Luis Gomez Camara
About Luis Gomez Camara
Luis Gomez Camara is a Research Engineer with a diverse background in natural sciences and engineering, specializing in audio-visual tracking for socially assistive robots. He has worked at various institutions, including Airbus and Inria, and holds degrees in Chemistry, Computational Chemistry, and Computer Vision.
Work at Inria
Luis Gomez Camara has been employed at Inria as a Research Engineer since 2020. He is part of the RobotLearn team, which was previously known as the Perception team. His work focuses on audio-visual tracking for socially assistive robots, contributing to the H2020 SPRING project. Inria is a national research institution in France that specializes in computer science and applied mathematics.
Education and Expertise
Luis Gomez Camara holds multiple degrees in various fields. He earned a PhD in Computational Chemistry from Imperial College London from 2001 to 2006. He also completed a Master of Science (MSc) in Digital Signal Processing (Music) at Queen Mary University of London from 2005 to 2006, and another MSc in Computer Vision at King Juan Carlos University of Madrid from 2015 to 2016. His educational background supports his expertise in computational chemistry, computer vision, and digital signal processing.
Background
Luis Gomez Camara has a diverse professional background that spans multiple industries. He began his career as a DSP audio developer at Juno Records and later at Soundmouse, where he worked on automatic music recognition and fingerprinting. He transitioned to the aerospace sector, serving as a Computer Vision Research Intern and later as a Research Engineer at Airbus. His experience also includes a role as a Research Scientist at the Czech Institute of Informatics, Robotics and Cybernetics.
Achievements
Throughout his career, Luis Gomez Camara has contributed to various projects and initiatives. His work in the field of robotic vision research has included a focus on life-long autonomy and visual place recognition. His involvement in the H2020 SPRING project at Inria highlights his commitment to advancing the capabilities of socially assistive robots through audio-visual tracking.