The European Journal of Emerging Data Science and Machine Learning (EJEDSML) is an international, peer-reviewed, open-access scholarly journal dedicated to advancing cutting-edge research in data science, artificial intelligence, machine learning, and computational intelligence. Published under the reputable Parthenon Frontiers Publishing House, this journal provides a premier platform for researchers, academicians, engineers, industry experts, and innovators to share impactful discoveries, algorithms, methodologies, and applications shaping the future of intelligent computing.
As data-driven technologies transform industries and society, EJEDSML aims to publish pioneering research that drives innovation, strengthens AI ecosystems, and fosters global collaboration in the rapidly expanding digital and computational landscape.
To become a leading European and globally recognized journal for breakthrough contributions in data science, machine learning, and artificial intelligence, fueling transformative discoveries and real-world advancements.
To publish high-quality, original, and rigorous academic research
To support interdisciplinary research across computing, engineering, and applied sciences
To promote transparency, ethical AI practices, and responsible technological progress
To foster global collaboration between academic, industrial, and research communities
To enable open-access knowledge-sharing that accelerates technological growth
EJEDSML welcomes diverse scholarly works including:
Original Research Papers
Technical Reports & Algorithmic Contributions
Review & Systematic Survey Papers
Machine Learning Models & Experimental Studies
Case Studies & Real-World Applications
Short Communications & Emerging Ideas
Perspectives, Commentaries & Framework Proposals
Data Science & Predictive Analytics
Machine Learning, Deep Learning & Reinforcement Learning
Artificial Intelligence & Intelligent Systems
Big Data Engineering & Data Mining
Computer Vision & Natural Language Processing
Cloud Computing, Edge Computing & Distributed AI
Data Privacy, Security & Ethical AI
Statistical Learning & Advanced Analytics
Scalable Computing & High-Performance Systems
AI in Healthcare, Finance, Cybersecurity, IoT & Smart Cities
Explainable AI (XAI) & Trustworthy Machine Learning
Computational Mathematics & Optimization Techniques
EJEDSML ensures academic excellence through:
Double-blind peer review
COPE-aligned publication ethics
International editorial & reviewer board
DOI assignment & indexing initiatives
Transparent and timely publishing process
We invite global researchers, AI practitioners, industry innovators, data scientists, engineers, and academic institutions to contribute their breakthroughs and be part of a dynamic community shaping the future of intelligent systems and computational science.