Statistics and Its Interface

ISSN Print 1938-7989  ISSN Online 1938-7997

4 issues per year


Heping Zhang (Yale University)

HomeEditorsSubmissionsRead Online

Aims and Scope

Exploring the interface between the field of statistics and other disciplines, including but not limited to: biomedical sciences, geosciences, computer sciences, engineering, and social and behavioral sciences. Publishes high-quality articles in broad areas of statistical science, emphasizing substantive problems, sound statistical models and methods, clear and efficient computational algorithms, and insightful discussions of the motivating problems.


Publishing since 2008.

4 issues per year.


Statistics and Its Interface is partially sponsored by The Mathematical Sciences Center (MSC) of Tsinghua University.

Special Notices

Call for Papers: Special Issue on Statistical and Computational Theory and Methodology for Big Data

Submission deadline: November 1, 2014

Statistics and Its Interface (SII) invites submissions for a special issue on Statistical and Computational Theory and Methodology for Big Data. The integration of computer technology into science and daily life has enabled the collection of big data, such as high-throughput biological assay data, large-scale genomic sequencing data, climate data, website transaction logs, and credit card records. Big data are bringing a revolution in science and technology. It also presents challenges to the current statistical and computational theory and methodology. Thus, we strongly encourage substantive applications and computational developments for analyzing big data in all areas of sciences. High-quality review articles in this emerging new research area are also welcome. Your papers, once accepted, will be published together in a future issue of SII. Some of accepted papers may be chosen as invited discussion papers in this special issue.

All submissions must be made online through the website In the box labelled “comments to the editors,” please state that your submission is for the special issue on Big Data.

All submissions will undergo the normal review process. As the editors for this special issue, we will manage peer review carefully and in a timely manner. With your support and collaboration, we are confident that this special issue will succeed communicating state-of-art of research from the frontiers of this vital and rapidly developing area. We look forward to receiving your papers in due course.

Ming-Hui Chen (Co-Guest Editor), University of Connecticut
Radu V. Craiu (Co-Guest Editor), University of Toronto
Faming Liang (Co-Guest Editor), Texas A&M University
Chuanhai Liu (Co-Guest Editor), Purdue University
Heping Zhang (Editor-in-Chief), Yale University

Website copyright © by International Press of Boston, Inc. All rights reserved.

This page last updated: 2014 Jun 27 12:10 pm EST.