Long Wan is a software development engineer at Microsoft with eight years of experience building high-performance, scalable systems and full-stack applications across cloud, networking, and ML domains. At Microsoft he contributes to Azure Monitor Container Insights for AKS and Azure Arc, focusing on containerized logging, metadata-rich schemas, and cost-efficient logging tiers that improve query performance at scale. His background spans cloud-native observability, SDN/NFV work with ONAP, and production ML deployments (CNN-CRF NER) using microservices—showing an unusual blend of low-level network intelligence and applied deep learning. Previously he helped manage $34B in grants systems at Leidos using Java, Spring, and enterprise patterns, and he holds an MS in Electrical Engineering from NYU. Based in Redmond, he combines production-grade engineering with open-source collaboration to improve hybrid cloud scalability and security.
8 years of coding experience
6 years of employment as a software developer
Master of Science (M.S.) Electrical Engineering(Machine/Deep Learning Cloud Computing Track) , Master of Science (M.S.) Electrical Engineering(Machine/Deep Learning Cloud Computing Track) at New York University
Bachelor of Science (B.S.) Applied Physics Electrical and Electronics Engineering, Bachelor of Science (B.S.) Applied Physics Electrical and Electronics Engineering at Beijing University of Posts and Telecommunications
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Long Wan - Software Development Engineer At Microsoft