InfraSense
Smart civic infrastructure management platform that allows citizens to report issues with images and location. Uses a MobileNet-based ML model to automatically predict issue severity and help authorities prioritize resolutions.
I build fast, accessible, and beautifully crafted web experiences. Currently leading web development at GDG SDSF.
I'm a third-year Integrated M.Tech student in Artificial Intelligence and Data Science at DAVV, Indore, with a strong interest in web development and machine learning.
I enjoy building modern, performant web applications and exploring how data-driven and intelligent systems can be used to solve real-world problems.
I'm always eager to learn new technologies, expand my skill set, and contribute to meaningful projects in the tech community.
Technologies and disciplines I use to build products end-to-end.
HTML, CSS, JavaScript, React, Tailwind CSS, Responsive UI
Node.js, Express.js, REST APIs,Flask, MongoDB, MySQL, API Integration
Python, Machine Learning Foundation, Scikit-learn, AI Concepts
C · C++ · Python · JavaScript· Java · SQL
Git, GitHub, Vercel, Render, Firebase, CI/CD Concepts
Team Leadership, Community Building
Smart civic infrastructure management platform that allows citizens to report issues with images and location. Uses a MobileNet-based ML model to automatically predict issue severity and help authorities prioritize resolutions.
ServEase is a full-stack local service booking platform where users can discover and book verified service providers for various home and professional needs. Built with MERN stack it features service browsing, appointment booking, and a provider dashboard for managing services and availability.
A machine learning system to detect fraudulent financial transactions using Scikit-learn models. Implemented class imbalance handling with SMOTE and evaluated performance using precision, recall, and ROC-AUC. Developed an interactive Streamlit dashboard for fraud prediction, risk scoring, and analytics visualization.
Built a Python-based analytics tool that leverages the GitHub API to analyze repositories, extract technical skills, and categorize them into domains. Implemented portfolio scoring, experience level prediction, and role recommendation logic, with an interactive visualization dashboard using Streamlit and Plotly.