Jose Rangel‐Magdaleno

Autonomous University of Queretaro, National Institute of Astrophysics, Optics and Electronics

Papers

Total Citations

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About

Jose Rangel-Magdaleno is a researcher whose work spans automatic control, robotics, and artificial intelligence, with a particular focus on practical, real-time implementations. His key research areas include FPGA-based control systems, bipedal robot modeling, and emotion classification for service robotics. One of his major contributions is the development of an open-core FPGA-Matlab framework for three-time controllers, which provides an accessible, hands-on platform for teaching and implementing automatic control in industrial and educational settings—a work that has garnered 15 citations. He has also advanced the field of robotics by modeling a 5-link biped robot on Matlab/SimMechanics, offering a streamlined methodology that saves time and effort in mathematical model development (10 citations). More recently, Rangel-Magdaleno has ventured into AI-driven human-robot interaction, introducing a multiplatform system for real-time emotion classification using convolutional neural networks within a fog computing environment. This work, published in 2024, demonstrates his commitment to deploying intelligent systems across diverse hardware ecosystems, enhancing the capabilities of service robots. His research is notable for bridging theoretical concepts with practical, deployable solutions, making significant impacts in both education and applied engineering.