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vidyashreerayar/README.md

Vidyashree Rayar

AI Engineer • LLM Systems • Production-Ready RAG


Email LinkedIn Portfolio

🎯 Here's What I Do

I build production AI systems that bridge symbolic reasoning (Knowledge Graphs, SPARQL) with neural networks (LLMs, RAG). Currently finishing my Master's thesis on LLM-driven industrial control systems at BTU Cottbus.

Core stack: Python • AI Agents • LangChain • RAG • HuggingFace • LLMs • PowerBI

🚀 My Recent Work

Project What It Does Stack
PDF-RAG Pipeline Enterprise doc Q&A with semantic search LangChain, ChromaDB, Gemini
NL-to-SPARQL Agent Converts natural language to SPARQL queries over Wikidata Python, SPARQL, Wikidata
Tourist AI Agent Tool-using LLM agent with real-time data smolagents, HuggingFace, Gradio

🔬 Currently working on my Master's thesis: LLM-based adaptive control for industrial fluid systems — read more on my portfolio.

🤝 Let's Build Together

Dear Recruiters: I'm open to AI/ML Engineer roles in Germany. Dear Collaborators: Interested in RAG systems, industrial AI, or Knowledge Graph applications?

📧 vidya.rayar@gmail.com — Let's talk.

🎓 MSc AI @ BTU Cottbus • 💼 Ex-Wipro • 🌍 Based in Germany

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  1. pdf-rag-langchain-gemini pdf-rag-langchain-gemini Public

    End-to-end PDF-based Retrieval-Augmented Generation (RAG) system built with LangChain, Google Gemini embeddings, and Chroma vector database. Enables semantic search and question-answering over cust…

    Jupyter Notebook

  2. Enhancing-FER-using-CBAM-Attention Enhancing-FER-using-CBAM-Attention Public

    Enhanced facial expression recognition using CBAM attention to improve accuracy and feature focus in deep learning models.

    Jupyter Notebook 1

  3. nl-to-sparql-wikidata nl-to-sparql-wikidata Public

    Demo prototype that converts natural language questions into SPARQL queries and retrieves answers from Wikidata.

    Python 1

  4. Data-Analytics-in-Netflix-Viewership-Trends-Pandas-Plotly Data-Analytics-in-Netflix-Viewership-Trends-Pandas-Plotly Public

    Analyzed Netflix viewership trends by content type, language, and season using Pandas & Plotly.

    Python 1