Oumaima Souguir

Selected to join the GeoBench project, a collaborative research and benchmarking initiative with HOT fAIr. Currently exploring computer vision and object detection approaches for identifying trees, bridges, and solar panels in aerial imagery.

Developing research-oriented AI/ML projects, building Kaggle notebooks for EDA, preprocessing, feature engineering, and model training. Preparing for Kaggle competitions to benchmark models and improve experimentation skills.

Contributed to Python and Selenium automation of data collection, processing, and validation for tourism contract workflows, improving reliability and turnaround speed. Acted as a link between Satisfy Insight and Best Time Travel, supplying and verifying contract data.

Managed 17 hotel allotment contracts with over 99% data accuracy on Sunhotels and WebBeds. Configured pricing rules, quotas, and booking conditions to optimize revenue yield.

Structured self-directed study of cybersecurity fundamentals, application security, and API security, applied through hands-on projects. Explored security testing methodologies, vulnerability analysis, and secure software development.

Developed secure Android apps in Kotlin using MVVM and RESTful APIs, following OWASP mobile guidelines with strong encryption. Worked in a remote Agile/Scrum team using Jira and Trello.

Built a secure web application using Angular 13, Node.js, and MongoDB with RSA/AES encryption and OAuth 2.0 authentication.

Secured RESTful APIs with JWT/OAuth 2.0, configured NGINX with SSL certificates, and ran basic penetration tests.

Currently completing the Machine Learning Specialization, covering key machine learning concepts and techniques.

Grade: 16.97/20

Licence STS in Computer Science with Highest Honors (Très Bien) and a grade of 16.97/20, earning 180 ECTS credits.

Grade: A2 (CEFR)

German language training from A1 to B2 levels, including a 90-hour A2 course and a 60-hour B2.2 intensive course.