SID User

I’m a computer science undergrad building AI applications with LLMs, RAG pipelines, and full-stack GenAI systems. I’m hands-on with LangChain, ChromaDB, HuggingFace Embeddings, and the Gemini API to turn data into grounded, usable outputs.

As a Data Science Intern at Unied Mentor, I built and evaluated ML models across healthcare, sales, and business datasets. I handled end-to-end data pipelines—cleaning, EDA, feature engineering, and predictive modeling—and delivered 6 independent project reports with visualizations using Matplotlib and Seaborn.

In my “RAG System v2” project, I developed a conversational document intelligence system with a Retrieval-Augmented Generation (RAG) pipeline using LangChain, ChromaDB, HuggingFace Embeddings, and Gemini. I implemented multi-format document ingestion and semantic retrieval across PDF, DOCX, CSV, and TXT, plus query rewriting and grounded response generation.

I also build practical, deployable systems: an AI Diagram Generator that converts natural language to Mermaid diagrams using Google Gemini, and a Lung CT Risk Estimation system using a custom CNN (achieving ~0.92 AUC) behind a Flask web application. I’m seeking GenAI engineering internships to contribute to reliable end-to-end GenAI product work.