Adobe Research at VIS 2021

October 25, 2021

Tags: Conferences, Data Intelligence

In this VIS 2021 paper, the authors propose a new pipeline for a responsive visualization recommender.

IEEE VIS is the premier forum for the discussion of advances in theory, methods, and applications of visualization and visual analytics. The conference is being held virtually from Oct 24 to 29, 2021.  

There are seven Adobe co-authored papers at IEEE VIS this year, including six technical papers and one workshop paper. Two technical papers received best paper honorable mentions. 

Nearly all of Adobe’s papers are the result of student internships or other collaborations with university students and faculty from Northwestern University, University of Maryland, University of Washington, Massachusetts Institute of Technology, and others. For those interested, please check out the Adobe Research Careers website to learn more about internships and full-time career opportunities

Technical Papers 

An Automated Approach to Reasoning About Task-Oriented Visualization Insights in Responsive Visualization 
Hyeok Kim, Ryan Rossi, Abhraneel Sarma, Dominik Moritz, Jessica Hullman
An Evaluation-Focused Framework for Visualization Recommendation Algorithms 
Best Paper Honorable Mention 
Zehua Zeng, Phoebe Moh, Fan Du, Jane Hoffswell, Tak Yeon Lee, Sana Malik, Eunyee Koh, Leilani Battle 

InfoColorizer: Interactive Recommendation of Color Palettes for Infographics 
Lin-Ping Yuan, Ziqi Zhou, Jian Zhao, Yiqiu Guo, Fan Du, Huamin Qu
VBridge: Connecting the Dots Between Features, Explanations, and Data for Healthcare Models 
Best Paper Honorable Mention 
Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni
Visual Arrangements of Bar Charts Influence Comparisons in Viewer Takeaways 
Cindy Xiong, Vidya Setlur, Benjamin Bach, Kylie Lin, Eunyee Koh, Steven Franconeri
A Design Space for Applying the Freytag’s Pyramid Structure to Data Stories 
Leni Yang, Xian XU, Xingyu Lan, Ziyan Liu, Shunan Guo, Yang Shi, Huamin Qu, Nan Cao 

Workshop Paper 

Aunt Lily Can Say Her Visualizations:  Directing Analysis, Design, and Storytelling in Natural Language 
Zening Qu, Fan Du, Ryan Rossi, Bill Howe 
Presented at NL VIZ: Workshop on Exploring Opportunities and Challenges for Natural Language Techniques to Support Visual Analysis 

Related Posts