Elizabeth González García
About Elizabeth González García
Elizabeth González García is the Team Lead for Research & Development at Devo in Madrid, where she has worked since 2018. She has extensive experience in computer vision, machine learning, and robotics, with a background in both academia and industry.
Work at Devo
Elizabeth González García has been serving as the Team Lead for Research & Development at Devo since 2018. In this role, she oversees projects related to machine learning applications in computer vision. Her work focuses on advancing technologies in object recognition and image segmentation. Based in Madrid, she has contributed significantly to the team, leveraging her extensive background in visual navigation for robotics and machine learning.
Education and Expertise
Elizabeth González García holds a Doctor of Philosophy (Ph.D.) in Mecatrónica from Universidad de Castilla-La Mancha. She also earned a Licenciatura in Ciencias de la Computacion from Universidad de La Habana. Her academic background provides a strong foundation for her expertise in visual navigation for robotics, Bayesian learning, multi-class boosting, and machine learning solutions for computer vision problems.
Background
Before joining Devo, Elizabeth worked as a researcher at Universidad de Castilla-La Mancha from 2004 to 2013. During her nine years there, she focused on various aspects of computer vision and robotics. Her research experience has equipped her with skills in automatic image synthesis, image-based rendering, and developing shape descriptors and grasping techniques.
Achievements in Research and Development
Throughout her career, Elizabeth González García has worked on significant projects related to object recognition in natural images and image segmentation. Her contributions to the field include advancements in image browsing and distance metrics, which are essential for improving machine learning models in computer vision. Her research has implications for various applications, particularly in robotics and automated systems.