Yuanqi Li is a second-year PhD student in Computer Science at UCLA with 11 years of engineering experience and a strong academic foundation from UCSB (BS, CS, major GPA 3.95). His research and practical interests span machine learning and big data, cloud-native virtualization, and operating system and managed runtime optimizations. Currently he applies advanced ML methods to computer-aided diagnosis systems, bridging clinical needs with scalable, performant software. Yuanqi brings a cross-disciplinary perspective that blends systems-level thinking with data-driven modeling—valuable for productionizing research prototypes. Based in Los Angeles, he combines rigorous academic training with hands-on development experience across research and engineering domains. Notably, his background suggests an ability to navigate both low-level performance tradeoffs and high-level ML design in medical applications.
11 years of coding experience
High School Diploma, High School Diploma at High School Affiliated to Nanjing Normal University
Bachelor of Science - BS, Computer Science, Major GPA 3.95, Bachelor of Science - BS, Computer Science, Major GPA 3.95 at University of California, Santa Barbara
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Los Angeles
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