Yifei worked on enhancing the stability and correctness of the NVIDIA/TensorRT-LLM repository by addressing a critical bug in CUDA stream synchronization within ModelRunnerCPP. Using Python and CUDA, Yifei implemented a fix that ensures proper synchronization before operations dependent on prompt table data, effectively preventing data races and improving inference determinism. This technical approach focused on robust execution and reducing production risk rather than introducing new features. The work included clear commit documentation and traceability, supporting maintainability and auditability. Yifei’s contributions demonstrated depth in deep learning systems engineering, prioritizing reliability and correctness in high-performance model inference environments.