Developed an AI-powered financial assistant using Claude Sonnet 4 via AWS Bedrock with a RAG-based agentic backend for personalized employee benefits guidance. Built a hybrid AWS stack with Lambda, API Gateway, S3, RDS (MySQL), and EC2, implementing secure CRUD operations, prompt engineering, and real-time retrieval optimization.

Engineered an AI-enhanced analytics and visualization platform that automates data tracking, insights generation, and performance optimization. Built a React + TypeScript frontend with Tailwind CSS, Recharts, and react-query, and a modular analytics engine designed for scalability with MongoDB and AWS/GCP integration.

Built a career exploration app using Kotlin and MongoDB to deliver personalized, data-driven career advising features. Collaborated with users through beta testing, improving UX and usability; received Special Recognition for Innovation at the Congressional App Challenge.

Developed a modular robotics software library with intuitive interfaces and optimized control algorithms. Collaborated with team engineers to translate system requirements into scalable technical solutions and created maintainable documentation for long-term usability.

Built a face recognition model on the LFW Deep Funneled dataset using PCA and Support Vector Machines with linear, RBF, and polynomial kernels; achieved highest accuracy with RBF on facial feature classification.