Zifan Zhu is a research scientist at Meta and a PhD candidate in Quantitative and Computational Biology at USC with nine years of experience applying machine learning and deep learning to large-scale systems. He holds an MS in Computer Science from USC and a top-ranked BS in Mathematics from Sichuan University, blending rigorous theory with production engineering. At Meta he focuses on deep learning frameworks, training data pipelines, and feature engineering for ads ranking, having previously improved model training metrics through novel signal architectures and monitoring pipelines. Zifan is comfortable spanning research and production: he designs algorithmic solutions informed by statistical rigor and ships robust data infrastructure at scale. Based in Menlo Park, he brings an uncommon combination of computational biology training and hands-on ads systems experience that accelerates ML-driven decisioning.
9 years of coding experience
Doctor of Philosophy - PhD, Computational Biology, 3.97/4.0, Doctor of Philosophy - PhD, Computational Biology, 3.97/4.0 at University of Southern California
Bachelor of Science - BS, Mathematics, 3.82/4.0 (Top 1), Bachelor of Science - BS, Mathematics, 3.82/4.0 (Top 1) at Sichuan University
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