Zhiqi Li is a Sr. Engineering Manager in San Francisco with nine years of experience building and leading large-scale identity resolution and data infrastructure at LiveRamp. He currently oversees three teams powering real-time identity APIs at 250k QPS and daily petabyte-scale identifier mappings, having driven migrations to GCP and Spark and optimized graph-building throughput by 50%. A hands-on leader, he has grown teams, coached individual careers, and led cost-saving efforts that reduced compute spend by $3M annually. His background in very large information systems (Carnegie Mellon) and information security (Shanghai Jiao Tong) underpins a pragmatic approach to scalable, privacy-conscious data systems. Notably, he started at LiveRamp as an intern improving device-matching reach by 40% and has since shaped core identity technology used across the company.
9 years of coding experience
8 years of employment as a software developer
Master's degree, Computer Science, Specialization in Very Large Information Systems, Master's degree, Computer Science, Specialization in Very Large Information Systems at Carnegie Mellon University
Bachelor of Science (BS), Information Security, Bachelor of Science (BS), Information Security at Shanghai Jiao Tong University
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
Contributions:2 releases, 19 commits, 6 PRs in 4 months
Contributions:1 release, 3 pushes, 1 branch in 4 years 6 months
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