During their work on PaddlePaddle/Paddle and PaddleCustomDevice, this developer enhanced CUDA kernel functionality by implementing and integrating fused sequence pooling with CVM and affine channel operations, focusing on both forward and gradient paths. Using C++ and CUDA, they addressed kernel discovery and registration issues, ensuring reliable cross-backend compatibility and correct compilation on iluvatar_gpu and metax_gpu. Their contributions included restructuring GPU-specific directories, refining header placements, and resolving bugs in kernel loadability and runtime correctness. The work demonstrated depth in CUDA kernel development and operator implementation, resulting in improved performance, maintainability, and correctness across deep learning workflows in the PaddlePaddle repositories.