Junior Data Scientist and AI Engineer
Junior Data Scientist and AI Engineer with a strong foundation in machine learning, computer vision, and generative AI. She has a proven ability to develop and implement AI solutions, demonstrated through projects with hands-on experience in data analysis. Eager to apply technical expertise to solve complex real-world challenges.
Expertise in developing and implementing machine learning models, coupled with strong data analysis skills.
Proficient in applying deep learning techniques to computer vision and pattern recognition, including image caption generation.
Foundational and advanced knowledge in generative AI model development, including Retrieval-Augmented Generation (RAG) systems.
Strong programming skills in multiple languages and a proven track record in competitive programming.
An end-to-end Retrieval-Augmented Generation (RAG) web application system allowing users to upload long documents and interact with them via a conversational assistant.
Impact: Enables efficient information retrieval and understanding from complex documents with chat-based Q&A and source citations.
Developed a deep learning model for automatic image caption generation specifically applied to retinal (fundus) images.
Impact: Aims to assist in clinical diagnosis by providing natural language descriptions of eye diseases.
Built a comprehensive database integrating data on populous cities, country economics, population statistics, and languages spoken.
Impact: Serves as a robust data source for geographical and economic analysis.
Completed Deep Learning for Computer Vision Upskilling Program at NTI.
Completed Level 2 of the ITI-NVIDIA Generative AI Program.
Served as a Microsoft Machine Learning Engineer Trainee at Digital Egypt Pioneers Initiative (DEPI).
Certified in CS50 SQL by Harvard.
Certified in CS50 Python by Harvard.