Tiantu Xu is a research scientist at Meta with 9 years of experience designing and building high-performance systems software for media understanding and generative AI. He holds a Ph.D. in Computer Engineering from Purdue, where his thesis produced multiple video analytics engines and a data store that ran queries hundreds of times faster than real time for city-scale and low-cost camera scenarios. At Meta he applies that systems expertise to scale LLM-driven media pipelines, bridging resource-efficient storage, retrieval, and spatio-temporal content re-identification. His background spans hands-on device-level research in applied physics and ferroelectric devices to practical AR localization and large-scale software, giving him a rare blend of low-level modeling and production systems know-how. Colleagues benefit from his focus on measurable performance gains and pragmatic orchestration of compute and storage for ML workloads.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science (B.S.), Applied Physics, Bachelor of Science (B.S.), Applied Physics at University of Science and Technology of China
Doctor of Philosophy (Ph.D.), Computer Engineering, Doctor of Philosophy (Ph.D.), Computer Engineering at Purdue University
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