retreats:2023fall:abstracts
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retreats:2023fall:abstracts [2023/10/04 11:48] kilov |
retreats:2023fall:abstracts [2023/10/11 22:50] (current) peziegler Changing my talk title and abstract |
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| =====Talk Abstracts: | =====Talk Abstracts: | ||
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| + | ====Keynote==== | ||
| + | * Leveling up journalism with data science, Cheryl Phillips, Stanford | ||
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| + | Abstract: | ||
| + | Machine-learning that identifies influence in The Supreme Court, building programs to identify problem doctors who are still practicing, building new methods to discover the patterns in police use of force cases. In this talk, Cheryl Phillips walks through some of ways journalism with impact is built on sophisticated data science and lays out the hardest technical challenges accountability and investigative journalists face now, including how to use generative AI in a way that produces reliable results, doesn’t break the bank and results in news stories with impact. | ||
| ====Session I==== | ====Session I==== | ||
| - | * Supporting Data Journalists through | + | * Automated Reverse Engineering of Data Visualizations from In-the-Wild Examples, //Parker Ziegler// |
| Abstract: | Abstract: | ||
| - | Examples are foundational in helping data journalists author interactive graphics, whether by demonstrating challenging techniques or serving as building blocks for new design exploration. However, a key element of an example’s usefulness is the availability of its source code. If a data journalist wants to work from an “in-the-wild” example for which no source code is available, they have to resort to manual reverse engineering to produce an approximation of the original visualization. This is a time-consuming and error-prone process, erasing much of the original benefit of working from an example. In this talk, I’ll present our work on reviz, a compiler and accompanying Chrome extension that automatically generates parameterized data visualization programs from input SVG subtrees. I’ll walk through the reviz architecture from an end user’s perspective before diving deep into the internals of our reverse engineering and compilation processes. I’ll finish by discussing reviz' | + | Examples are foundational in helping data journalists author interactive graphics, whether by demonstrating challenging techniques or serving as building blocks for new design exploration. However, a key element of an example’s usefulness is the availability of its source code. If a data journalist wants to work from an “in-the-wild” example for which no source code is available, they have to resort to manual reverse engineering to produce an approximation of the original visualization. This is a time-consuming and error-prone process, erasing much of the original benefit of working from an example. In this talk, I’ll present our work on reviz, a compiler and accompanying Chrome extension that automatically generates parameterized data visualization programs from input SVG subtrees. I’ll walk through the reviz architecture from an end user’s perspective before diving deep into the internals of our reverse engineering and compilation processes. |
| * ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data, //Liana Patel// | * ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data, //Liana Patel// | ||
retreats/2023fall/abstracts.1696445336.txt.gz · Last modified: 2023/10/04 11:48 by kilov
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