Qi Zhang is a research scientist with six years of industry experience building secure, AI-accelerated systems and large-scale model serving platforms for hybrid cloud environments. Currently at Meta after a research staff role at IBM Watson, Qi has blended deep systems research—confidential computing for Kubernetes/Openshift, virtualization, and blockchain performance—with practical production deployment. Their academic background (PhD from Georgia Tech) underpins work on VM and shared-memory optimizations for big-data and graph workloads, enabling higher throughput in virtualized infrastructures. Qi’s profile reflects a rare mix of low-level performance tuning for IBM System Z and cloud-native model serving expertise, making them fluent across old and new enterprise stacks. Based in the New York City area, they pair rigorous research instincts with hands-on platform engineering to move advanced security and AI features from prototype to production. Despite a self-described “little nervous” GitHub bio, their career shows consistent impact across academia and industry.
6 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Georgia Institute of Technology
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Huazhong University of Science and Technology
Sui, a next-generation smart contract platform with high throughput, low latency, and an asset-oriented programming model powered by the Move programming language
Contributions:9 pushes, 1 branch in 2 years 4 months
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