Kevin Zhu developed targeted enhancements for the FastVideo framework, focusing on implementing mask search functionality for the Wan2.1 model to optimize Spatial-Temporal Attention masks and improve video generation quality. He designed and integrated supporting scripts and configuration management using Python and Bash, enabling efficient experimentation and tuning of attention mechanisms within the end-to-end workflow. In addition to core engineering, Kevin contributed to jeejeelee/vllm by refining documentation, correcting a model path reference to improve clarity for users. His work demonstrated depth in model optimization, scripting, and technical writing, addressing both feature development and documentation quality within a short timeframe.