Biotechnology student at NIT Rourkela building machine learning and full-stack systems — at the intersection of biotech, computer vision, and applied AI.
Previously an AI/ML Intern @ Glowvista Instruments, where I trained a YOLO model to classify infected cells for a point-of-care malaria/dengue screening device, and built a real-time fluorescence visualization tool integrated into a Raspberry Pi UI.
| Project | What it does |
|---|---|
| energy-market-analytics | Institutional-grade platform for collecting, modeling, and forecasting crude oil & refined product prices with quantitative stress-testing |
| enterprise-ai-copilot | AI analytics copilot — ask business questions in natural language over your data and get insights, dashboards, and predictions |
| Plant_disease_detection | Two-stage crop→disease classifier with a vision-LLM + RAG fallback for out-of-distribution photos, served via FastAPI |
| Food_Ai_vision | Vision Transformer detecting food spoilage and AI-generated food images, deployed as separate frontend/backend/nginx services |
| cv-project | Real-time hand gesture recognition — gesture-based volume control, ASL detection, and an AR "portal" effect |
| expense-tracker | FastMCP-based expense tracking MCP server backed by SQLite |
Python PyTorch FastAPI React TypeScript SQL OpenCV YOLO Docker LangGraph / RAG