Projects

Medical Equipment Failure Prediction System
Team Size: 8 Live : Click

• Led an 8-member team in the Hackathon to develop a predictive maintenance solution for medical equipment.
• Built a Gradient Boosting Machine Learning model achieving 91% prediction accuracy for equipment failure detection.
• Performed data preprocessing, feature engineering, and exploratory data analysis on operational datasets.
• Designed a risk scoring and maintenance recommendation system to reduce equipment downtime and improve patient safety.
• Applied AI-driven insights to support proactive maintenance and operational decision-making.

Food Health Evaluation System
Team Size: 3

• Developed an AI-driven food quality assessment system using OCR (Tesseract) to extract ingredient information from food labels.
• Implemented Convolutional Neural Networks (CNN) to predict food health scores and classify items as Good, Moderate, or Bad.
• Integrated the Edamam API to enrich nutritional data and improve ingredient-level analysis.
• Designed an end-to-end ETL pipeline for data extraction, preprocessing, and health evaluation.
• Built an automated system to help users make informed dietary decisions through transparent nutrition insights.

AI Image Generator (MERN Stack), June 2025 – July 2025
GitHub: Click

• Developed a full-stack AI-powered image generation platform using MERN stack integrated with Stable Diffusion API.
• Built RESTful APIs using Node.js and Express.js for image generation, storage, and community sharing.
• Implemented Cloudinary for image hosting and MongoDB (Mongoose) for managing user posts and prompts.
• Designed a responsive UI using React, styled-components, and MUI with support for light/dark themes.
• Enabled features like image search, gallery browsing, and prompt-based filtering for enhanced user experience.

MERN E-Learning Platform, May 2025 – June 2025
Full Stack Web Application (Team-2)
GitHub: Click

• Developed a full-stack E-Learning platform using MongoDB, Express.js, React.js, and Node.js.
• Implemented JWT-based authentication with role-based access for students, instructors, and admins.
• Built RESTful APIs for course creation, enrollment, quizzes, assignments, and progress tracking.
• Integrated Cloudinary and Multer for secure video and resource uploads.
• Designed a responsive UI using React, Redux, and Bootstrap/Tailwind CSS with secure password handling via bcrypt.

Stock Price Analysis & Prediction, Dec 2024 – Jan 2025
Data Analytics Project
GitHub: Click   

• Analyzed historical stock data to identify trends and market patterns.
• Performed data cleaning, preprocessing, and feature engineering using Pandas and NumPy.
• Built predictive models using Linear Regression, Random Forest, and Gradient Boosting.
• Evaluated models using MSE and achieved up to 0.85 R² score.
• Visualized results using charts and proposed improvements for real-time forecasting.

Customer Churn Analysis, Dec 2024 – Jan 2025
Data Analytics Project
GitHub: Click

• Analyzed customer data to identify key factors influencing churn, focusing on contract type, payment method, and customer tenure.
• Identified that 42% of month-to-month customers churned compared to only 3–11% of long-term contract users.
• Discovered that customers using electronic check payments had a 45% churn rate, significantly higher than other payment methods.
• Performed data cleaning, preprocessing, and exploratory data analysis using Pandas and NumPy.
• Visualized churn trends using charts and graphs and provided data-driven recommendations to improve customer retention.