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MLAIJ 2026 : Machine Learning and Applications: An International Journal

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Link: https://airccse.org/journal/mlaij/index.html
 
When N/A
Where N/A
Submission Deadline Jan 23, 2026
Notification Due Feb 21, 2026
Final Version Due Feb 28, 2026
Categories    machine learning   computer science   robotics   artificial intelligence
 

Call For Papers

Machine Learning and Applications: An International Journal (MLAIJ)

Citations, h-index, i10-index of MLAIJ

Scope & Topics

Machine Learning and Applications: An International Journal (MLAIJ) is a quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the machine learning. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of machine learning and applications.The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on machine learning advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of machine learning.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of machine learning.

Topics of interest include but are not limited to, the following

  • Machine Learning Algorithms
  • Learning in knowledge-intensive systems
  • Learning Methods and analysis
  • Supervised Machine Learning
  • Unsupervised Machine Learning
  • Deep Learning
  • Neural Networks
  • Reinforcement Learning
  • Predictive Learning
  • Learning Problems
  • Computer Vision
  • Bayesian Network
  • Data Mining

Paper Submission

Authors are invited to submit papers for this journal through E-mail: mlaijjournal@airccse.org or through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates

Submission Deadline:January 23, 2026
Authors Notification: February 21, 2026
Final Manuscript Due: February 28, 2026
Publication Date:Determined by the Editor-in-Chief

Current Issue


December 2025, Volume 12, Number 4

About an Automating Annotation Method for Robot Markers Full Text
Wataru Uemura and Takeru Nagashima, Ryukoku University, Japan

AI Based Transformation Projects-Language Processing Environments for Audit and Governance (LPE_AG) - the Proof of Concept Full Text
Antoine Trad, Paris La-Defense France, France

AI Based Transformation Projects-ML and NLP Managed Audit, Control, and Governance (ML_ACG) - the Basics Full Text
Antoine Trad , Paris La-Defense France, France

September 2025, Volume 12, Number 3

Preserving Employees' Personal Knowledge During the Transition to Automated Production Full Text
Ekaterina Mashina, Germany

June 2025, Volume 12, Number 2

Comparing Classifiers in the Presence of Errors in True Label Assignment in Medical Datasets Full Text
Vishwa Vallabh Angampally and Eugene Pinsky, Metropolitan College Boston University, USA

March 2025, Volume 12, Number 1

Revolutionizing Big Data with AI-Driven Hybrid Soft Computing Techniques Full Text
Praveen Kumar Myakala, Anil Kumar Jonnalagadda and Prudhvi Naayini, Independent Researchers, USA


Understanding the Heterogeneous Impact of Remittances on Saving Behaviour in Uzbekistan: A Machine Learning Approach Full Text
Masuda Isaeva, Asakabank, Uzbekistan


Cluster-Specific Propensity Score Weighting To Stabilize Treatment Effect Estimation Full Text
Hardev Ranglani, EXL Service Inc, USA


Artificial Intelligence and Cloud Computing in Healthcare: Innovations and Impacts Full Text
Mohammad Amir Salari, Saint Louis University, USA


Artificial Intelligence Based Business Transformation Projects-the Role of Data Sciences in Mixed-Methods Patterns (RDSMMP) Full Text
Antoine Trad, IBISTM, France


Estimating the Accuracy of a Bagged Ensemble Full Text
Eugene Pinsky and Siddhant Shah, Boston University, USA


Analyzing Fashion Trends Using Hierarchical Clustering and Temporal Analysis Full Text
Shivani Parab and Eugene Pinsky, Boston University, USA


Quantile Regression with Q1/Q3 Anchoring: A Robust Alternative for Outlier-Resistant Modeling Full Text
Xiaoying Zeng and Eugene Pinsky, Boston University, USA


An Adaptive Hierarchical Tree-Based Clustering Approach to Outlier Detection in ETF-Focused Financial Time-Series Full Text
Shlok Mandloi, Aryaman Jalali, and Eugene Pinsky, Boston University, USA


Detection of Alzheimer’s Disease using Bidirectional LSTM and Attention Mechanisms Full Text
Mehdi Ghayoumi and Kambiz Ghazinour, SUNY, USA


Analysis of Unsupervised Clustering Algorithms and Impact of Dimensionality Reduction: A Data Driven Approach Full Text
Palak Narula, Adobe Inc., India

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