We welcome Ethel García from the Universidad del Norte (Barranquilla, Colombia). Ethel will be part of our team during the next three months as an internship in her PhD studies.

Ethel Garcia

“As a student in the field of industrial engineering, I have always been passionate about improving processes and ensuring product quality. I embarked on this academic journey with a deep interest in understanding and optimizing industrial systems. After completing my undergraduate studies, I pursued a master’s degree in industrial engineering, which further refined my knowledge and skills in this discipline.

During my master’s program, I delved into various aspects of industrial engineering, from quality control to process optimization. The program equipped me with a solid foundation in statistical analysis and data-driven decision-making, which is crucial in ensuring the quality and efficiency of industrial processes.

Now, as a doctoral student, I have the privilege of working on control chart pattern recognition using deep learning algorithms for quality assurance. This cutting-edge technology allows us to identify patterns and anomalies in industrial processes, enabling us to take proactive measures to maintain product quality and reduce defects. This work not only aligns with my academic background but also reflects the real-world applications of industrial engineering principles.

Being in the midst of my internship at Universidad de Zaragoza in the IAAA Lab from the Informatics Department fills me with great excitement. It’s an incredible opportunity to gain hands-on experience and apply the knowledge I’ve acquired during my studies. This internship is not just a step in my academic and professional journey; it’s a chance to grow and shape my future in industrial engineering. I am grateful for this opportunity and look forward to the valuable experiences and knowledge I will gain during my time at Universidad de Zaragoza.

The path ahead may be challenging, but my commitment to innovation and excellence in industrial engineering remains unwavering. I am excited to be part of a generation of engineers and scientists who are leveraging the power of deep learning to redefine the way we ensure quality and efficiency in industrial processes. As I continue my research and work towards my doctorate, I’m determined to shape the future of industrial engineering, one deep learning algorithm at a time.”