Focused on building reliable, scalable applications that solve real problems. I'm passionate about full-stack development, crafting intuitive user interfaces, and leveraging AI/ML to create smarter systems. With experience across modern web technologies, cloud platforms, and machine learning frameworks, I love turning complex ideas into simple, elegant solutions that make a meaningful impact.
June 2025 – September 2025
Remote, USA
Delivered a Deal Engine reporting module with React and AWS, enabling 5000 clients to create customized reports and improving analysis speed by 25%
Built scalable microservices using Python FastAPI and PostgreSQL on AWS EC2 with Docker, ensuring data consistency and persistent report formatting across sessions
Developed retrieval-augmented financial pipelines with SageMaker and Lambda, integrating EDGAR filings into FAISS and Qdrant for faster insights delivery
Orchestrated multi-agent LLM frameworks with GPT, Claude, and Sonnet, automating financial data enrichment and cutting insight generation time by 25%
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August 2023 - May 2025
Tempe, AZ, USA
GPA: 4.0/4.0
A showcase of some of my recent work, featuring full-stack applications, AI integrations, and scalable cloud solutions.
A scalable cloud-based face recognition system for student attendance. Built with microservices architecture using AWS services including S3, Lambda, SQS, and EC2 for automatic scaling. Features Spring Boot API, Python face recognition workers with FaceNet, and real-time processing pipeline.
A comprehensive graph data processing pipeline for NYC taxi trip analysis. Implements Neo4j graph database with PageRank and BFS algorithms on large-scale transportation data. Features Docker containerization, Minikube orchestration, real-time data ingestion, and interactive graph visualizations.
A comprehensive coding platform with distributed architecture featuring Java Spring Boot backend, Next.js TypeScript frontend, and microservices worker system. Deployed on AWS EC2 with RDS database, supports multiple programming languages, real-time code execution, automated testing with SQS message queuing, and S3 integration.
Advanced machine learning system for crime prediction in Tempe, Arizona using spatial-temporal analysis. Implements Gradient Boosting, feature engineering with 7x7 spatial grids, and interactive visualization with choropleth maps. Achieves high accuracy with comprehensive model evaluation metrics.
Intelligent retrieval-augmented generation system for academic paper analysis. Features PDF scraping, multi-modal content processing with CLIP embeddings, FAISS vector storage, and LLM integration. Supports text and image vectorization with Django web interface for seamless research assistance.
A comprehensive data science project for analyzing Instagram content performance and optimizing posting strategies. Features automated data extraction (Selenium, Instaloader), advanced analytics (engagement, content type, temporal trends), and an interactive Streamlit dashboard for real-time insights. Includes robust error handling, secure authentication, and professional visualizations. Case study: Cristiano Ronaldo's profile.
Driven to turn complex ideas into impactful, intelligent software solutions. Specializes in building scalable systems, integrating AI for smarter user experiences, and delivering products with reliability and precision. Focused on creating technology that not only works efficiently but also inspires trust and innovation in every interaction.