Yihe Hua
About Yihe Hua
Yihe Hua is a Software Engineer at Torc Robotics, specializing in machine learning applications for robotics and autonomous driving. He has a background in Mechanical Engineering, with degrees from Carnegie Mellon University and Shanghai Jiao Tong University, and previous internship experience at Bosch and Philips Lighting.
Work at Torc Robotics
Yihe Hua has been employed at Torc Robotics as a Software Engineer since 2021. In this role, he focuses on applying machine learning techniques to address challenges in robotics and autonomous driving. His work involves collaboration with team members on various projects, showcasing his ability to work effectively in a professional environment. Torc Robotics is known for its advancements in autonomous vehicle technology, and Hua contributes to this mission through his expertise in software engineering.
Previous Experience at Bosch
Prior to his current position, Yihe Hua worked at Bosch as a Marketing Operations Intern in 2019. This internship lasted for four months and took place in Shanghai. During this time, he gained valuable experience in marketing operations, which contributed to his professional development in the technology sector.
Internship at Philips Lighting
Yihe Hua also completed an internship at Philips Lighting as a Research and Development Intern from 2016 to 2017. This internship lasted for two months and was conducted in Shanghai City, China. His role involved engaging in research and development activities, which helped him build a foundation in engineering practices.
Education and Expertise
Yihe Hua holds a Master of Science degree in Mechanical Engineering with a focus on robotics and autonomous systems from Carnegie Mellon University, where he studied from 2019 to 2021. He also completed an exchange semester at the University of Wisconsin-Madison in 2018, studying Mechanical Engineering for 11 months. Additionally, he earned his Bachelor's degree in Mechanical Engineering from the UM-SJTU Joint Institute at Shanghai Jiao Tong University, where he studied from 2015 to 2019. His educational background equips him with the knowledge and skills necessary to specialize in machine learning applications within the robotics field.