Bapuray Patil

I’m a Computer Science student specializing in Artificial Intelligence and Machine Learning, driven by the goal of solving real-world problems with practical AI systems. I’ve built and tested solutions in NLP, Deep Learning, and LLM-based workflows—always with a focus on improving usability and measurable performance.

Through my AI/ML Research Internship at DRDO (CEMILAC), I built an Aircraft Defect Analysis System to help aerospace engineers search and analyze maintenance and defect documents. I implemented NLP techniques to extract, process, and organize information from technical manuals and records, improving document accessibility and supporting faster decision-making. I also built a solution with 80%+ query relevance.

In a Microsoft-focused internship with Edunet Foundation (AICTE), I completed an intensive program covering Artificial Intelligence, Generative AI, and Computer Vision. This experience strengthened my ability to develop end-to-end AI pipelines and work effectively with modern AI tooling and evaluation practices.

My projects reflect the same applied mindset. I developed a CNN-based Deepfake Detection system using Python, TensorFlow, and OpenCV; built an AI-Based UPSC Answer Evaluation System using LLMs and RAG; and created a Machine Learning-Based Disease Prediction System with Scikit-learn and Pandas, deployed via Streamlit.