Work Samples

Technical exposure

These are honest examples of technologies and problem areas I have worked with. The focus is what each sample demonstrates.

Live App

FutArabi

A live, SEO-optimized web application deployed on a DigitalOcean droplet using Docker.

Demonstrates: taking an application from code to deployment, Docker-based hosting, server operations, SEO-focused growth, and maintaining a public-facing product that generated 400K+ visits over 3 years without ads, tracked through Google Analytics and Google Search Console.

  • ASP.NET MVC
  • Docker
  • DigitalOcean
  • SEO
  • Google Analytics
  • Search Console
  • Deployment
  • GitHub
WordPress

Shatlat

A live WordPress blog focused on SEO-oriented content structure, publishing, and site operations.

Demonstrates: running a live content site, WordPress administration, SEO-focused publishing, and maintaining a public web property.

  • WordPress
  • SEO
  • Content operations
  • Live site
  • Visit
Static Web

Brackets Contracting Co.

A concise static portfolio microsite for a contracting company, built from the company's technical PDF portfolio and organized around services, sectors, project proof, and contact paths.

Demonstrates: static HTML/CSS/JS delivery, responsive layout, PDF content extraction, portfolio information architecture, project filtering, subtle UI animation, and building a deployable subfolder experience for shared hosting.

  • HTML
  • CSS
  • JavaScript
  • Responsive design
  • Information architecture
  • View
Backend API

Mirsal API

A Java Spring Boot API for an anonymous message-in-a-bottle style product with authentication, bottle delivery, accept/reject/resend flows, conversations, messages, inbox, and outbox.

Demonstrates: Spring Boot REST APIs, JWT authentication, PostgreSQL schema design, Flyway migrations, JDBC repositories, domain services, Docker Compose, and focused unit tests.

  • Java 21
  • Spring Boot
  • PostgreSQL
  • Flyway
  • JWT
  • JUnit
  • GitHub
ML

Computer Vision and ML

A graduation project that used computer vision to predict possible cheating during online exams.

Demonstrates: research, Python implementation, OpenCV/Dlib usage, and ML-adjacent problem framing.