Gokce Akadir developed a modular integration of TimM pre-trained models into the brain-score/vision repository, focusing on expanding the platform’s benchmarking capabilities for computer vision research. Using Python and PyTorch, Gokce engineered a scalable extension point that allows seamless registration, loading, and preprocessing of models such as ConvNeXt variants and Vision Transformers. The work included building utilities for configuration management, ensuring that future model families can be incorporated efficiently. This feature-rich addition addressed the need for broader model support in brainscore_vision, demonstrating depth in deep learning and machine learning while laying groundwork for ongoing extensibility and robust evaluation workflows.