Panqu Wang
About Panqu Wang
Panqu Wang is the Director of Deep Perception at TuSimple, where he has worked since 2020. He holds a Ph.D. in Electrical and Computer Engineering from the University of California, San Diego, and has extensive experience in deep learning and perception systems for autonomous vehicles.
Current Role at TuSimple
Panqu Wang serves as the Director of Deep Perception at TuSimple, a role he has held since 2020. Based in San Diego County, California, he leads initiatives focused on the development of perception systems for autonomous vehicles. His responsibilities include overseeing a team dedicated to hiring for various perception-related positions, particularly those emphasizing deep learning and fusion technologies.
Previous Experience at TuSimple
Prior to his current position, Panqu Wang held several roles at TuSimple. He worked as a Senior Manager in Deep Learning for eight months in 2019, and as a Research Scientist from 2017 to 2018. Additionally, he served as a Senior Research Scientist from 2018 to 2019. His tenure at TuSimple has been marked by a focus on advancing technologies related to autonomous driving.
Education and Expertise
Panqu Wang earned his Ph.D. in Electrical and Computer Engineering from the University of California, San Diego, where he studied from 2011 to 2017. He also completed a Bachelor of Science in Electrical Engineering at Fudan University from 2007 to 2011. His academic background includes significant research experience, including roles as a Graduate Student Researcher and Staff Research Assistant at UC San Diego.
Internship Experience
Throughout his academic career, Panqu Wang gained practical experience through various internships. He interned at eBay Inc. as a PhD Technical Intern in 2013 and at Hewlett-Packard as a Research Associate Intern from 2014 to 2015. He also completed an internship at TuSimple in 2016, contributing to his foundational knowledge in deep learning and perception systems.
Research Contributions
Panqu Wang has been actively involved in the perception aspect of autonomous driving trucks since at least 2020. His work focuses on enhancing the capabilities of perception systems, which are critical for the safe and efficient operation of autonomous vehicles. His contributions in this area reflect a commitment to advancing technology in the autonomous driving sector.