Shengbin Wang is a seasoned professional with a robust background in machine learning and mechanical engineering. Experience includes serving as a Research Assistant at the University of Houston from August 2018 to December 2022, where significant projects involved the self-sensing of dielectric tubular actuators and the design of a jellyfish robot with optical control systems. Currently, Shengbin is a Machine Learning Engineer at Meta since January 2025. Prior internships at Bosch China and Mercedes-Benz China provided foundational industry exposure, while a role at BKO AI as an Analytics Engineer involved developing a predictive health model that processed over 2 million Siemens Cloud files to enhance operational efficiency. Educational qualifications include a PhD in Mechanical Engineering and multiple degrees in related fields from institutions such as Georgia Institute of Technology and Huazhong Agricultural University.
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