Statistical Learning and Data Science (SLADS) is a peer-reviewed quarterly journal sponsored by the Chinese Academy of Sciences, serving the international statistics community. The journal publishes cutting-edge research while fostering discussions about future developments across all data-driven disciplines, including economics, social sciences, biology, physics, engineering, health sciences, and humanities. Dedicated to publishing only the highest quality, field-impacting research in the area of statistics, machine learning, and data science, SLADS features

Open: Full open access with waived article processing charges (APCs) Transparent open peer review process while maintaining rigorous standards

Fast: Desk rejection within 7 days First post-review decision within 60 days of submission Immediate online publication of accepted manuscripts (pre-copyedited version)

Online publication (copyedited and proofed) within 30 days of final acceptance

Diverse: Regular sections include: Research papers, Review papers, Discussion papers, Perspectives, and Special topics.