The task of data visualization generally involves a design step, which requires the knowledge of the data domain and visualization methods to do well. Because of the immense design space for optimization, it can take both novices and experts substantial effort to derive desired visualization results from data for exploration or communication. Following the resurgence of artificial intelligence (AI) technology in recent years, in the field of visualization, there is a growing interest and opportunity in applying AI to perform data transformation and to assist the generation of visualization, aiming to strike a balance between cost and quality. The use of visualization to enhance AI is the other active line of research. This workshop, held in conjunction with IEEE PacificVis 2024, aims at exploring this emerging area of research and practice by fostering communication between visualization researchers and practitioners. Attendees will be introduced to the latest and greatest research innovations in AI-enhanced visualization (AI4VIS) as well as visualization-enhanced AI (VIS4AI), and also learn about further research opportunities. The workshop will be composed of full-paper presentations, short-paper presentations, and invited talks.
We welcome contributions as full papers and short papers. All accepted papers will appear in the proceedings of the IEEE PacificVis 2024 and the IEEE Xplore Digital Library.
Papers should follow the formatting guidelines for VGTC Conference Style Papers. There is no strict page limit, but authors are encouraged to submit a paper whose length matches its contribution. Our recommendation for the paper length is as follows:
- Full paper: up to 10 pages (including reference)
- Short paper: up to 6 pages (including reference)
Both full papers and short papers are to be submitted using PCS (Track Name: PacificVis 2024 Visualization Meets AI Workshop). We will accept both single-blind (not anonymized) as well as double-blind (anonymized) submissions. In the case of double-blind submissions, please substitute the author names with the paper ID number.
- Paper due: December 29, 2023 January 5, 2024
- 1st cycle notification: February 2, 2024
- Revision due: February 16, 2024
- 2nd cycle notification: February 26, 2024
- Camera ready paper due: March 4, 2024
- Workshop: April 23, 2024
All deadlines are due at 11:59pm (23:59) Anywhere on Earth (AoE).
We encourage submissions of high quality research and application papers incorporating visualization and AI/machine lerning. Our interest includes both topics of AI4VIS and VIS4AI.
Example papers:
Takanori Fujiwara, Linköping University
Junpeng Wang, Visa Research
Angelos Chatzimparmpas, Northwestern University
Dylan Cashman, Brandeis University
Steffen Frey, University of Groningen
Hanqi Guo, the Ohio State University
Jun Han, the Chinese University of Hong Kong
Wenbin He, Bosch Research
Oh-Hyun Kwon, Apple
Mengchen Liu, Microsoft Research
Shusen Liu, Lawrence Livermore National Laboratory
Huan Song, Amazon AWS AI
Jun Tao, Sun Yat-sen University
Qianwen Wang, University of Minnesota
Yong Wang, Singapore Management University
John Wenskovitch, Pacific Northwest National Laboratory
Jiazhi Xia, Central South University
Jun Yuan, Apple
pvis_ai4vis@pvis.org