Chandan K S

I worked as a Cloud Engineer Intern on a GCP-powered E-Healthcare Monitoring System, helping develop and deploy it with Compute Engine, Cloud SQL, App Engine, and Firebase. I configured virtual machines, cloud storage, databases, and APIs so text and real-time data could integrate smoothly.

I’ve also built projects like an end-to-end Multimodal-RAG system with Streamlit, FastAPI, and Docker to extract insights from text and audio using embedding models, rerankers, and LLMs. On the data side, I designed scalable pipelines and a microservices-style architecture to keep processing and response relevance efficient.

For applied ML, I built a Collision-and-Hazard-Analysis pipeline using YOLOv8, OpenCV, and PyTorch—covering dataset conversion, fine-tuning, and real-time driver warning logic with Time-to-Collision (TTC) estimation.