Abstract
A VR network visualization system using voice commands and LLM-powered agents to transform natural language into Neo4j queries, enabling interactive graph exploration through categorical coloring, shape encoding, and dynamic layouts.
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This is an ongoing project with one lead PhD and two main developers. I designed and implemented the multi-agent LangGraph pipeline that transforms voice input into visualization operations, including speech error correction and ambiguity detection. Also, I am responsible for the categorical encoding system for bivariate visualization (color and shape by attribute) with automatic mapping and legend generation. I also created the end-to-end execution flow integrating Whisper STT, LangGraph, Neo4j, and Unity rendering.