Bohui Fang
About Bohui Fang
Bohui Fang is a Research Engineer with expertise in designing scenario logic modules for autonomous vehicles. He has a background in machine learning and algorithms, having worked at notable institutions such as TuSimple and Carnegie Mellon University.
Current Role at TuSimple
Bohui Fang currently serves as a Research Engineer at TuSimple, a company specializing in autonomous vehicle technology. Since joining in 2021, he has focused on developing and testing scenario logic modules for autonomous driving systems. His work involves creating logic specifically for 'intersection' scenarios, which are critical for safe and efficient navigation in urban environments.
Previous Experience at TuSimple
Prior to his current position, Bohui Fang worked as a Research Engineering Intern at TuSimple in 2020. During this three-month internship in San Diego, California, he gained hands-on experience in the field of autonomous vehicles, contributing to the development of innovative solutions in the industry.
Research Background at Carnegie Mellon University
Bohui Fang was a Research Intern at Carnegie Mellon University from 2018 to 2019. His six-month tenure in Pittsburgh, Pennsylvania, allowed him to deepen his expertise in machine learning and algorithms, which are essential for advancements in autonomous vehicle technology.
Academic Qualifications
Bohui Fang earned his Bachelor of Engineering in Computer Science and Technology from Shanghai Jiao Tong University, completing his studies from 2015 to 2019. He furthered his education by obtaining a Master's degree in Computational Data Science from Carnegie Mellon University, where he studied from 2019 to 2020. His academic background provides a strong foundation for his research and engineering work.
Experience at Shanghai Jiao Tong University
Before his internships and current role, Bohui Fang worked as a Research Assistant at Shanghai Jiao Tong University from 2017 to 2018. This one-year position in Shanghai, China, contributed to his development in research methodologies and practical applications in the field of autonomous systems.