Ahmad Mady

Led the design, development, and implementation of articulated robotics projects utilizing the Robot Operating System (ROS, ROS2), and Docker containerization platform in an Agile methodology. Developed and implemented state-of-the-art machine and deep learning algorithms for data analysis and for perception and computer vision tasks, including object detection, tracking and localization, in the context of autonomous driving.

Employed a state-of-the-art object detection model (YOLO) to efficiently and accurately localize and classify objects of interest, such as tumors, within medical images. •Developed a medical image analysis system for lung, liver, and atrium tumor segmentation •Tracked the movement of objects over time in medical image sequences, allowing for tasks like monitoring tumor growth or predicting the path of a surgical tool.