Special Issue on Frontiers in Statistical Learning: Data, Networks, and Knowledge Transfer

Aims and Scope

Statistical Learning and Data Science (SLADS) is a newly launched journal sponsored by the Chinese Academy of Sciences, dedicated to publishing high-quality research across statistics, machine learning, artificial intelligence, and data science. SLADS emphasizes both rapid publication and rigorous peer review, using the OpenReview system to ensure transparency and quality. The editorial goal is to reach an Accept/Reject decision within 3.5 months of submission while maintaining high scholarly standards.
This special issue aims to showcase cutting-edge advances in theory, methodology, and applications across the broad spectrum of modern statistical learning.

Submission Deadline: June 30, 2026

• Early submissions will be reviewed and published online ahead of the final issue.

Topics of Interest

Data

• Curation and Integration — Managing and combining diverse, large-scale datasets.
• Multimodal Modeling — Analyzing varied data types, including text, images, and video.
• Data Integrity — Ensuring data quality, consistency, and effective representation.

Networks

• Relational Inference — Modeling and drawing conclusions from social or relational data.
• Complex Representations — Tensor and matrix-based methods for complex interactions.
• Random Matrix Theory — Foundations and applications within networked learning.

Knowledge Transfer

• Cross-Domain Learning — Transfer and multi-task learning across heterogeneous settings.
• Distributed Learning with Privacy — Federated and privacy-preserving model frameworks.
• Adaptive Model Sharing — Theory and practice of dynamic, collaborative model sharing.

Guest Editors

• Yang Feng (New York University)
• Guangming Pan (Nanyang Technological University)
• Jiaming Xu (Duke University)
• Emma Zhang (Emory University)

Submission Information

Manuscripts should be submitted through the SLADS website at http://slads.scichina.com.

Contact: Ruiyan Zhang, zhangry@scichina.com