About Me
Full Stack MERN Developer with expertise in React.js, Next.js, Node.js, Express.js, and MongoDB. Passionate about creating modern web applications and continuously improving my skills.
Experience
1+
Years
Projects
4 +
Completed
Verified Certifications
Issued by Mern · 2026
Work History
MERN STACK INTERN
Dooritt · Aug 2025 - Feb 2026
• Built and optimized full-stack modules for a real estate platform, improving page load performance by ~35% through code splitting and lazy loading. • Streamlined property buying workflows, improving operational efficiency for 500+ daily active users; resolved 20+ critical production bugs reducing error rate by 60%. • Developed RESTful APIs for property search, filtering, and user management using Node.js, Express.js, and MongoDB Atlas.
MERN STACK TRAINEE
Auspicious Soft Pvt. Ltd. · Jan 2025 - Jul 2025
Built 3+ full-stack web apps using MVC architecture, React.js, and reusable components; developed secure REST APIs with CRUD, JWT auth, and session handling. • Created responsive UIs with Tailwind CSS and real-time chat using Socket.IO for 100+ concurrent users; used Git, Postman in an Agile environment.
Featured Projects
Tech: React.js, Tailwind CSS, MongoDB, Node.js, Express.js • Led a 20-member team to build and deploy an alumni platform supporting 50,000+ student records with secure login, faculty directory, notifications, and full admin panel.
Tech: Next.js, MongoDB, Auth.js, Tailwind CSS, Vercel https://teachertrack.vercel.app/ • Role-based full-stack app (Admin / Teacher / Student) with secure Auth.js authentication, assignment management dashboards, and submission tracking.
Research Paper Reading Tracker is a web application designed to help users organize, save, and track research papers efficiently. It offers a simple and user-friendly way to monitor reading progress and manage academic content in one place.
This project is a matchmaking dashboard that helps users organize customer profiles, rank compatible matches, and manage outreach actions like sending matches and adding notes. It uses a rule-based scoring system with gender-specific logic to generate explainable match rankings and personalized intros. The UI is clean, emotionally aligned, and readable, while the code is modular, maintainable, and scalable. Overall, it combines practical CRUD features, smart matching logic, and human-centered design into a real-world matchmaking workflow tool.