During March 2025, this developer contributed to the secretflow/spu repository by delivering comprehensive Chinese documentation for the Policy-SGD optimizer, focusing on its application within MPC-ML. They compiled and published experimental results comparing Policy-SGD to naive SGD, incorporating adaptive learning-rate scaling, learning-rate decay, and early stopping across multiple datasets. Their work established a reproducibility framework and robust baseline for future optimizer research. Utilizing technical writing, machine learning expertise, and PO language skills, the developer enhanced onboarding for Chinese-speaking engineers and clarified the technical challenges of SGD in secure computation, demonstrating depth in both documentation and experimental benchmarking.