Samuel Rojo álvarez
About Samuel Rojo álvarez
Samuel Rojo Álvarez is an Embedded Software Developer at thyssenkrupp in Municipio de Trelleborg, Escania, Sweden, with previous experience at FICOSA and Grupo Empresarial Electromédico GEE. He specializes in firmware development for IoT and AI devices, with expertise in various communication protocols.
Title
Samuel Rojo álvarez holds the title of Embedded Software Developer.
Company
Samuel Rojo álvarez is currently working at thyssenkrupp as an Embedded Software Developer in Municipio de Trelleborg, Escania / Skåne, Suecia.
Previous Employment
Samuel Rojo álvarez has a diverse work history, having been employed at FICOSA as an Embedded Software Engineer from 2019 to 2020 in Viladecavalls, España. Previously, he also worked at Grupo Empresarial Electromédico GEE as an Electronics & Automation Engineer in a Biomedical Internship from 2016 to 2017 in Burela, Lugo, Spain.
Education and Expertise
Samuel Rojo álvarez completed a Back End Development Certification in Computer Software Engineering from freeCodeCamp in 2018. He also holds a Bachelor of Engineering degree in Electrical and Electronics Engineering, Biomedical Instrumentation from the University of Ljubljana, achieved in 2018. Additionally, he earned a Bachelor of Engineering in Electronics and Automation Engineering from the University of A Coruna in 2017.
Technical Skills and Specializations
Samuel specializes in designing and developing firmware for sensors and LED display images using Embedded Linux (ARM) and AVR software development, particularly with ESP32. His expertise covers a wide range of communication protocols including CAN, ETHERNET, UART, SPI, I2C, USB, RS-232/485, and TCP. He has developed firmware algorithms to enhance performance under exceptional conditions for IoT and AI devices, including detection and surveillance cameras.
Projects and Initiatives
Samuel has worked on software for Point Cloud LIDAR processing to aid in docking aircrafts, utilizing image recognition algorithms for filtering and cluster recognition.