Andres Aranguren

Guided Master’s students in foundational programming, version control, and machine learning practices. Mentored topics included Git workflows, model evaluation with W&B, building ML portfolios, and writing reproducible research papers.

Guided Master’s students in foundational programming, version control, and machine learning practices. Covered Git workflows, model evaluation with W&B, building ML portfolios, and reproducible research practices.

Designed and implemented computer vision pipelines for fruit quality assessment, developing deep learning models for automatic segmentation, color calibration, and geometric measurement. Evaluated model performance under varying lighting and occlusion conditions, improving robustness for real-world agricultural environments. Implemented data preprocessing and augmentation strategies and deployed models to production with a reproducible CI/CD workflow.