson, Arizona. He then advanced to the position of Senior System Engineer, where he continued for another three years. During his tenure, he contributed to the sensor system architecture for autonomous trucks, specifically focusing on GNSS, IMU, and EO Cameras.
Education and Expertise
Navid A holds a Master's degree in Optics/Optical Sciences and a Bachelor's degree in Electrical and Computer Engineering, both from the University of Arizona. He also completed a Graduate Professional Certificate in Optical System Engineering at UC Irvine. Additionally, he achieved an Agile System Certificate in 2020 and a Google Project Management Professional Certificate through Coursera in 2022.
Research and Teaching Assistant Role
From 2008 to 2010, Navid A served as a Graduate Research and Teaching Assistant at the University of Arizona. This role provided him with valuable experience in academic research and teaching methodologies, further enhancing his expertise in engineering and system design.
Technical Skills and Contributions
Navid A is experienced in utilizing data analysis tools such as Matlab for system engineering tasks. He has collaborated with teams to design sensing architecture and perform Failure Mode and Effects Analysis (FMEA). His work includes significant contributions to the localization algorithm team, enhancing the overall functionality of autonomous systems.