European Journal of Emerging Data Science and Machine Learning (EJEDSML) is an international, peer-reviewed, open access journal dedicated to publishing high-quality research in emerging areas of data science, machine learning, big data analytics, and intelligent computational methods. The journal provides a platform for researchers, academicians, data professionals, and industry experts to share innovative methodologies and real-world applications across diverse domains including healthcare, finance, engineering, social sciences, and smart technologies. EJEDSML follows a rigorous double-blind peer review process and is supported by an international editorial board comprising experts from diverse academic, industrial, and research backgrounds. The journal strictly adheres to the Committee on Publication Ethics (COPE) guidelines, ensuring transparency, integrity, and ethical publishing practices. All published articles are released under a Creative Commons license, allowing unrestricted access, distribution, and reuse with proper citation, thereby enhancing the visibility and global impact of authors’ research.
Call for Papers: European Journal of Emerging Data Science and Machine Learning invites original research articles, review papers, technical reports, and interdisciplinary studies for its
Current Publication: Volume 03, Issue 01 (2026)
Frequency: Half-Yearly | Journal Type: Peer Reviewed | Open Access | International Journal
Open Access
Articles
Prof. Michael Thompson, Dr. Yuki Tanaka (Author) 1
Pages: 1-6 || Published: 2026-01-11
The accelerating convergence of predictive analytics, human resource management, and organizational capability development has fundamentally reshaped how contemporary organizations understand, manage, and retain human capital. In an era defined by pervasive digitization, continuous data generation, and heightened competition for skilled emplo... More >