Songbin Liu is a seasoned software engineer with nine years of experience building large-scale, data-driven systems, currently contributing at Facebook from New York. He combines deep expertise in C/C++, Python, Go and Java with hands-on machine learning and data engineering—having implemented bi-directional LSTM semantic filters, item-CF, pLSA, word2vec, and time-series predictors in production. His background spans distributed systems, Hadoop/Spark/Storm pipelines, Kafka, Prometheus/ Istio integrations, and performance work for containers on Kubernetes/OpenShift. Songbin’s PhD research in distributed storage and data compression complements practical experience in async sockets, multi-threading, and data deduplication, enabling robust low-level and ML-infused solutions. He’s an active contributor to tooling and demos (e.g., kubeturbo, podmove, timeSeriesPredict) that bridge observability, orchestration and prediction in cloud environments.
9 years of coding experience
6 years of employment as a software developer
Exchange Student, Distributed Database, Exchange Student, Distributed Database at New York University
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Beijing Information Science and Technology University
Doctor of Philosophy (Ph.D.), Distributed storage system, data compression, Doctor of Philosophy (Ph.D.), Distributed storage system, data compression at Tsinghua University
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