Embedded Systems
Raspberry Pi, ESP32-S3, sensor integration, GPIO, SPI, I2C, UART, real-time constraints.
I am Muhammad Jabbar, a motivated Software Engineer with a strong academic foundation in Electrical Engineering and Information Technology, currently pursuing my Master’s degree at Otto von Guericke University Magdeburg, Germany. I bring diversified professional experience in Python, C++, and MATLAB, with a strong focus on embedded systems, machine learning, and data-driven software solutions.
I began my professional journey at Pakistan Aeronautical Complex (PAC) Kamra, working on diagnosing, repairing, and maintaining aircraft inverter systems. I later joined Devomech Solutions GmbH as an Embedded Software Developer, integrating sensors and HQ cameras on Raspberry Pi and ESP32-S3 using SPI, I2C, UART, and GPIO while building efficient embedded and image-processing solutions.
Since moving to Germany, I worked as a Working Student Software Engineer at Goldschmidt Smart Rail Solutions, focusing on ultrasonic data acquisition, preprocessing, visualization, and deep-learning-based classification in MATLAB. I also served as a Student Research Assistant (Hiwi), where I worked on automating literature surveys using LLMs and building scalable AI-assisted workflows. My recent projects include face detection and recognition pipelines using PyTorch, MediaPipe, OpenCV, and Hugging Face embeddings across image and video data.
Raspberry Pi, ESP32-S3, sensor integration, GPIO, SPI, I2C, UART, real-time constraints.
MATLAB deep learning pipelines, CNN training/evaluation (AlexNet/ResNet), signal & image processing.
OpenCV, MediaPipe, PyTorch, embeddings (Hugging Face), face detection/recognition, video processing.
Python, C++, MATLAB, Git, Docker, Linux, reproducible workflows, clean and maintainable code.