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

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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

AI Powered Mental Health Peer Platform

(Pytorch, Flask, NumPy, Pandas, Python, HTML, CSS) Developed a machine learning-based movie recommendation system using Matrix Factorization in PyTorch, enabling personalized movie suggestions based on user ratings.Created a web application with Flask to handle user interactions, allowing users to log in, add ratings, and receive real-time movie recommendations, while leveraging TMDB API for fetching movie details.                                                                         