Sizhe Fu
About Sizhe Fu
Sizhe Fu is a Production Engineer at Murata in Shanghai, China, with extensive experience in machine learning and computer vision technologies. He holds a Master's degree in Electrical Engineering from Southern Methodist University and has worked in various engineering roles over the past decade.
Work at Murata
Sizhe Fu has been employed at Murata as a Production Engineer since 2019. In this role, he is based in Shanghai City, China, and has accumulated five years of experience in the position. His responsibilities involve applying advanced technologies and methodologies to enhance production processes.
Education and Expertise
Sizhe Fu holds a Master's degree in Electrical Engineering from Southern Methodist University, where he studied from 2013 to 2015. He also earned a Bachelor of Science in Physics from Shanghai Jiao Tong University, completing his studies there from 2008 to 2012. His educational background includes coursework in Artificial Intelligence, Machine Learning, and Computer Networks.
Technical Skills and Technologies
Sizhe Fu possesses a strong foundation in machine learning and computer vision, with experience in advanced technologies such as TensorFlow, GoogleNet V3, and ResNet100. He is skilled in various programming languages, including Python, C++, Java, JavaScript, and SQL. Additionally, he is proficient in software development environments like Anaconda, IntelliJ, Eclipse, and Visual Studio.
Previous Work Experience
Before joining Murata, Sizhe Fu worked as an RF/Quality Engineer at CVE Technology from 2015 to 2019 in Allen, TX. He also served as a Project Assistant at Shanghai Jiao Tong University for seven months in 2011-2012. These roles contributed to his technical and project management skills.
Organizational and Management Skills
Sizhe Fu demonstrates strong organizational skills, including project management, time management, and problem-solving abilities. These skills are essential for effective collaboration across different functions within the engineering and production environments.