My Projects

AI-Powered Resume Analysis and Job Matching System

  • Designed an intelligent resume parsing and analysis system using advanced RAG techniques for candidate evaluation

  • Implemented PDF document processing with vector embeddings for semantic resume matching and ranking

  • Built ChromaDB integration for efficient resume storage, retrieval, and similarity matching

  • Developed conversational interface for resume queries, job matching, and candidate recommendations

  • Created automated resume ingestion pipeline supporting multiple document formats and structures

Distributed Systems Key-Value Store

  • Designed and implemented a scalable key-value store using a distributed systems approach.

  • Utilized gRPC and Protobuf for efficient inter-service communication.

  • Implemented consistency protocols such as leader election and replication to ensure data integrity.

  • Deployed the system using Docker, enabling containerized microservices.

Integrated Playwright MCP

  • Developed an intelligent test automation framework that generates Python Playwright test scripts from natural language descriptions

  • Built template-based test generation system ensuring 100% valid Python code with cross-platform compatibility

  • Created Streamlit web interface for seamless test management, execution, and reporting with real-time feedback

  • Implemented robust error handling, screenshot capture, and HTML reporting for comprehensive test analysis

  • Achieved zero syntax errors in generated tests with support for login, forms, navigation, and e-commerce scenarios

Music Genre Classification Application

  • Developed a music genre classification app using Python, TensorFlow, and Librosa.

  • Built a CNN model for data preprocessing and feature extraction.

  • Created a React interface for audio uploads and classification results.

  • Utilized GitHub for version control and teamwork, ensuring seamless collaboration and efficient project management.

  • Deployed the application on AWS, utilizing EC2 and S3 for scalable infrastructure.

Multi-Source RAG System

  • Engineered a sophisticated RAG system that processes and queries multiple data sources including PDFs, Excel files, and text documents

  • Implemented ChromaDB vector database with advanced document processing and response grading mechanisms

  • Built intelligent document processor supporting company policies, market analysis, and product specifications

  • Developed Excel data integration with financial, inventory, and sales data processing capabilities

  • Created public corpus integration for enhanced knowledge retrieval and context-aware responses

Social Media Sentiment Analysis

  • Developed a web application that analyzes sentiment from social media posts using natural language processing (NLP).

  • Built and trained a deep learning model using TensorFlow to classify text sentiment as positive, negative, or neutral.

  • Integrated the model with a Flask API, with a React frontend for user interaction and result visualization.

  • Deployed the application on AWS, utilizing EC2 and S3 for scalable infrastructure.

Intelligent SQL Query Generator and Database Analysis Assistant

  • Developed an AI-powered SQL agent that generates complex database queries from natural language descriptions

  • Built comprehensive database analysis tools with automated report generation and data visualization

  • Implemented SQL query optimization and validation with error handling and performance analysis

  • Created interactive frontend for database exploration, query execution, and result interpretation

  • Integrated with SQLite databases for sample data analysis and business intelligence reporting