Hi, I'm Aryan Mohammadi
Full Stack Developer | Data Analyst | Machine Learning Developer
Full Stack Developer with a strong background in data analysis and machine learning. Experienced in building modern web applications and data-driven solutions using tools like React, Node.js, Python, and ML libraries.

My Projects
A curated showcase of my latest work and contributions

Portfolio Website
A personal portfolio website built with Next.js and Tailwind CSS. Features responsive design and dark mode support.

Echoes of the Steps
Contributed to Echoes of the Steps, a narrative-driven game, by designing interactive elements, immersive audio, and atmospheric effects like rain, enhancing the player's emotional and sensory experience.

CINEMAGO
CINEMAGO is a mobile application developed using Expo and powered by MongoDB Atlas, designed to provide users with a seamless cinema booking experience. The project focuses on delivering essential functionalities for moviegoers, from ticket bookings to user profile management.

Automotive Dealership
Developed a feature-rich car dealership website showcasing Toyota, Mercedes-Benz, and BMW, with a focus on user-friendly browsing, secure test drive bookings, and an admin panel for content management—emphasizing both seamless UX and robust data privacy.

Hamk Design Factory project
This project focuses on providing constructive feedback to students based on their responses to questions. The aim is to improve overall learning outcomes by analyzing data and creating insightful charts that highlight trends and areas for improvement.

Pizzurger Restaurant
This project is tailored for Hamk University, aiming to design, develop, and implement a comprehensive Restaurant Management System for Pizzurger. The focus lies in creating a seamless user experience, both for the customers interacting with the frontend and the staff managing the backend. The project encompasses the entire lifecycle, from initial design to code implementation.

Taylor Series Visualizer
This project combines mathematical intuition with programming to demonstrate how Taylor series approximate functions like e^x, sin(x), and cos(x). Developed using Python and Jupyter Notebook, it includes animated visualizations that dynamically show how adding more terms improves the approximation. It's designed as a learning aid for both students and educators.

Automated News Categorization Using Natural Language Model Tools and Machine Learning Models
This project focuses on automating news article classification using Natural Language Processing (NLP) and machine learning. Utilizing the MN-DS dataset from Zenodo, it evaluates nine ML models to classify news into hierarchical categories. A Windows application built with PyQt provides a user-friendly interface for predicting article categories, enhancing efficiency for media professionals.