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

Home

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