Niv Neuvirth
Passionate Fullstack Developer and Computer Science student with a talent for building dynamic, user-friendly web applications.
Passionate Fullstack Developer and Computer Science student with a talent for building dynamic, user-friendly web applications.
DBT is a full-stack web application that allows users to explore and discover popular tourist attractions. Built using React for the frontend and Node.js/Express for the backend, the application connects to a PostgreSQL database hosted on Azure Cloud. The platform features a responsive design with Material-UI, secure JWT-based authentication, and a seamless user experience. It was deployed with Netlify for the frontend and Render for the backend, ensuring fast and reliable access to data for travelers.
The Cost Manager is a backend project designed to help users track and manage their expenses efficiently. Built with Node.js and Express.js for the backend and MongoDB Atlas for Cloud data storage, the project features a structured database with two collections—'users' for authentication and 'costs' for storing expense records. I developed a set of RESTful API endpoints using GET and POST requests to handle expense tracking, user authentication, and data retrieval. To test and document the API, I used Postman, ensuring smooth and efficient communication between the client and the server. Additionally, I implemented unit testing in Python to verify the core functionalities, improving code reliability and accuracy
This project is a Windows-based American Checkers game developed in C# with Windows Forms. The main goal was to create a structured and modular application that separates the game logic from the user interface, allowing future enhancements. The project follows an event-driven programming approach, using event handlers for game interactions. Technologies used include C#, .NET Framework, Windows Forms (WinForms), and Object-Oriented Programming (OOP) principles. This structured approach ensures that the interface can be upgraded easily, such as transitioning to a graphical or web-based version in the future.
This project focuses on representing the functionalities and interactions of a self-checkout system through visual diagrams and models. Additionally, a graphical user interface (GUI) has been developed using Python, utilizing the generated code from the Statecharts to create an interactive interface for users to simulate the self-checkout process.
As part of my data science course, I developed a project to explore factors that contribute to a beer's rating and predict its score. Using thousands of beer data entries, I conducted data scraping, handling, exploratory data analysis (EDA), and machine learning techniques to analyze and visualize key trends. The project culminated in building a machine learning model that predicts beer ratings based on specific features, with insights on what makes a beer highly rated.
Holon Institute of Thecnology, 2022-2025
GPA: 88/100
Please contact me through the form below or directly at niv.neu@gmail.com