Visualization Tool
Visualization tools are rapidly evolving to address the challenges of interpreting complex data across diverse scientific domains. Current research emphasizes interactive, scalable tools leveraging techniques like UMAP for dimensionality reduction, LLMs for automated data processing and visualization generation, and AI-powered systems for iterative refinement based on user feedback. These advancements are significantly improving data exploration and analysis, facilitating deeper insights in fields ranging from machine learning model interpretation to drug safety research and human-swarm interaction studies.
Papers
SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks
Zijie J. Wang, David Munechika, Seongmin Lee, Duen Horng Chau
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion
Seongmin Lee, Benjamin Hoover, Hendrik Strobelt, Zijie J. Wang, ShengYun Peng, Austin Wright, Kevin Li, Haekyu Park, Haoyang Yang, Duen Horng Chau