Yue Niu is an ML research scientist with a PhD in Computer Engineering from USC and eight years of experience at the intersection of efficient and privacy-preserving machine learning. Currently at Meta, Yue's work spans differential privacy, federated learning, and leveraging trusted execution environments to balance performance and data confidentiality. Prior roles at Amazon and USC combined applied science and systems-focused research, including FPGA-based CNN acceleration and low-rank compression for efficient inference. He brings deep expertise in distributed ML optimization—particularly second-order methods—to accelerate training while preserving privacy, and uniquely couples hardware-aware implementations with theoretical ML techniques. Based in Los Angeles, he is reachable at yueniu2022@gmail.com for collaboration on private and scalable ML systems.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at University of Southern California
Master of Engineering - MEng, Electrical and Electronics Engineering, 3.7, Master of Engineering - MEng, Electrical and Electronics Engineering, 3.7 at Northwestern Polytechnical University
Contributions:360 pushes, 1 branch in 1 year 5 months
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