Ghofrane Ben Hassan

Design of an autonomous audio-photo device with embedded AI for monitoring bats and nocturnal insects. - Developed a MicroPython pipeline on the OpenMV N6 (STM32N6 with NPU): image capture synchronized with infrared flash, motion detection by frame differencing, and blob filtering by size, density and local contrast. - Built and annotated a dataset from field images. - Trained a YOLOv8n classification model (bat / insect / unknown), quantized to INT8 (1.5 MB) and deployed on the embedded NPU.

Real-Time Computer Vision System for Automated Rivet Inspection on Electronic Boards - Developed a real-time computer vision system using OpenCV and Convolutional Neural Networks (CNNs) to detect and classify rivet defects on TV power supply boards. - Deployed the system on a Raspberry Pi 4 with a Pi camera for on-site, real-time inspection. - Built a Streamlit monitoring interface to display detections and defects live for operators. - Gained hands-on experience with electronic board assembly.

- Discovered the structure and operations of a national electricity utility, with exposure to energy distribution and maintenance processes. - Visited and observed the operation of power transformers and substations, understanding their role in voltage regulation and grid stability. - Observed and analyzed the work of maintenance teams in troubleshooting and preventive maintenance of electrical installations.

English-taught research Master’s program (SST track) at ENIT, completed as a double degree alongside the engineering degree. Key modules: - Artificial Intelligence, Advanced Pattern Recognition - Advanced Image Processing, Advanced Speech Processing - Embedded Systems, System-on-Chip Design - Wir

Three-year engineering program in the Electrical Engineering department of ENIT, taught in French: two years of core electrical engineering, then a final year specialized in Automation and Industrial Computing. Core electrical engineering (years 1–2): - Electronics, digital electronics and progra

Two-year intensive preparatory program (Technology section), equivalent to the French CPGE, preparing for the national competitive entrance exam to engineering schools. Key subjects: - Mathematics: analysis, linear algebra, probability - Physics: mechanics, electricity, electromagnetism, thermody