The project involves developing a cross-platform mobile application to help users manage and track their contacts, social media accounts, and personal preferences. The app enables users to maintain detailed profiles, adjust privacy settings, send private messages, and receive notifications.
Users can also add custom contact details, follow or unfollow others, and manage their interests through a two-level categorization system. The application will be deployed on both iOS and Android platforms.

Mobile first wellness and trading support application designed to help users achieve emotional balance, track physiological health, and correlate their mental state with trading performance. By blending biometric insights, mindfulness, and trading analytics, the app empowers users to make more rational and confident trading decisions. 
 

This project delivers an integrated AI and analytics platform for the Foundation for Sickle Cell Disease Research (FSCDR). It connects ECW (eClinicalWorks) EHR data with advanced AI-based predictive models to identify high-risk patients, automate follow-ups, and streamline state grant reporting (CMO99, CMOAE Tasks 5–13).
The goal is to transform static EHR data into actionable insights — improving research visibility, compliance, and patient outcomes while cutting down manual reporting workloads. The solution supports predictive ER-risk modeling, AI-based outreach automation, and Power BI-driven compliance dashboards across FSCDR’s Centers of Excellence.