Computer Application student with a strong foundation in Java and JavaScript. Gained hands-on experience in developing web based applications through academic projects and internships. Skilled in analyzing complex challenges and building efficient software solutions within a team-driven environment.
• Designed and optimized the backend schema for the IPO module , ensuring 99.9% uptime and scalability for 1M+ transactions .
• Implemented database normalization and indexing , enhancing query performance by 50% and reducing latency from 500ms to 250ms .
• Developed and deployed RESTful APIs handling 100,000+ IPO transactions daily , ensuring secure and efficient data exchange .
• Led a team of four developers to integrate financial data processing workflows , reducing manual effort by 30% .
• Strengthened data integrity and validation , reducing compliance violations by 40% and passing audits with zero major issues .
Java, JavaScript
HTML5, CSS3, ReactJS
Npm, NodeJS, Express JS
MySQL, MongoDB
Git, Github
Linux, MacOS, Windows
Splitwise – Expense Sharing Web App
• Developed a full-stack expense management system using MongoDB, Express.js, ReactJS, and Node.js , inspired by Splitwise, for tracking shared bills and managing group finances.
• Engineered real-time expense splitting, debt settlement logic, and transaction histories , enabling efficient group and individual cost management.
• Integrated JWT authentication , Redux for state management, and a responsive dashboard UI for seamless, secure multi-user access.
• Leveraged Gemini AI to provide intelligent financial summaries, spending insights, and automated expense categorization , enhancing user experience and decision-making.
• Automated reconciliation tracking, reducing user effort and minimizing financial confusion in shared transactions.
• Used data visualization tools and responsive charts to present clear overviews of balances and settlements.
ByteShrink - A File Compressor and Decompressor
• Constructed a Data Structures and Algorithms project using the MERN stack, integrating an implemented Huffman Encoding
and Decoding Algorithm for improved performance.
• Devised a file compression and decompression system , reducing file sizes efficiently while maintaining data integrity.
• Enhanced encoding and decoding algorithms to enhance compression speed and improve storage efficiency.
• Ensured lossless data compression , preserving original content while minimizing space usage.
LRU Cache Implementation in a Chat Application
• Redesigned a high-performance caching system project using MongoDB, Express, and ReactJS, integrating a Least
Recently Used (LRU) Cache for enhanced performance.
• Engineered efficient message storage and retrieval , reducing database queries and enhancing response times.
• Built a session management system with caching, ensuring seamless user authentication and faster access to
recent conversations.
• Leveraged file compression algorithms and caching strategies for media assets, shrinking bandwidth consumption by 15%
and on average, accelerating page load times by 2.1 seconds.