gautami Patnaik

I’m a final-year ECE student with a strong interest in AI and computer vision, currently pushing my work into real healthcare impact. I’m interning at Cruvix AI Research, where I build healthcare AI systems and co-write an IEEE conference paper, and I genuinely enjoy learning fast and shipping reliable solutions.

In my current role, I built a contactless vitals detection system that measures heart rate, SpO2, HRV, stress index, and breathing rate from a live camera feed using the CHROM signal processing algorithm. I also developed end-to-end product surfaces—building the complete React Native healthcare mobile app frontend and creating admin/superadmin dashboards with React, TypeScript, and Django REST with live API integration for AI model monitoring and real-time vitals display. Along the way, I evaluated a YOLO-based robotics object detection model across 83 images, documented accuracy metrics, and achieved a 96% detection rate.

My projects reflect how I like to work across the stack: I built a full-stack AI SaaS for PDF Q&A using RAG architecture with FastAPI, LangChain, Groq LLaMA3, and FAISS, delivering real-time document chat with sub-second response times. I also constructed a contact-free heart rate & stress detection pipeline (rPPG) from scratch—using MediaPipe ROI extraction, CHROM, filtering/normalization, and peak detection—and fixed a BPM accuracy bug by correcting frame-rate assumptions. Beyond AI, I’ve built IoT/embedded solutions like adaptive smart water heater optimization and an alcohol detection system for vehicles, because I like turning ideas into working systems.