Juncong Fei
About Juncong Fei
Juncong Fei is a Senior Data Scientist at Torc Robotics in Stuttgart, Germany, specializing in AI sensor fusion and automated driving. He has a strong academic background with a PhD candidacy from Karlsruhe Institute of Technology and extensive experience in various roles within the automotive industry.
Work at Torc Robotics
Juncong Fei has been employed as a Senior Data Scientist at Torc Robotics since 2022. He is based in Stuttgart, Baden-Württemberg, Germany. In this role, he focuses on data science applications within the field of automated driving, contributing to the development of advanced technologies that enhance vehicle perception and decision-making capabilities.
Education and Expertise
Juncong Fei pursued his education at multiple institutions. He is a PhD candidate at Karlsruhe Institute of Technology (KIT), where he studied AI Sensor Fusion, LiDAR-based Perception, and Automated Driving from 2019 to 2023. He also holds a Master's degree in Electrical Engineering and Information Technology from KIT, completed from 2016 to 2019. His academic background includes a Bachelor's degree in Electrical and Electronics Engineering from Tongji University, obtained from 2011 to 2016.
Background in Racing and Engineering
Before his current role, Juncong Fei gained significant experience in the racing and automotive sectors. He served as Team Leader and Technical Director for the DRe15 at 同济大学DIAN Racing车队 from 2012 to 2015 in Shanghai, China. He was also a Driverless Team Member at KA-RaceIng e.V. in Karlsruhe from 2016 to 2017. His experience includes working as a Deep Learning Intern at Volkswagen AG, focusing on Environment Perception in 2018.
Research and Development Experience
Juncong Fei has a strong research background, having worked as a PhD Researcher at Stellantis from 2019 to 2022, where he specialized in AI Sensor Fusion and Automated Driving. Additionally, he completed his Master Thesis at Volkswagen AG, focusing on Sensor Fusion, Object Detection, and Tracking from 2018 to 2019. His roles have involved applying advanced data science techniques to improve vehicle perception systems.