About Me
I’m passionate about creating digital experiences that are both meaningful and easy to use. I enjoy turning ideas into clear, functional solutions, with a focus on simplicity, thoughtful design, and user needs.
I value organization, attention to detail, and continuous improvement, and I’m always exploring new ways to grow and refine my skills. I believe that good design is not just about how things look, but how they work and connect with people.
My goal is to create digital solutions that are impactful, intuitive, and genuinely useful
Skills & Tools
Selected Work
VeriNews App
VeriNews is an intelligent mobile application designed to verify the authenticity of news and combat the spread of misinformation. It allows users to input news content or links, which are then analyzed using AI-based techniques and reliable data sources.
The app compares the content against multiple trusted references to determine its credibility and provides a clear result to help users make informed decisions before sharing any news.
This project focuses on promoting digital awareness and supporting a more accurate and trustworthy information environment, especially in the era of rapid social media content sharing.
Riyadh Season
This project focuses on designing and implementing a SQL database for Riyadh Season, one of the most significant entertainment events in Saudi Arabia. It was developed to manage and organize large-scale real-world data related to events, activities, and attractions.
The project demonstrates how complex and high-volume data can be structured efficiently using SQL database systems. It also reflects the real-life impact of Riyadh Season on both society and the economy, while enhancing our practical skills in database design and management.
The goal was to create a realistic system that closely simulates real-world data handling scenarios and improves our understanding of database concepts through a large and meaningful project.
FLORA FINDER
This project focuses on building a machine learning model to classify iris flowers into three species: Iris setosa, Iris versicolor, and Iris virginica. The classification is based on key physical measurements of the flowers, including sepal length, sepal width, petal length, and petal width.
The goal of the project is to train a model that learns from these features and accurately predicts the correct species of a given iris flower. This helps automate the classification process using data-driven techniques instead of manual identification.
The project demonstrates the practical application of machine learning in pattern recognition and highlights how data analysis can be used to solve real-world classification problems.
Work Experience
Intern - Data Verification
Tabuk Municipality
- •• Entered and verified data accuracy within the system using Balady platform
- •• Assisted in reviewing and organizing documents and records to ensure compliance
Education
Bachelor in Computer Science
University of Tabuk