- About ASMBD 2025 -

2025 International Conference on Applied Statistics, Modeling and Big Data

The 2025 International Conference on Applied Statistics, Modeling and Big Data (ASMBD 2025) will be held on May 23-25, 2025 in Xi`an, China.

ASMBD is to bring together innovative academics and industrial experts in the field of applied statistics, modeling and big data in a common forum. The primary goal of the conference is to promote research and developmental activities in applied statistics, modeling and big data, and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in applied statistics, modeling and big data and related areas.

▶ Submission

 Please send the full paper(word+pdf) to Submission System : 

Submission (Pay by CNY)

Submission  (Pay by USD)

For more information, please click: Submission

▶ Registration

Access the registration system, Fill information and pay online. : 

Registration (Pay by CNY)

Registration  (Pay by USD)

For more information, please click: Registration

▶ Call For Papers

The topics of interest for submission include, but are not limited to:

Call for Papers

Templates: Downloads

▶ Publication

 All papers will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers will be published in the conference proceedings and will be submitted to EI Compendex, Scopus and Inspec for indexing.

All submitted articles should report original results, experimental or theoretical, not previously published or being under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.