European Journal of Emerging Data Science and Machine Learning
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About the Journal

About Us

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.

Vision

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.

Mission

  • 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

What We Publish

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

Key Areas of Interest

  • 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

Editorial & Ethical Standards

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

Join Our Global Innovation Community

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.