Ramtin Kardan

Mechanical & Systems Engineer at Thread

Ramtin Kardan has work experience in various roles and companies. From May 2020 to present, they have worked as a Robotics Engineer at Thread. In this role, they have been responsible for developing robotics systems. From October 2021 to September 2022, they held another position as a Robotics Engineer at Thread. In this role, they likely continued their work on robotics systems. Additionally, from May 2020 to September 2021, they worked as a Computer Vision Engineer at Thread, where their focus was likely on developing computer vision systems. Prior to joining Thread, Ramtin worked as a Research Officer at Universiti Teknologi PETRONAS from August 2017 to December 2018. Ramtin also worked as a Research Assistant at Universiti Teknologi PETRONAS from October 2016 to July 2017. Furthermore, they gained experience at Siemens working on the KV-MRT Project from May 2015 to December 2015.

Ramtin Kardan pursued their education at various institutions, starting with the National Organization for Development of Exceptional Talents (NODET), where they completed their Highschool and Pre-University education. The exact years for this period are not provided.

Ramtin then went on to attend Universiti Teknologi PETRONAS, where they completed their Bachelor's degree in Mechanical Engineering from 2012 to 2016.

Continuing their education, Ramtin Kardan enrolled at the University of North Dakota, undertaking the pursuit of a Master of Science (MS) degree in Mechanical Engineering. Ramtin completed this program from 2019 to 2022.

Overall, Ramtin Kardan has a strong educational background in Mechanical Engineering, spanning from their high school years to their Master's degree.

Location

Grand Forks, United States

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Thread

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Thread specializes in enterprise-scale autonomous data collection that delivers precise inspection insights. Its suite of tools empowers users to programmatically capture knowledge into consistent and replicable plans. Any visual inspection activity being performed by a pilot in GPS-accessible locations today can be automated through Airtonomy.These tools can be used to make full end-to-end automated workflows as they have done with its wind product.


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51-200

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