Developed Foodie-AI, an ML-powered application for preventative medicine that analyzes dietary and health data to deliver personalized recommendations using SQL, NoSQL (MongoDB), and vector databases for efficient semantic search and retrieval-augmented generation.
Integrated LiDAR, MediaPipe, and Three.js systems to resolve landmark scan inaccuracies, enabling precise 3D body modeling, improved pose estimation, and reliable anatomical landmark detection for accurate health metrics.
Built scalable stream data pipelines to process unstructured datasets for ML-driven applications helping process TB of data.
Implemented autoscaling, monitored with AWS CloudWatch, and collaborated on container security, for the purpose of scalable, and reliable systems