Dhwanil Chauhan

I am a Master of Science candidate in Computer Science at Purdue University specializing in machine learning, generative AI, and full-stack system development. I build production-oriented ML solutions that integrate local LLMs, RAG, and real-time computer vision to improve safety and decision-making.

At Purdue's Center of Innovation through Visualization and Simulation I designed an LLM-powered incident reporting chatbot that extracts structured data from free-text narratives and an AI Hazard Recognition System using YOLOv8 and contextual zone logic to detect safety violations in steel manufacturing.

I have internship experience as an AI Venture Analyst where I created conversational founder intake workflows that use local models and rubric-based scoring to automate screening, and I lead personal projects in flood scenario modeling, lip-reading, and health diagnostics using a mix of ML, DL, and graph methods.

I publish in AI, ML, deep learning, and cybersecurity and enjoy turning research into deployed systems—building modular FastAPI+React platforms, optimizing prompts and pipelines, and improving operational metrics like accuracy and screening time.