Sana Maghraoui

At Valhko, I contributed to building autonomous AI systems aimed at empowering communities, supporting workforce development, and advancing sustainable solutions. This experience allowed me to apply my skills in multi-agent systems and intelligent platforms in a context where technology meets social and economic challenges. Working with diverse teams and on mission-driven projects deepened my understanding of how AI can be leveraged not just for innovation, but for meaningful, scalable impact. I not only gained technical skills in AI and multi-agent systems but also learned a great deal about myself. Working with a talented and mission-driven team helped me understand my capacities, strengths, and areas for growth. I discovered how I adapt to new challenges, contribute effectively in collaborative settings, and take initiative to make an impact. This experience was as much about personal growth as it was about professional development.

Optimization of Drone Area Mapping in GNSS-Denied Environments UM6P AI Movement Lab – End of Studies Internship I worked on optimizing drone navigation and area mapping in environments without GNSS signals, focusing on multi-agent coordination for search and rescue missions. After reviewing existing strategies, I developed new bio-inspired navigation algorithms using digital pheromones combined with Deep Q-Learning (DQN). 🔍 Key Focus Areas: • Multi-agent systems • Bio-inspired algorithms • Deep reinforcement learning • Navigation in GNSS-denied zones This project deepened my interest in intelligent systems and reinforced my passion for combining AI and nature-inspired approaches to solve real-world challenges.

Autonomous Exploration and Mapping with Heterogeneous UAVs and UGVs in GPS-Denied Environments As part of a research project, I developed an autonomous exploration and mapping system using a team of UAVs (drones) and UGVs (ground robots) operating in environments without GPS. I used ROS and Gazebo for simulation, and implemented multi-agent coordination and navigation using SLAM and path-planning algorithms. 🔍 Key Focus Areas: • Multi-robot coordination • SLAM and autonomous navigation • ROS and Gazebo simulation • Area mapping in GPS-denied environments This project strengthened my skills in robotics and multi-agent systems, and deepened my interest in autonomous and intelligent exploration.

Optimizing Bottling Processes through Lean Tools and AI During this internship, I analyzed production data to improve the performance of a bottling line. Using Power BI and Excel, I identified key inefficiencies and applied Lean manufacturing techniques, including Pareto analysis, Ishikawa diagrams, and SMED, to reduce machine changeover times and enhance overall productivity. I also developed a Convolutional Neural Network (CNN) for defect detection to improve quality control and designed a preventive maintenance plan to reduce unplanned downtimes. 🔍 Key Focus Areas: • Lean Manufacturing & SMED • Power BI & Data Analysis • CNN for visual defect detection • Preventive Maintenance Planning This experience strengthened my ability to combine data-driven analysis with practical industrial improvements.