(AI4SciSci Workshop 2026) (Artificial Intelligence for Science of Science)
Over the past decade, the field of artificial intelligence (AI) has witnessed significant advancements across various domains, such as natural language processing and computer vision, which have further accelerated discoveries, innovations, and breakthroughs in many interdisciplinary fields — including Science of Science, which relies on big data to uncover reproducible patterns governing the evolution of research topics, collaboration networks, knowledge diffusion, and the systemic factors that drive scientific progress. Today, Science of Science is incorporating AI techniques into the analysis of big data, yielding deep and compelling insights into both longstanding and emerging problems in the field. Building on the success of the first and second AI4SciSci workshops, held in conjunction with ICDM’23 and JCDL’25, respectively, we propose the Third International Workshop on Artificial Intelligence for the Science of Science (AI4SciSci) to further engage the AI and Science of Science communities in promoting research and discussion on frontier topics in this area.
We welcome papers on topics of interest that include, but are not limited to, the following.
One unique feature of our workshop is that we will accept both original and published submissions. Authors of published works will need to submit an extended abstract (up to 2 pages) that explicitly cites the published work. In addition to summarizing the published work, the extended abstracts may also contain incremental updates or new results of the published work.
Ai4SciSci adopts the same double-blind review policy as JCDL. Submissions must not include any information that could identify the authors, such as names, institutional affiliations, acknowledgments, or references to prior work written in the first person. Authors should refer to their own prior work in the third person (e.g., “Prior work by Smith et al. (2020)” rather than “In our previous work…”). If authors share supplementary materials (e.g., code, data, models), these must be anonymized to avoid revealing author identities. Authors are encouraged to use anonymous hosting platforms such as anonymous.4open.science.
All submissions must be written in English, following the CEUR workshop proceedings style.
Paper submission link: EasyChair
** References and appendices are not counted towards the page limits.
All accepted papers that report original work will be published at the CEUR proceedings.
(Co-Chair)
Associate Professor
Old Dominion University, USA
jwu@cs.odu.edu +1 (757)-683-7753
(Co-Chair)
Associate Professor
The Pennsylvania State University, USA
smr48@psu.edu +1 (814)-863-2554
(Co-Chair)
Assistant Professor
The College of William & Mary, USA
yihe@wm.edu +1 (757)-683-7821