Experience

PhD in Artificial Intelligence

Topic: Handwritten Text Recognition of medieval Arabic scientific manuscripts and development of dedicated LLM.

State Engineer's Degree in AI & Computer Science Engineering

Selective access based on average. Graduated with Highest Distinction.

Integrated Preparatory Cycle in Mathematics, Physics & Engineering Sciences

Baccalaureate in Mathematical Sciences (French option)

Highest Distinction.

Doctoral Researcher, ATHAAR Project

Automatic recognition of al-Bīrūnī's al-Qānūn al-Masʿūdī to support its critical edition.

• Building an HTR ground-truth dataset from the manuscript witnesses using Calfa Vision and PAGE-XML.
• Benchmarking vision-language models and LLMs in zero-shot and few-shot settings.
• Developing an error taxonomy and a rule-based automatic error classifier.

Research Intern, AI & Medical Imaging

Medical image segmentation using few-shot learning techniques.

• Conducted a state-of-the-art review of segmentation algorithms with limited data and few-shot learning.
• Processed MRI and CT images, understanding their specificity and formats.
• Developed a segmentation model based on the U-Net architecture in a few-shot learning configuration.

Volunteer Computer Vision Developer

Intelligent platform for real-time sign-language to text translation.

• Conducted a state-of-the-art review of hand detection and segmentation methods.
• Developed a CNN-based algorithm for hand gesture recognition.
• Created an interface and deployed developed algorithms using Flask and OpenCV.

Computer Vision Intern

Intelligent solution for segmentation of damaged vehicle areas.

• Collected and processed car images using Python, Selenium, and Scrapy.
• Implemented a CNN for classification of damaged vehicles using PyTorch.
• Developed a licence plate verification algorithm combining CNNs and OCR.

AI & Image Processing Intern

PPE detection from video to minimise operational risks in industrial environments.

• Built a structured dataset containing various PPE classes from diverse sources.
• Designed a PPE detection and recognition algorithm based on CNNs.

Teaching Assistant, 32h of lab sessions

Undergraduate teaching in algorithms and artificial intelligence.

• Algorithms (L1): 26h of Python lab sessions covering sorting and complexity.
• Artificial Intelligence (CUPGE, Year 2): 6h of lab sessions.

Supervision of an M2 Research Internship

Corpus annotation for the ATHAAR project.

• Defined the annotation strategy and wrote a detailed annotation guide.