Keming Zhang is a skilled software engineer with extensive internship experience, including roles at CaseCtrl, Amazon Web Services, Santa Fe Institute, and Rice University. At CaseCtrl, Keming contributed to the development of a full-stack enterprise application for surgical scheduling. During the internship at AWS, Keming designed and implemented a domain join feature in the EC2 Launch agent to enhance EC2 instance boot time. Previous work includes research on traffic flow dynamics at the Santa Fe Institute and developing a frontend dashboard for research monitoring at Rice University. Currently, Keming serves as a Machine Learning Engineer at Meta, focusing on core ML modeling for Facebook's recommendation systems. Keming holds a Master of Science in Computer Science from Rice University and completed an undergraduate program at St. John's College.
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