Chong Zhou is a Principal Engineer specializing in AI/ML software with a decade of experience building production-grade time-series, anomaly, and drift-detection systems for enterprise-scale telemetry. He has driven measurable impact at Splunk—shipping a decoder-based time-series foundation model, an LLM-agent for automated root-cause analysis that cut investigation time from hours to minutes, and production drift/anomaly frameworks that reduced false positives for customers. Prior roles at Meta and Microsoft applied ML to large-scale caching, pricing, and device-driver risk problems, and his academic background includes a PhD in Data Science from Worcester Polytechnic Institute. Based in the Greater Seattle Area, he blends research rigor with pragmatic engineering, often translating advanced smoothing and calibration techniques into shipped features; intriguingly, his GitHub bio simply reads "An anomaly," hinting at both domain focus and a dry sense of humor.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Data Science, Doctor of Philosophy - PhD Data Science at Worcester Polytechnic Institute
Bachelor of Engineering (BE) Computer Science, Bachelor of Engineering (BE) Computer Science at Southwest University
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