Scope of the Journal

Machine Learning Foundations

Research covering supervised, unsupervised, semi-supervised learning, optimization, and statistical modeling.

Deep Learning Architectures

Work involving CNNs, RNNs, LSTMs, GANs, transformers, and next-generation neural architectures.

AI Applications

Breakthrough applications in vision, NLP, audio processing, robotics, biomedical AI, and automation.

Responsible & Secure AI

Research on explainability, fairness, federated learning, privacy-preserving AI, and model security.

Journal Highlights

Peer Review

Rigorous Double-Blind Peer Review

Each manuscript is evaluated by qualified reviewers to ensure originality, clarity, and scientific contribution.

Open Access

Fully Open Access

All articles are freely accessible to researchers worldwide, increasing the reach and visibility of your work.

Special Issues

Special Issues & Thematic Editions

The journal hosts special issues focusing on current breakthroughs in ML and DL technologies.

Fast Review

Fast & Transparent Publication

Authors receive the first decision within 4–6 weeks, ensuring timely and reliable communication.

Indexing

Indexing & Archiving

The journal aims for indexing in Google Scholar, CrossRef, Scopus (future), and other major academic platforms.

Ethics

Ethical Publishing Standards

All submissions undergo plagiarism checks and must comply with international publishing ethics guidelines.