{"678196":{"#nid":"678196","#data":{"type":"event","title":"PhD Defense by Arpit Narechania","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Designing, Developing, and Democratizing Guidance for Visual Analytics\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDate:\u003C\/strong\u003E\u0026nbsp;Tuesday, November 19, 2024\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E\u0026nbsp;8\u201310 AM Eastern Time (US)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp; \u003Ca href=\u0022https:\/\/maps.app.goo.gl\/i8yusVJT3cryf5yC7\u0022\u003ETSRB\u003C\/a\u003E 334 (VIS Lab) \u2013 just walk in, show your BuzzCard to the concierge if asked\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EVirtual Meeting:\u003C\/strong\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/91780204382?pwd=3lYHR26srieKkeYRDS52buYkvu2euz.1\u0022\u003EZoom\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EArpit Narechania\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/arpitnarechania.github.io\u0022\u003Ehttps:\/\/arpitnarechania.github.io\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EComputer Science PhD Student\u003C\/p\u003E\u003Cp\u003ESchool of Interactive Computing\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Alex Endert \u2013 Advisor, Georgia Tech, School of Interactive Computing\u003C\/p\u003E\u003Cp\u003EDr. John Stasko \u2013 Georgia Tech, School of Interactive Computing\u003C\/p\u003E\u003Cp\u003EDr. Duen Horng (Polo) Chau\u0026nbsp;\u2013 Georgia Tech, School of Computational Science \u0026amp; Engineering\u003C\/p\u003E\u003Cp\u003EDr. Clio Andris \u2013 Georgia Tech, School of City and Regional Planning\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Shamkant B. Navathe \u2013 Georgia Tech, School of Computer Science\u003C\/p\u003E\u003Cp\u003EDr. Mennatallah El-Assady \u2013 ETH Z\u00fcrich, ETH AI Center\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe ubiquity and utility of data today underscore the importance of balancing system efficiency with human intuition and expertise to ensure timely and accurate decision-making. Yet, challenges arise when users must extensively input their analytic intent or when automated system actions misinterpret their needs. \u201cGuidance\u201d \u2013 or any kind of help, tip, advice, support, suggestion, or recommendation \u2013 offers a promising solution to bridge this \u201cknowledge gap\u201d between the two, enhancing both the quality of analysis and making the process more enjoyable for users. This thesis extends information visualization (InfoVis), visual analytics (VA) and human-computer interaction (HCI) literature by contributing a series of mixed-initiative guidance-enriched tools and techniques, wherein the user and the system both learn from and take initiative on behalf of each other to steer the analysis process. We categorize these contributions under three main thrusts:\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003E(1) Investigate the Role of Guidance in Visual Analytics:\u003C\/em\u003E We introduce a data preparation system (\u003Ca href=\u0022https:\/\/dl.acm.org\/doi\/10.1145\/3544548.3581509\u0022\u003E\u003Cstrong\u003EDataPilot\u003C\/strong\u003E\u003C\/a\u003E) that utilizes data quality and usage insights to guide users in selecting effective subsets from large, unfamiliar tabular datasets. Bringing the human into the (analysis) loop, we introduce a question-answering system integrated with a self-service debugging view (\u003Ca href=\u0022https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3397481.3450667\u0022\u003E\u003Cstrong\u003EDIY \u2013 Debug-It-Yourself\u003C\/strong\u003E\u003C\/a\u003E), that helps users interactively assess the correctness of natural language to SQL workflows.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003E(2) Develop Mixed-Initiative Guidance Systems.\u003C\/em\u003E We introduce a visual data analysis system (\u003Ca href=\u0022https:\/\/lumos-vis.github.io\/\u0022\u003E\u003Cstrong\u003ELumos\u003C\/strong\u003E\u003C\/a\u003E) that increases users\u2019 awareness of (biased) analytic behaviors by comparing it against a target behavior;\u0026nbsp; users can adjust this target behavior, achieving co-adaptivity. We enhance Lumos into a multimodal data analysis system (\u003Ca href=\u0022https:\/\/lumos-vis.github.io\/\u0022\u003E\u003Cstrong\u003EBiasBuzz\u003C\/strong\u003E\u003C\/a\u003E) that additionally provides haptic feedback to quickly draw users\u2019 attention in case of significantly biased behaviors. As a culmination system,\u0026nbsp; we introduce the first mixed-initiative visual data analysis system that can seamlessly transition between different levels of guidance based on the analysis needs and user preferences (\u003Cstrong\u003ELighthouse\u003C\/strong\u003E).\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003E(3) Democratize Building Custom Guidance Systems.\u003C\/em\u003E We contribute an open-source library of enhanced user interface (UI) controls that track and dynamically overlay analytic provenance, enabling developers to prototype custom guidance-enriched systems (\u003Ca href=\u0022https:\/\/provenancewidgets.github.io\/\u0022\u003E\u003Cstrong\u003EProvenanceWidgets\u003C\/strong\u003E\u003C\/a\u003E). To ensure consistent and effective user interfaces for visual data analysis, we also derive two design spaces: one for communicating analytic provenance (\u003Cstrong\u003EProvenanceLens\u003C\/strong\u003E) and another for communicating guidance (\u003Cstrong\u003ELighthouse\u003C\/strong\u003E).\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe outcomes of this thesis have been disseminated through multiple publications in top journals and conferences (TVCG, VIS, CHI, IUI), multiple patent filings by Adobe and Microsoft, integration into an Adobe product, open-source software, and inclusion in coursework on visualization and human-centered data analysis at Georgia Tech, achieving broader impact for researchers, developers, practitioners, and students alike.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDesigning, Developing, and Democratizing Guidance for Visual Analytics\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Designing, Developing, and Democratizing Guidance for Visual Analytics"}],"uid":"27707","created_gmt":"2024-11-05 21:19:55","changed_gmt":"2024-11-05 21:20:42","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-11-19T08:00:00-05:00","event_time_end":"2024-11-19T10:00:01-05:00","event_time_end_last":"2024-11-19T10:00:01-05:00","gmt_time_start":"2024-11-19 13:00:00","gmt_time_end":"2024-11-19 15:00:01","gmt_time_end_last":"2024-11-19 15:00:01","rrule":null,"timezone":"America\/New_York"},"location":"TSRB 334 (VIS Lab) ","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"177814","name":"Postdoc"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}