Projects 💻
Step into my laboratory of innovation, where comfort zones are merely starting points and each project is a bold leap into the unknown—here's to coding daringly and living on the edge of possibility!
- • Developed a real-time document editing platform with WebSocket communication for live updates and user synchronization
- • Implemented session management and document versioning, ensuring consistent data integrity across multiple users
- • Enhanced user experience by integrating gRPC and Protocol Buffers for efficient communication and DynamoDB for robust data storage
- • Utilized AWS EC2 for scalable deployment and Docker for containerization, ensuring high availability and portability of the service
- • Designed the system to handle concurrent user edits, minimizing conflicts and providing real-time conflict resolution
- • Improved document synchronization speed by 20% through optimized WebSocket handling and efficient data transmission protocols
Real-Time Document Collaboration Service | Go, gRPC, WebSocket, AWS, Docker, Protocol Buffers | GitHub
- • Increased concurrent upload capacity by 30% & reduced processing time, by integrating AWS SQS for efficient uploads to S3
- • Reduced data sync time by 15% using DynamoDB and Lambda, enhancing event-driven triggers & real-time handling
- • Introduced real-time alerts for video creators via Kafka, thus increasing user engagement in terms of comments and likes
- • Enhanced video playback quality by coupling AWS S3 with CloudFront, ensuring high-quality content delivery to end-users
StreamCraft - Video Streaming Service | Javascript, AWS (S3, DynamoDB, Lamda, CloudFront), Kafka | GitHub
- • Developed browser plugin for summarizing job descriptions & identifying key skills, using Falcon 7B (Large Language Model)
- • Employed Flask for LLM interactions and Node.js with Express.js for managing other backend services, hosted on AWS
- • Enhanced plugin scalability and reliability by using AWS EC2 for hosting and AWS Lambda for asynchronous operations
Job Description Summarization Plugin | Flask, Generative AI, Large Langauge Models, AWS
- • Built full-stack social media application using MERN stack, enabling user registration and login, & dynamic real-time updates
- • Designed a responsive and engaging frontend with ReactJS, integrated with an Express.js API for user activity handling
- • Utilized MongoDB’s NoSQL flexibility for efficient, scalable management and quick retrieval of user data, posts, and comments
CROWD - A Social Network Application | MongoDB, Express.js, React, Node.js (MERN) | GitHub
- • Developed a real-time stock portfolio management application in Java, achieving robust and scalable design by implementing MVC architecture with design patterns like Factory and Singleton, adhering to SOLID principles
- • Attained 97% code coverage and minimized potential defects by rigorously writing JUnit tests for functionality testing
- • Ensured efficient data caching and accessibility by fetching real-time stock data using the Alphavantage API, storing it in SQL, and employing programming constructs like stored procedures, functions, and triggers
Stock Portfolio Management | Java, MVC, SQL, Object-Oriented Programming & Design | GitHub
- • Increased concurrent upload capacity by 30% & reduced processing time, by integrating AWS SQS for efficient uploads to S3
- • Reduced data sync time by 15% using DynamoDB and Lambda, enhancing event-driven triggers & real-time handling
- • Introduced real-time alerts for video creators via Kafka, thus increasing user engagement in terms of comments and likes
- • Enhanced video playback quality by coupling AWS S3 with CloudFront, ensuring high-quality content delivery to end-users
Credit Worthiness of a Customer | Self-supervised Machine Learning, Binary Classification Model | GitHub
- • Optimized ResNet101 architecture to accurately detect face masks over faces, achieving a remarkable 99% detection accuracy
- • Implemented a Deep Metric Learning network with ResNet-34 architecture, for recognizing individuals’ faces with precision
Face Mask Detection and Face Recognition | Computer Vision, Deep Learning | GitHub | Manuscript
- • Attained 87% accuracy in identifying answer phrases using a Gaussian Naive Bayes classifier on the SQuAD 1.0 dataset
- • Utilized word embeddings and cosine similarity to generate distractors for the questions, enhancing the tool’s robustness