During February 2025, Zhonghan Jun focused on improving the stability and resource efficiency of image processing workflows in the modelscope/data-juicer repository. He addressed a memory leak in the ImageNSFWFilter by wrapping model inference with torch.no_grad(), a technique in Python and PyTorch that prevents unnecessary gradient tracking during inference. This change reduced memory usage and enabled more deterministic memory management, allowing longer-running batch jobs without spikes. Zhonghan validated that the fix did not alter end-user behavior and prepared the update for production deployment. His work demonstrated depth in deep learning, memory management, and performance optimization within a production codebase.