Mehdi
Ranjbar

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Finished gigs

Finished jobs

Website

Not specified

Country

Not specified

Specialization

Full-Stack Engineer | Spring Boot (Backend) | Next.js (Frontend) | Kotlin (Android/KMP)

Hourly rate

$15/hr

Preferred payment options

ETH

USDT

About me

I am a Software Engineer with a strong background in Android development, Kotlin ecosystem technologies, and modern full-stack web development. I started programming in 2018 with Android development using Java and XML, and later transitioned to Kotlin and Jetpack Compose. Over the years, I have worked with modern Android architectures including MVVM and MVI, as well as technologies such as Dependency Injection, Kotlin Coroutines, KMP (Kotlin Multiplatform), and Compose Multiplatform. I hold a Bachelor's degree in Computer Engineering (Information Technology) from Shahrekord University and a Master's degree in Artificial Intelligence from Islamic Azad University, Najafabad Branch. My master's thesis focused on Improving Aspect-Based Sentiment Analysis Using Contrastive Learning. Since 2024, I have been working at Tafakor va Negresh Moj Chaharom Company located in the Science and Technology Park of Chaharmahal and Bakhtiari province. During this time, I have contributed to various rea

Work experience

Fourth Wave Thinking and Attitude

December 2025 – Current time

Job title

back-end developer

Work experience & achievements

Software Engineer Fourth Wave Thinking and Attitude Company 2024 - Present * Developed and maintained full-stack web applications using Next.js, Express.js, NestJS, Spring Boot, MongoDB, and PostgreSQL. * Worked on SEO optimization and content management for company projects. * Migrated a WordPress-based website to Next.js. * Built and maintained frontend interfaces using modern JavaScript technologies. * Collaborated on backend API development and database design.

Education

Shahrekord University

Graduation year: 2021

Level of study

Bachelor

Major / Field of study

Computer Engineering - Information Technology

Islamic Azad University, Najafabad Branch

Graduation year: 2025

Level of study

PGCE

Major / Field of study

Computer Engineering - Artificial Intelligence

Mehdi Ranjbar

(0)

I will rebuild your WordPress website into a modern Next.js web app

Web, Mobile & Software Dev

HTML

Javascript

$150

More info

Kishvan - Agri-Tech Marketplace & Job Board

I developed the backend for Kishvan.ir, a specialized marketplace and recruitment platform for the agricultural industry. The platform connects farmers, producers, employers, and job seekers directly. Key Features I implemented: Scalable RESTful API architecture using Express.js. Complex data modeling with MongoDB for diverse categories including Products, Equipment, Services, and Agricultural Jobs. Advanced filtered search system for real-time listing discovery and categorization. User authentication and role-based access control (RBAC) for multiple user roles including Sellers, Buyers, Employers, Employees, and Consultants. Premium package and subscription system with dynamic ad ranking, featured listings, auto-refresh logic, and time-based publishing management. Integrated order and payment workflow for activating advertisement packages and subscriptions. Optimized database queries to efficiently handle large-scale agricultural listings and high-traffic filtering operations. Tech

Kishvan.pdf

Polidasht.co — 5-Language Corporate Website (Custom WordPress → Next.js Rebuild)

Built and maintained the official website of Polidasht (polyethylene pipe manufacturer). The website is currently live on WordPress, originally developed by me around 3 years ago as a fully custom implementation (no themes/templates used). Recently, I rebuilt the entire website using Next.js to modernize the stack and improve performance and maintainability. The Next.js version is completed and ready for deployment. Developed the original WordPress website from scratch (custom build, no pre-made themes) Implemented and maintained a 5-language (i18n) structure Rebuilt the website with Next.js for better performance and modern architecture Improved SEO readiness, clean routing, and responsive UI Tech Stack Current live: WordPress (custom build) New version: Next.js (React) (+ Tailwind CSS / TypeScript if applicable) Features: Multi-language, responsive design, SEO optimization Live (WordPress): https://polidasht.co Next.js version: Completed (deployment pending

Crypto Market Tracker (Android) — Java + XML

Android app (2020) built with Java and XML that displays a list of cryptocurrencies with live market data fetched via REST APIs using Volley; users can tap on any coin to open a details screen showing price changes, market information, and chart visualization for better trend analysis.

Watch Store E‑Commerce Platform (Full‑Stack)

A full-stack e-commerce marketplace for luxury watches, built with a React frontend and a Node.js/Express backend with MongoDB. Key features include secure JWT-based authentication, a comprehensive admin dashboard for inventory management, a persistent shopping cart, and a seamless order workflow. The application is fully containerized using Docker and Docker Compose, ensuring a scalable and reproducible deployment environment.

Handicrafts E‑Commerce Platform (Full‑Stack)

A comprehensive full-stack marketplace for handmade products, featuring a robust Kotlin/Spring Boot backend and a modern Next.js frontend. The platform implements secure OTP-based authentication, advanced product and category management, a streamlined cart-to-checkout flow, order processing, and a native review system. The architecture is supported by automated database migrations and is fully containerized with Docker and Docker Compose for efficient development and production deployment.

Aspect-Based Sentiment Analysis Enhancement with Contrastive Learning and Adaptive Memory Mechanisms

Master's thesis research focused on advancing Aspect-Based Sentiment Analysis through a hybrid BERT-based architecture enhanced with supervised and unsupervised contrastive learning. The project incorporates Label-Aware Multi-Level Attention, Adaptive Memory Bank, Hard Negative Mining, Dynamic Loss Scheduling, and Augmentation-Aware Mutual Information Minimization to improve representation learning and robustness against noisy data. The research outcomes were accepted for publication and presented at the International Conference on Computer Engineering and Science (CCES 2025).

MehdiRanjbar