Co-located with ACM/IEEE-CS JCDL 2025

The 2nd International Workshop on Artificial Intelligence for the Science of Science AI4SciSci Workshop 2025

(AI4SciSci Workshop 2025) (Artificial Intelligence for Science of Science)

Workshop Date: TBD On: TBD

Key Dates

About the 2nd Workshop on AI4SciSci About AI4SciSci

Over the past years, the field of artificial intelligence (AI) has witnessed significant advancements in various fields, which have further accelerated discoveries, innovations, and breakthroughs in many interdisciplinary fields, including the Science of Science, which relies on big data to unveil the reproducible patterns that govern individual scientific careers and the workings of science. Recently, the Science of Science has made promising progress by adopting AI techniques into big data, providing deep and interesting insights into new and long-standing Science of Science problems. Here, we present the second International Workshop on Artificial Intelligence for the Science of Science (AI4SciSci) to engage the AI and Science of Science communities in further promoting research and discussion on frontier topics in this field.

Call for Papers

This workshop is aimed at bringing together researchers from the areas of data mining (DM), artificial intelligence (AI), and Science of Science (SciSci). We expect to encourage an exchange of ideas and perceptions through the workshop, focusing on novel research directions, challenges, and techniques in the intersectional areas of AI and DM for SciSci. We welcome papers on topics of interest that include, but are not limited to:

  1. Scholarly Graph Analytics
    • Citation networks and their applications
    • Social networks and their applications
    • Knowledge graphs and their applications
  2. Scholarly Data Mining
    • Innovation/novelty detection and prediction
    • Scholarly collaboration and mobility prediction
    • Career trajectory modeling
    • Numerical modeling of scientific development
    • Causal inference and reasoning for SciSci
    • Streaming data mining and applications for SciSci
  3. Scientific Document Processing and Understanding
    • Scientific document parsing and applications
    • Scientific metadata extraction and applications
    • Scientific claim extraction and verification
    • Scientific tabular data structure recognition and understanding
    • Scientific figure/chart extraction and understanding
    • Scientific document summarization and topic modeling
  4. Computational Social Sciences
    • Scientific reproducibility, replicability, repeatability, and generalizability
    • Innovation automation with AI
    • Scientific goods for AI and ethical implications
    • Socio-economic effects on scientific progress and innovation
    • Scientific misinformation and disinformation
    • Scientific impact quantification using metrics outside of academia (e.g., patents, technology transfer to industry and revenue)

Originality

Submissions must report original work that has not been previously published and is not under concurrent review elsewhere.

Double-Blind Review and Anonymity Guidelines

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.

Submissions

All submissions must be written in English, following the CEUR workshop proceedings style.

Paper submission link: EasyChair

Submission Length
  • Extended Abstracts (up to 2 pages)
  • Short Papers (up to 4 pages)
  • Full Papers (up to 8 pages)

** References and appendices are not counted towards the page limits.

All the accepted papers will be published to the CEUR-WS repository at https://ceur-ws.org/.

Important Dates

  • Call for Papers: Friday, October 03rd, 2025
  • Paper Submission Deadline: Friday, October 24th, 2025
  • Author Notification: Friday, November 14th, 2025
  • Camera-Ready Deadline: Friday, November 28th, 2025
  • Registration: Link
  • Workshop date: TBD

Program

— TBD —

Keynote Speaker

Dr. Daniel Acuña
Associate Professor
University of Colorado Boulder
Dr. Daniel Acuña is an Associate Professor in the Department of Computer Science at the University of Colorado at Boulder. He leads the Science of Science and Computational Discovery Lab. He works in science of science, a subfield of computational social science, and A.I. for science. He writes papers and builds web-based software tools to accelerate knowledge discovery. His current research aims to understand historical relationships, mechanisms, and optimization opportunities of knowledge production.

Program Committee

Chair 1
Dr. Jian Wu

(Co-Chair)

Associate Professor

Old Dominion University, USA

jwu@cs.odu.edu +1 (757)-683-7753
Chair 1
Dr. Sarah Rajtmajer

(Co-Chair)

Associate Professor

The Pennsylvania State University, USA

smr48@psu.edu +1 (814)-863-2554
Chair 1
Dr. Yi He

(Co-Chair)

Assistant Professor

The College of William & Mary, USA

yihe@wm.edu +1 (757)-683-7821
Member 2
Dr. Yian Yin

Assistant Professor

Cornell University, USA

Member 2
Dr. Staša Milojević

Associate Professor

Indiana University, USA