Ashwin Arunmozhi
About Ashwin Arunmozhi
Ashwin Arunmozhi is a Sensor Systems Engineer currently working at Motional, with a background in autonomous vehicle technology and extensive experience in the automotive industry. He has held various engineering roles, including positions at Ford Motor Company and Daimler, and has completed advanced studies in automotive systems.
Work at Motional
Ashwin Arunmozhi has been employed at Motional as a Sensor Systems Engineer since 2020. His role involves working on advanced sensor systems for autonomous vehicles. Based in Pittsburgh, Pennsylvania, he contributes to the development and integration of sensor technologies that enhance vehicle perception and safety.
Education and Expertise
Ashwin Arunmozhi holds a Master of Science and Engineering in Automotive Systems from Kettering University, completed between 2016 and 2018. He also earned a Bachelor’s Degree in Automobile Engineering from PSG College of Technology from 2010 to 2014. His educational background is complemented by the completion of the Udacity Self-driving Car Nanodegree, which focused on autonomous vehicle technology. He possesses expertise in camera sensor calibration, radar and camera sensor fusion, and training deep neural networks.
Background
Ashwin Arunmozhi has a diverse background in the automotive industry. He worked as a Systems Engineer for Autonomous Vehicles at Ford Motor Company from 2018 to 2020. Prior to that, he served as a Graduate Research Assistant at Kettering University, focusing on NVH and Body Structures from 2016 to 2017 and on Autonomous Vehicles from 2017 to 2018. His early experience includes internships and training at several automotive companies, including Ashok Leyland, Hyundai Motor India Ltd., and Daimler.
Achievements
During his academic career, Ashwin led the college SAE BAJA team, gaining practical experience in automotive engineering and leadership. He developed environment perception algorithms for the SAE/GM AutoDrive challenge while pursuing his graduate studies. His technical skills include proficiency in modifying deep neural networks such as AlexNet, ResNet, and GoogLeNet, which are essential for advancements in autonomous vehicle technology.