Frontend Developer

Sadeen Ryahi

Building clean, responsive web experiences focused on usability, and real-world impact.

About

Frontend Developer focused on building responsive and user-centered web applications. Experienced in Vue.js, JavaScript, HTML, and CSS, with a strong focus on creating clean, intuitive interfaces and enhancing user experience through real-world projects.

Built and worked on projects including web applications, chat interfaces, and a clinic booking system, gaining hands-on experience in API integration and working with data using SQL, PHP, and Python.

Currently expanding skills in backend development and full stack concepts, with ongoing work in Node.js, APIs, and database integration.

Projects

Other Projects

Python Project

Data Scraper

Fetches product listings from a target site, parses the HTML, and collects structured fields for each item so they can be reviewed or analyzed offline.

Example extracted fields

  • Title Wireless Headphones Pro
  • Price $79.99
  • Rating 4.6 / 5 (128 reviews)
  • Links product URL, image URL

Output is saved as a CSV file with one row per item for spreadsheets or further processing.

Python BeautifulSoup Requests
GitHub
Backend Project

Image Processing API

RESTful API built with Node.js and Express that dynamically resizes images using query parameters.

Implements caching for processed images to improve performance, and includes automated testing using Jasmine and Supertest with Sharp for efficient image processing.

Node.js Express TypeScript REST API Sharp Testing
GitHub
Computer Vision Project

Image Retrieval System

Computer vision system that retrieves visually similar images using feature extraction techniques on the Caltech-101 dataset.

Implements image representation and similarity-based ranking to return the most relevant images based on visual features.

Python Computer Vision Image Retrieval Feature Extraction
GitHub
AI Project

Text-to-Video Retrieval

Deep learning retrieval system that returns the most relevant video for a natural language query using a dual-encoder architecture.

Uses a CNN (ResNet18) to encode video and a Transformer (DistilBERT) to encode text, then projects both modalities into a shared embedding space for similarity-based retrieval.

Python PyTorch Deep Learning Computer Vision NLP
GitHub

Skills

Frontend

Vue.js, JavaScript, HTML, CSS

Backend Knowledge

PHP, Python Flask, REST APIs

Databases

SQL, MySQL, PL/SQL

Tools

Git, GitHub, VS Code, Postman

Familiar With

Node.js, PostgreSQL, Docker, Airflow, Machine Learning