Lu Zheng is a Biz Ops Manager with 8 years of experience at Intel, combining supplier quality management, process engineering and operations digitization to drive continuous quality improvement and cost savings. She has 3+ years leading supplier quality and project management, plus semiconductor process development roots and formal training in process control engineering. At Intel she progressed from hands-on process development and quality programs to site-level carrier management and regional ops digitization, demonstrating both technical depth and operational leadership. Lu pairs Lean and Six Sigma statistical methods with ISO9001-aligned quality systems to translate data into measurable productivity gains. She also contributes to open-source ML infrastructure work—optimizing quantized operations in the widely used PyTorch repository—highlighting a knack for bridging hardware-aware process thinking with software-level performance tuning. Based in Shanghai, she is skilled at coordinating cross-functional supplier ecosystems across Asia while maintaining a strong focus on scalable, auditable quality controls.
9 years of coding experience
2 years of employment as a software developer
Master, Process Control Engeering & Theory, Master, Process Control Engeering & Theory at East China University of Science and Technology
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
ML Engineer
Contributions:15 reviews, 22 PRs, 152 pushes in 3 months
Contributions summary:Lu focused on enabling and optimizing quantized operations within the PyTorch framework for the `pytorch/pytorch` repository. Their contributions centered on implementing and integrating new post-op fusion patterns, particularly for the `hardswish` and `gelu` activation functions, within the Inductor framework. This involved modifying core files in the `ATen`, and `quantization` directories. The user's work also included adding test cases to validate the functionality of these quantized operations.
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