David (Xunda) Zhou
About David (Xunda) Zhou
David (Xunda) Zhou serves as the Tech Lead Manager for Perception at Cyngn, where he has worked since 2022. He holds both a Bachelor's and a Master's degree in Electrical and Computer Engineering from Carnegie Mellon University and has extensive experience in software engineering and AI, particularly in the field of autonomous driving.
Work at Cyngn
David Zhou currently serves as the Tech Lead Manager for Perception at Cyngn, a position he has held since 2022. His role involves overseeing the development of perception systems for autonomous vehicles. Prior to this, he worked at Cyngn in various capacities, including Software Engineer and Tech Lead for AI. His tenure at Cyngn has been marked by significant contributions to the perception team, focusing on data-efficient solutions and the development of deep learning models for Level 4 autonomous systems.
Education and Expertise
David Zhou holds both a Bachelor's and a Master's degree in Electrical and Computer Engineering from Carnegie Mellon University. His educational background has equipped him with a strong foundation in engineering principles, which he applies in his professional roles. His expertise spans areas such as autonomous driving, robotics, and emerging technologies, including augmented and virtual reality.
Background
David Zhou's career began with internships at SAP and Autodesk, where he gained experience in analytics and machine learning. He later worked as a Research Assistant at Carnegie Mellon University, contributing to projects in the field of engineering. His professional journey includes multiple roles at Cyngn, where he has progressively taken on more responsibility, ultimately leading to his current position as Tech Lead Manager.
Achievements
Throughout his career, David Zhou has successfully managed vendor collaborations to enhance autonomous driving capabilities through mapping, localization, and data annotation. He has played a crucial role in building a robust perception team at Cyngn, focusing on innovative and data-efficient solutions. His leadership in developing advanced deep learning models has significantly contributed to the company's efforts in autonomous vehicle technology.