Yongqin Wang is a PhD candidate and Research Assistant in Electrical and Computer Engineering at USC with eight years of experience focusing on efficient and secure machine learning systems. His research spans Secure Multi-Party Computation, Oblivious RAM, and Trusted Execution Environments, blending theoretical rigor with systems-building to make privacy-preserving ML practical. He spent a research internship at Facebook AI, bringing industry-scale perspectives to academic problems and accelerating prototype-to-proof workflows. Based in Pasadena, he pairs deep hardware and software training from UW and USC to tackle performance and security simultaneously, often exploring how system-level optimizations can reduce cryptographic overheads in real deployments.
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