I am an Embedded Systems Engineer with a degree in Industrial Electronics from the National Engineering School of Sousse, a distinguished institution in Tunisia. With a keen interest in artificial intelligence and machine learning, I have mastered various programming languages such as Python, C, and C++, and gained practical expertise in operating systems, including Embedded Linux. I am skilled in embedded communication protocols such as UART, I2C, SPI, CAN, LIN, and Ethernet.My academic projects have been diverse and impactful, including the design of a real-time energy consumption monitoring system using the ESP32 board and PZEM-004T module. I also led a project leveraging TensorFlow and Raspberry Pi for precise real-time detection of plant diseases using convolutional neural networks (CNNs). Another notable project involved programming a microcontroller for an intelligent door opening system based on occupancy detection, crucial for managing space occupancy during the Covid-19 pandemic. Additionally, I initiated a project using Matlab, deep learning, and CNNs to accurately detect and categorize brain tumors in medical images.Beyond technical skills, I have cultivated essential soft skills such as communication, teamwork, and adaptability through diverse experiences. Notably, I was selected among hundreds to participate in the WOmentoring Global Experience in Engineering and attended the Engineering and Humanity Academy at SMU Lyle School of Engineering in Dallas, Texas. I also contributed to the Earthx2023 Sustainability Exhibition in Dallas.My career goal is to drive meaningful advancements in embedded systems and Artificial Intelligence by applying my skills and knowledge. I am passionate about continuous learning and contributing to innovative projects. Let's connect to explore opportunities for collaboration and innovation in these dynamic fields.