The Journal of Advances in Statistical Learning and Data Analysis (JASLDA) is an open-access, double-blind, peer-reviewed academic journal published by Payame Noor University, one of the leading higher education institutions in Iran. The journal aims to provide a scientific platform for the exchange of knowledge and the dissemination of original research in the fields of statistical learning, data analysis, biostatistics, time series modeling, fuzzy statistics, statistical modeling, statistical inference, reliability and operation research, optimization algorithms and statistical quality control.

JASLDA seeks to publish high-quality theoretical, methodological, and applied research that contributes to the advancement of modern statistics and data science. The journal encourages submissions that explore innovative statistical techniques, machine learning approaches, and interdisciplinary applications in engineering, health, and other related areas.

To ensure broad accessibility to recent scientific developments, JASLDA follows an open-access policy, allowing free and immediate access to all published articles. Manuscripts submitted to the journal must present original and unpublished research and should not be under review elsewhere.
The journal is published in both print and online formats to serve the global statistical research community.


📊 Call for Papers – Next Issue

The Journal of Advances in Statistical Learning and Data Analysis (JASLDA) is pleased to announce that articles in its first issue are being published online on a rolling basis.

The journal is now welcoming submissions for its upcoming issue. We cordially invite researchers, academics, and practitioners to submit their original, high-quality research articles in the fields of statistics, statistical learning, data science, artificial intelligence, machine learning, and related areas.

We look forward to receiving your valuable contributions and to advancing high-quality scientific research and scholarly exchange.