Engineered and deployed an AI-powered mental health peer support platform at MHacks2024 Hackathon, utilizing MongoDB for scalable data storage, Streamlit for an interactive userinterface, and NLP techniques combined with K-Means clustering to match users based ontheir worries and emotional states; seamlessly integrated Magic Loops API for automatedmeeting scheduling, providing real-time peer support with empathetic, data-driven matching

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Developed a stock hedging platform using linear regression, statistical analysis, and historical market data to forecast systematic risk, integrating machine learning models and real-time data scraping tools, enhancing risk management and achieving a 356.46% portfolio increase

Stock Hedging Platform

Developed a full stack AI SaaS platform using Next.js, MongoDB, Stripe, and Cloudinary forimage transformations, with secure route protection, serverless functions optimized by cache-based webhooks, and user authentication to enhance efficiency and streamline operations