Yimu Wang
About Yimu Wang
Yimu Wang is a Principal Engineer and Localization Lead at Motional, where he has worked since 2018. He has a background in perception engineering and has contributed to various self-driving technology projects.
Current Role at Motional
Yimu Wang serves as the Principal Engineer and Localization Lead at Motional, a position he has held since 2018. In this role, he manages a team dedicated to developing next-generation localization software. His responsibilities include overseeing the maintenance and improvement of sensor fusion systems, which are critical for the functionality of autonomous vehicles. Wang's leadership in this area is vital for advancing Motional's technology in the self-driving sector.
Previous Experience at Motional
Prior to his current role, Yimu Wang worked at Motional in various capacities. He began as an Automated Driving Perception R&D Engineer from 2016 to 2017, where he contributed to the development of key technologies. He later transitioned to the position of Senior Perception Engineer for five months in 2017. His work during this time laid the groundwork for his current responsibilities in localization.
Experience at Uber
Before joining Motional, Yimu Wang worked at Uber as a Perception/Deep-learning Engineer for seven months in 2016. During his tenure, he focused on developing perception algorithms that are essential for the operation of autonomous vehicles. This experience contributed to his expertise in deep learning and perception systems, which he later applied in his roles at Motional.
Educational Background
Yimu Wang earned his Bachelor's degree from Sichuan University, where he studied from 2010 to 2014. He furthered his education at Carnegie Mellon University, attending from 2014 to 2015. His academic background provided a strong foundation in engineering principles, which he has applied throughout his career in the autonomous driving industry.
Contributions to Self-Driving Technology
Throughout his career, Yimu Wang has made significant contributions to self-driving technology. He developed a calibration system from scratch and created a map-based localization system. Additionally, he played a role in developing a lidar tracking system and a pedestrian-related planning system, both of which are essential for the safe operation of autonomous vehicles. His contributions have been integral to programs such as Aptiv's self-driving car initiative, which achieved 100,000 paid rides in the Lyft network.