Industrial computing and automation engineering student specializing in robotic perception and embedded vision, with hands-on experience across multi-national research internships and robotics competitions in Tunisia and…
Industrial computing and automation engineering student specializing in robotic perception and embedded vision, with hands-on experience across multi-national research internships and robotics competitions in Tunisia and Norway. Skilled at designing and deploying deep learning-based perception (YOLOv8, EfficientDet) on edge hardware (Raspberry Pi, STM32, ESP32) using HALCON and CVAT, and integrating it with multi-board robotic architectures using ROS 2, Micro-ROS, Gazebo and MoveIt 2.
<p>Simulated and operated the lab’s JetCobot robot arm in Gazebo with MoveIt 2 for collision-aware trajectory planning<br>
Developed a ROS 2 pipeline for automated multi-view plant image acquisition (Green2Behave project)<br>
Benchmarked COLMAP and MASt3R for monocular 3D reconstruction, point cloud segmentation and skeletonization-based plant trait extraction<br>
Implemented self-supervised Barlow Twins representation learning integrated into the PheNo phenotyping infrastructure</p>
<p>Mentored the Tunisian junior RoboCup team (Robot Rescue Maze) on computer vision and robotics<br>
Designed custom PCBs and programmed ESP32 microcontrollers for the team’s robots</p>
<p>Built and deployed a real-time YOLOv8 vision system on Raspberry Pi 4 interfacing with Siemens PLCs<br>
Improved operator safety monitoring on the production line</p>
<p>Applied a modified Barlow Twins pre-training strategy on EfficientDet (D0/D1) for animal detection<br>
Improved mAP at higher IoU thresholds on a custom pig-farm dataset</p>
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