Minghan Zhu
About Minghan Zhu
Minghan Zhu is a Perception Research Engineer Intern specializing in Deep Learning at TuSimple, with a strong academic background in perception, SLAM, and autonomous driving. He holds a PhD from the University of Michigan, a Master's in Mechanical Engineering, and a Bachelor's degree from Tsinghua University.
Work at TuSimple
Minghan Zhu is currently employed at TuSimple as a Perception Research Engineer Intern specializing in Deep Learning. He has been part of the team since 2021, contributing to projects that focus on enhancing perception systems for autonomous vehicles. His internship responsibilities include working on monocular 3D vehicle detection, which is essential for improving the safety and efficiency of autonomous driving technologies.
Education and Expertise
Minghan Zhu has an extensive educational background in engineering and perception technologies. He earned a Doctor of Philosophy (PhD) from the University of Michigan, where he studied Perception, SLAM, and autonomous driving from 2018 to 2022. Prior to this, he obtained a Master's degree in Mechanical Engineering from the same institution, studying from 2016 to 2018. His undergraduate studies were completed at 清华大学, where he earned a Bachelor's degree in Automotive Engineering from 2012 to 2016.
Research Focus
Minghan Zhu's research primarily concentrates on vision- and lidar-based 3D perception in the fields of autonomous driving and robotics. His work aims to advance the understanding and implementation of perception systems that are critical for the development of safe and reliable autonomous vehicles. This focus aligns with his current role at TuSimple, where he applies his academic knowledge to practical challenges in the industry.
Background
Minghan Zhu completed his secondary education at 长沙市雅礼中学 from 2009 to 2012. His foundational studies in engineering began with a Bachelor's degree in Automotive Engineering at 清华大学, which set the stage for his advanced studies in Mechanical Engineering and later, his PhD at the University of Michigan. This educational trajectory has equipped him with a strong understanding of the principles of engineering and autonomous systems.