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 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 Manuscripts submitted to the journal must present original and unpublished research and should not be under review elsewhere.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.
Publisher:
Payame Noor University Press
Editor-in-Chief:
Parviz Nasiri
Director-in-Charge:
Iman Makhdoom
Manager:
Vahdat Rafee
Editorial Board:
Siamak Noorbaloochi
Mohammed Zafar Anis
Mohammad Bameni Moghadam
Esmail Khorram
Rahim Chinipardaz
Abdolrahman Rasekh
Gholam Ali Parham
Alireza Nematollahi
Masoud Ganji
Mahmoud Afshari
Masoud Yarmohammadi
Gholamreza Hesamian
Alireza Daneshkhah
Ghodratollah Roshanaei
Hassan Doosti
Reza Pourtaheri
Ali Shadrokh
Kambiz Ahmadi Angali
Mehdi Jabbari Nooghabi
Abbas Pak
Narges Abbasi
Majid Jafari Khaledi
Rahim Mahmoudvand
Ahad Malekzadeh
Ali Mohammadian Mosammam
Amin Golabpour
Roshanak Alimohammadi
Sarah Jomhoori
English Text Editor:
Elkhas Vaysi
Frequency: Quarterly