Yenny Villuendas-Rey

Papers

Total Citations

H-Index

About

Yenny Villuendas-Rey is a leading researcher at the forefront of intelligent manufacturing and industrial automation. Her work focuses on the intersection of computer vision, machine learning, and quality control, particularly within robotic welding processes. Her major contribution lies in developing automated segmentation techniques for gas metal arc welding (GMAW), a critical advancement for ensuring uniform weld strength and reducing defects in high-stakes industries like automotive and construction. By enabling real-time, automatic quality inspection, her research directly supports cleaner, more efficient production lines and minimizes material waste. Her highly cited 2025 paper, "Automatic Segmentation of Gas Metal Arc Welding for Cleaner Productions," has already garnered 3 citations, reflecting its immediate relevance and impact. Villuendas-Rey’s work is notable for bridging the gap between theoretical computer vision models and practical, industrial-scale applications, offering tangible solutions for smart factories. Her research is essential reading for engineers and computer scientists seeking to integrate AI-driven inspection into modern manufacturing, promising safer, more reliable, and environmentally friendly production processes.