I'm an Artificial Intelligence graduate from Umm Al-Qura University with hands-on experience in machine learning, natural language processing, generative AI, intelligent automation, and data analysis.
I enjoy building practical AI solutions that connect models and data with real-world applications.
- Machine Learning & Deep Learning
- Natural Language Processing (NLP)
- Generative AI & Large Language Models
- Retrieval-Augmented Generation (RAG)
- Computer Vision
- Intelligent Automation
- Data Analysis
Languages: Python, SQL, Java
AI & ML: PyTorch, Transformers, Scikit-learn, Pandas, NumPy, NLTK
LLMs: RAG, Fine-Tuning, QLoRA, Hugging Face Transformers
Development: FastAPI, Streamlit, Git, GitHub
Data & Automation: Airtable, Make, Pabbly, Power BI
Graduation project developed in collaboration with the Saudi Geological Survey.
Co-developed a domain-specific AI digital twin designed to preserve expert geological knowledge and provide reliable, cited responses through interactive text and avatar interfaces.
Technologies: LLMs, RAG, QLoRA Fine-Tuning, NLP, FastAPI, Python
Developed an interactive guest seating and capacity-planning system that organizes guests based on priority, calculates seating capacity, automatically assigns seats, and generates visual seating plans.
Technologies: Python, Streamlit, Pandas, Matplotlib, NumPy
Developed and evaluated NLP pipelines for mathematical problem classification using transformer-based embeddings and machine learning.
Technologies: SciBERT, NLP, Machine Learning, Python
Developed a computer vision prototype as part of the Health & Security in Hajj Hackathon Forum, exploring AI-based visual monitoring to support security personnel at inspection points and critical locations during Hajj.
Technologies: Computer Vision, OpenCV, Python, Streamlit
Developed an AI-based emergency triage concept during the 5th Health Innovation Hackathon to support faster patient prioritization using medical history and vital signs.
The concept was designed to help reduce delays associated with manual triage, ease emergency department congestion, and improve healthcare resource utilization.
Focus: Artificial Intelligence, Machine Learning, Healthcare Technology
- 📍 Makkah, Saudi Arabia