Yang Xia is a research scientist at Meta with 12 years of experience building high-performance parallel and distributed systems, specializing in GPUs, CUDA, and ML system deployment. He holds a PhD in Computer Science and Engineering from The Ohio State University and combines deep academic rigor with hands-on engineering across C/C++, Python, Java, RDMA, MPI and Triton. His work spans networked database management, parallel algorithms, and system-level optimization—highlighted by an NVIDIA internship where he implemented a memory-efficient, high-performance non-deterministic SpGEMM for cuSPARSE. Comfortable across heterogeneous compute (OpenCL, Xeon Phi) and communication stacks, he focuses on squeezing performance at scale while maintaining practical deployability. Based in Jersey City, he blends research-driven innovation with production engineering at the intersection of ML infrastructure and distributed databases. Colleagues know him for translating complex parallel research into tangible system improvements that lower resource use and boost throughput.
12 years of coding experience
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Huazhong University of Science and Technology
Doctor of Philosophy - PhD, Computer Science and Engineering, Doctor of Philosophy - PhD, Computer Science and Engineering at The Ohio State University
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