SLADS is a peer-reviewed quarterly journal sponsored by the Chinese Academy of Sciences. It serves the international statistics and data science community by publishing cutting-edge research and fostering discussions on future developments across all data-driven disciplines, including but not limited to biology, economics, engineering, health sciences, humanities, physics, and social sciences. Dedicated to excellence, SLADS commits to publishing only the highest quality research with significant impact in statistics, machine learning, and data science.

Open:         

Full open access with waived article processing charges (APCs)

Transparent yet rigorous peer review process powered by the OpenReview platform

Fast:          

Desk rejection within 7 days

Single-round review with an author rebuttal phase

Almost final decision in 3.5 months

Immediate online publication of accepted manuscripts (pre-copyedited version)

Online publication (copyedited and proofed) within 7 days of final acceptance

Diverse:     

Covers a wide spectrum of topics in statistics, machine learning, and data science, and welcomes contributions that introduce new datasets or present large-scale empirical studies.

Publishes Research papers, Review papers, Discussion papers, Short Communications, Perspectives, and Special topics.

Editorial Board