Farzine Hossen

Gaibandha Students Association Website

• Tech Stack: NodeJS, NextJS, ExpressJS, Node Mailer, MongoDB, Cloudinary
• Website URL: www.gsa-sust.org

Developed a full-stack web platform with a dedicated admin panel for the Gaibandha Student Association at SUST to manage member activities, events, gallery, notices, and member information.

Implemented a user-friendly interface using NextJS and NodeJS, allowing members to easily access information and updates related to the association.

Integrated a robust admin panel for efficient management of member activities, events, and notices, enhancing the overall functionality and user experience of the platform.

ICERIE-2025

• Tech Stack: NodeJS, NextJS, ExpressJS, MongoDB, SUST e-payments, Javascript, Cloudinary
• Website URL: icerie2025.sust.edu

Developed the official website for ICERIE 2025 at SUST to showcase conference details, manage registrations and payments, display schedules, and provide updates for participants and organizers.

Implemented a user-friendly interface using NextJS and NodeJS, allowing participants to easily access information and updates related to the conference.

ICAP-2025

• Tech Stack: NodeJS, NextJS, ExpressJS, TailwindCSS, MongoDB, SSLCOMMERZ
• Website URL: icap2025.sust.edu

Built the official website for ICAP 2025 at SUST to provide conference information, facilitate participant registration, and manage schedules, announcements, and updates for attendees and organizers.

The website serves as a comprehensive platform for the International Conference on Advanced Physics (ICAP) 2025, offering essential details about the conference, including schedules, speaker information, and registration options. It also features a user-friendly interface for participants to access important announcements and updates related to the event.

Effective-learning through improved prompt design

• Tech Stack: Fewshot-prompting, GPT-API, NextJS, JavaScript, MOngoDB, TailwindCSS
• Website URL: effective-learning-nu.vercel.app

Developed a research data collection website utilizing few-shot prompting to gather user responses and feedback for studying effective learning through improved prompt design.

The website is designed to collect user responses and feedback on various prompts, enabling researchers to analyze the effectiveness of different prompt designs in enhancing learning outcomes. It employs few-shot prompting techniques to guide users in providing meaningful input, thereby facilitating a more structured and insightful data collection process.

FarmAI

• Tech Stack: NodeJS, NextJS, ExpressJS, MongoDB, Finetuned Yollo Model, GPT-API
• Website URL: farm-ai-fz.vercel.app
• Github URL: Project Link

A deep learning-based crop disease detection and prevention system using YOLO, integrated with a related marketplace to support farmers with actionable insights and relevant resources.

FarmAI is a comprehensive solution designed to assist farmers in identifying and managing crop diseases. By leveraging advanced deep learning techniques, the platform provides real-time disease detection and actionable insights, empowering farmers to make informed decisions. The integration of a marketplace further enhances the user experience by offering relevant resources and products tailored to their needs.

Chol-Kheli

• Tech Stack: NodeJS, ExpressJS, NextJS, Web Socket, MySQL
• Github URL: Project Link

Developed an online auction platform for cricket and football players, featuring live bidding, team and player management, and admin controls to facilitate seamless team formation and tournament setup

The project was developed as a part of my BSc in course project at the University. It was a collaborative effort with my team members, and I played a key role in the backend development using NodeJS and ExpressJS, as well as implementing real-time features using Web Socket. The platform allows users to register, create teams, and participate in live auctions for players, enhancing the overall experience of managing sports teams online.

Lemon Leaf Disease Detection

• Tech Stack: Fine Tuned Yollow Model, Roboflow, NextJS, Dataset, Notebook, Kaggle
• Website URL: lemon-leaf-diseases-detection-ai.vercel.app
• Github URL: Project Link

The Lemon Leaf Disease Detection is a web application that uses a fine-tuned YOLO model to detect diseases in lemon leaves. The application is built using Next.js and utilizes the Roboflow platform for model training and deployment. The dataset used for training the model is sourced from Kaggle, ensuring high-quality data for accurate disease detection.

The application allows users to upload images of lemon leaves and receive real-time predictions on whether the leaves are healthy or affected by diseases. The fine-tuned YOLO model ensures high accuracy in detecting various diseases, making it a valuable tool for farmers and agricultural professionals.

IICT-SUST

• Tech Stack: NextJS, NodeJS, PostgreSQL, Nodemailer, Cloudinary
• Website URL: iict-sust-swe.vercel.app

IICT-SUST is a comprehensive web application designed to facilitate the management of student information, course details, and faculty data for the Institute of Information and Communication Technology (IICT) at Shahjalal University of Science and Technology (SUST). The application features a user-friendly interface that allows students to register, view their courses, and access faculty information. Faculty members can manage their profiles and courses efficiently. The backend is powered by NodeJS with PostgreSQL as the database, ensuring robust data handling and security. The application also integrates Nodemailer for email notifications and Cloudinary for image storage.

DP-Learning App

• Tech Stack: Flutter, Dart, Riverpod, NodeJS, ExpressJS, MongoDB, Google Map, Gemini api
• Github URL: Project Link

This is a mobile application designed to help users learn about design patterns in software development. It provides a user-friendly interface for exploring various design patterns, understanding their concepts, and implementing them in real-world scenarios. The app includes features such as interactive tutorials, code examples, quizzes, and a community forum for discussions. It aims to enhance the learning experience by providing practical insights and hands-on exercises related to design patterns.

Candle Stick

• Tech Stack: Apache ECharts, Shadcn, NextJS
• Github URL: Project Link

A candlestick chart visualization tool that displays Apple Inc. stock price data using Apache ECharts and shadcn UI components.

This project utilizes the Apache ECharts library to create an interactive candlestick chart that visualizes stock price movements over time. The chart is designed to provide insights into the stock's performance, including opening, closing, high, and low prices for each trading day.

Waste Management App

• Tech Stack: Flutter, Firebase, Google Auth
• Github URL: Project Link

The Waste Management App is a mobile application designed to facilitate the management and recycling of waste materials. It provides users with a platform to report waste issues, find recycling centers, and learn about proper waste disposal methods. The app integrates with Firebase for data storage and retrieval, and it uses Google Authentication for secure user login.

3D Car Game

• Tech Stack: Unity, C#
• APK File: Download

Developed a 3D car game using Unity and C#, featuring realistic physics, dynamic environments, and engaging gameplay. The game allows players to experience driving in a virtual world with various terrains and challenges.

Brick Changer Game

• Tech Stack: Java, Java Swing
• Github URL: Project Link

Developed a Brick Changer game using Java and Java Swing, Here i learn how to use Java Swing for GUI development and implement game logic in Java.

Golf Game with SFML

• Tech Stack: C++, SFML library
• Github URL: Project Link

Developed a console golf game using C++ and the SFML library, featuring realistic physics, multiple levels, and engaging gameplay.

Console Snake Game

• Tech Stack: C++, Graphics.h library
• Github URL: Project Link

Developed a console-based Snake game using C++ and the Graphics.h library, featuring classic gameplay mechanics, dynamic levels, and engaging user interaction. The game allows players to control the snake, collect food, and grow in size while avoiding collisions.