Yexuan Hao

Yexuan Hao

Software Development Engineer In Test @ Torc Robotics

About Yexuan Hao

Yexuan Hao is a Software Development Engineer In Test at Torc Robotics, where he contributes to the development of autonomous vehicle software. He holds a Master of Science in Mechanical Engineering from Carnegie Mellon University and a Bachelor of Science in Mechanical Engineering from the University of Wisconsin-Madison.

Work at Torc Robotics

Yexuan Hao has been employed at Torc Robotics since 2021 as a Software Development Engineer In Test. In this role, he actively participates in the development of new vehicle behaviors and algorithms. His contributions are focused on enhancing the software for autonomous vehicles. Prior to his current position, he worked as an Application Test Engineer at Torc Robotics from 2020 to 2021, where he gained experience in testing and validating software applications.

Education and Expertise

Yexuan Hao holds a Master of Science in Mechanical Engineering from Carnegie Mellon University, where he studied from 2018 to 2020. He also earned a Bachelor of Science in Mechanical Engineering from the University of Wisconsin-Madison, completing his degree from 2014 to 2018. His educational background provides a strong foundation in engineering principles, which he applies in his current role in software development for autonomous vehicles.

Background

Yexuan Hao's professional journey includes significant roles in both academia and industry. He served as a Course Assistant at Carnegie Mellon University for Robot Dynamics and Analysis in 2019 and for Multivariable Linear Control in 2020. These positions allowed him to deepen his understanding of robotics and control systems while assisting students in their learning.

Contributions to Autonomous Vehicle Software

In his role at Torc Robotics, Yexuan Hao contributes to the development of autonomous vehicle software by performing root cause analysis on complex integrated systems. This involves identifying and resolving issues within the software, ensuring that the systems operate effectively and reliably in real-world conditions.

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