Zhongjun Jin is a software engineer with 11 years of experience, currently building query engine and database technologies on TikTok’s Data Platform in San Jose/Bellevue. He holds a PhD from the University of Michigan, where he was co-advised by Mike Cafarella and H. V. Jagadish and developed interactive data-preparation systems using program synthesis, ML-guided combinatorial search, and data profiling. His background spans industry research and product work—from Microsoft Research and Trifacta (where his intelligent data-cleaning feature shipped in Trifacta Cloud) to internships at Qualcomm—bridging research ideas and production systems. He’s especially interested in improving productivity for data scientists and non-expert users via runtime/engine innovations and hardware-software co-design. Notably, he combines deep academic rigor with hands-on engineering of high-scale query engines in consumer-facing data platforms.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Michigan
Electrical and Electronics Engineering, Electrical and Electronics Engineering at Tianjin University
Bachelor's Degree, Computer Science, Mathematics, Bachelor's Degree, Computer Science, Mathematics at Purdue University
A new C++ vectorized database acceleration library aimed to optimizing query engines and data processing systems.
Contributions:2 PRs, 26 pushes, 6 branches in 1 year 4 months
queryvectorizedcppdata-processingacceleration
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