Kaoutar Ait-Ahmad received her M.Sc. in Control, Signal, and Image Processing from CentraleSupélec at Paris - Saclay University (Artificial Intelligence degree certified by the DATAIA institute) in France and her engineering degree from Mohammadia School of Engineers in Morocco. Her master's thesis required her to develop a learning-based approach to detect and measure the optic nerve sheath diameter ONSD adapted to ultrasound imaging, to prevent raised intracranial pressure ICP, by bridging the gap between statistical models and deep learning. Kaoutar was involved in various projects themed as computer vision (medical image analysis, image segmentation, object detection, etc.), machine learning, and data science. Kaoutar's position as Research Engineer at CEDAR, she strives to bring impeccable achievements and extraordinary engagement to the work field. Her exposure to real-world data on multiple projects, such as the classification of skin lesion images, provides valuable experience for her mission which refers to doing pioneering work in the field of cancer research to improve the quality of life for people and build a worldwide network for early diagnosis. Kaoutar enjoys traveling to explore new cultures.