GrayMatter Robotics
Miguel Ángel Chávez has a diverse work experience spanning several industries. Miguel Ángel began their career as a CAD Designer/Machinist Apprentice at RPM Machining, where they gained experience in operating various machines, assisting with CAD modeling, and collaborating with engineers to resolve manufacturing issues. Following this, Miguel worked as a New Product Development Engineer at Alcoa Fastening Systems & Rings, where they contributed to the development of new products. Miguel Ángel then transitioned to roles as a Manufacturing Engineer-Programmer at Zodiac Aerospace and Safran, where they focused on programming and improving manufacturing processes. Miguel later served as a Project Engineer at Performance Composites Inc., managing projects and overseeing engineering tasks. Miguel Ángel then joined Hexagon Manufacturing Intelligence as a Manufacturing Engineer, where they utilized their expertise in manufacturing processes. Currently, Miguel is working at GrayMatter Robotics, initially as a Robotics Applications Engineer and now as a Robotics Applications Engineer II. Overall, Miguel has extensive experience in robotics, manufacturing engineering, project management, and CAD design.
Miguel Ángel Chávez obtained a Bachelor of Science (B.S.) degree in Mechanical Engineering from California State University, Long Beach. Miguel Ángel studied at the university from 2008 to 2013. In addition to their formal education, Miguel Ángel Chávez has obtained several certifications, including PowerMill Essentials/Intermediate Class from NexGenCAM in April 2019, Adobe XD CC Essential Training: Design, Adobe XD Essential Training: Prototype and Share, and InDesign for UX Design from Lynda.com in June 2018.
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GrayMatter Robotics
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GrayMatter Robotics creates solutions to assist humans in tedious and ergonomically challenging tasks. They make AI-Brains for robots to make them smart, easy to use, and rapidly deployable for complex operations. Their software combines commercially available robots and multi-modal sensing with artificial intelligence to create smart robotic assistants that are well-suited for complex operations in high-mix manufacturing and service applications.