Zhibei Ma
About Zhibei Ma
Zhibei Ma is a Machine Learning Infra Engineer at TuSimple in San Diego, California, with a background in statistics and computer science. He has over seven years of experience in research and engineering roles, including previous positions at the University of Southern California and TuSimple.
Work at TuSimple
Zhibei Ma has been employed at TuSimple since 2021, serving as a Machine Learning Infra Engineer. This role is based in San Diego, California, where he has contributed to the development and optimization of machine learning infrastructure for autonomous driving technology. Prior to his current position, he worked at TuSimple as a Research Engineer from 2017 to 2021, focusing on research initiatives that support the company's mission in the autonomous vehicle sector.
Education and Expertise
Zhibei Ma holds a Master's degree in Computer Science from the University of Southern California, where he studied from 2015 to 2017. He also completed a Bachelor of Engineering in Communication Sciences and Engineering at Fudan University from 2011 to 2015. Additionally, he participated in a Summer Course in Statistics at Washington University in St. Louis in 2014, which lasted for 11 months. His educational background provides a strong foundation in both computer science and statistical analysis.
Background
Before joining TuSimple, Zhibei Ma worked as a Student Researcher at the University of Southern California from 2015 to 2017. During this time, he was involved in projects within the Robotic Embedded Systems Laboratory (RESL), gaining practical experience in robotics and embedded systems. His background in research and engineering has equipped him with the skills necessary for his current role in machine learning infrastructure.
Professional Experience
Zhibei Ma has accumulated significant experience in the field of machine learning and robotics. His tenure at TuSimple includes four years as a Research Engineer, where he focused on advancing the company's research efforts in autonomous driving. His earlier role as a Student Researcher at the University of Southern California provided him with hands-on experience in robotic systems, further enhancing his expertise in the domain.