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  <title><![CDATA[PhD Defense by Grace Guo]]></title>
  <body><![CDATA[<p><strong>Title:</strong>&nbsp;Augmenting Visualizations with Statistical and User-defined Data Facts</p><p>&nbsp;</p><p><strong>Date:</strong>&nbsp;Friday, June 28, 2024</p><p>&nbsp;</p><p><strong>Time:</strong>&nbsp;7.30 - 9.30AM EST</p><p>&nbsp;</p><p><strong>Location (In person):</strong>&nbsp;TSRB 334 Lab</p><p>&nbsp;</p><p><strong>Location (Virtual):</strong>&nbsp;<a href="https://gatech.zoom.us/j/97764163553">https://gatech.zoom.us/j/97764163553</a></p><p>&nbsp;</p><p><strong>Grace Guo</strong></p><p>PhD Candidate in Human-centered Computing</p><p>School of Interactive Computing</p><p>Georgia Institute of Technology</p><p>&nbsp;</p><p><strong>Committee:</strong></p><p>Dr. Alex Endert (Advisor), School of Interactive Computing, Georgia Institute of Technology</p><p>Dr. John Stasko, School of Interactive Computing, Georgia Institute of Technology</p><p>Dr. Clio Andris, School of Interactive Computing, Georgia Institute of Technology</p><p>Dr. Jessica Roberts, School of Interactive Computing, Georgia Institute of Technology</p><p>Dr. Bum Chul Kwon, MIT-IBM Watson AI Lab, IBM Research</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Abstract:</strong></p><p>When designing visualizations and visualization systems, we often augment charts and graphs with visual elements in order to convey richer and more nuanced information about relationships in the data. However, we do not yet fully understand user considerations when creating these augmentations, nor do we have toolkits to support augmentation authoring.</p><p>&nbsp;</p><p>I my thesis, I first outline a design space of user-created augmentations, then introduce Auteur, a front-end JavaScript toolkit designed to help developers add augmentations to web-based D3 visualizations and systems to convey statistical and custom data relationships. The library is then customized and extended for the domains of online learning and causal inference, where users may be interested in domain-specific data relationships or work with unique chart types and data sets. Collectively, these contributions aim to help us better incorporate user-defined augmentations into visualizations for analysis and storytelling, thus conveying human context, user preferences, and domain knowledge through our charts and graphs.</p>]]></body>
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