Why SLADS?
Our Mission
SLADS was created to address a critical gap in statistical publishing. While the field has evolved rapidly with advances in AI and data science, existing statistical journals have not fully kept pace with these developments. Our journal aims to bridge this divide by focusing on cutting-edge research at the intersection of these disciplines. We are building a transformative platform that integrates rigorous statistical theory with modern computational and data-driven methodologies.
Distinguished Leadership
Our journal is supported by a distinguished Advisory Board and editorial leadership team:
David Donoho
Stanford University
Jianqing Fan
Princeton University
Michael I. Jordan
UC Berkeley
Jun Liu
Harvard University
Wing H. Wong
Stanford University
Editors in Chief
- Song Xi Chen
- Jiashun Jin
Editors
- Runze Li (Statistics)
- Weijie Su (Machine Learning)
- Hongyu Zhao (Data Science)
Innovative Review Process
SLADS employs the OpenReview platform for its manuscript review process to enhance the integrity and impact of the scholarly record. Upon final article acceptance, the complete review history—including all reviewer comments, author responses, and editorial decisions—is made publicly available on the OpenReview website.
The platform also facilitates an interactive review process: authors are encouraged to engage in open discussion with reviewers, submit detailed rebuttals to clarify any potential misunderstandings transparently, and subsequently update their paper. This emphasis on constructive communication helps resolve disagreements more efficiently, reduces the need for unnecessary revisions, and allows the entire review process to be completed within a single round.
Join Our Community
We believe your expertise and research contributions would greatly enrich our journal. We welcome both original research articles and review papers.