Journal of Artificial Intelligence, Machine Learning and Data Science (JAIMLD - ISSN: 2583-9888) is an international, peer-reviewed, open access online journal on all aspects of artificial intelligence (AI), machine learning and data science published quarterly. As technology continues to rapidly evolve, our journal serves as a platform for researchers, academics, and industry professionals to explore and contribute to the latest developments in these exciting fields.

Journal Features

- Subject: Computer Science & Engineering; Science & Technology

- All papers are published in English and online

- Frequency of publication is quarterly

- ISSN: 2583-9888

- DOI: doi.org/10.51219/JAIMLD/....

- Double blind peer review process

Aim & Scope

Aim: This journal aims to provide scholarly input to the debate of the future impact of AI on society, as well as to host a forum in which research in AI focused on social good can be presented. JAIMLD is designed to meet the needs of a wide range of AI researchers, data scientists in academic and industrial research. With the rapid advancement of technology, AI, machine learning, and data science have become critical components in various industries, including healthcare, finance, transportation, and manufacturing.

The journal aims to publish research that is both theoretical and empirical, including papers that present novel algorithms, methodologies, models, and frameworks for solving challenging problems in AI, machine learning, and data science.

Scope: The scope of the journal extends to the application of intelligent systems in industry, medicine, and daily life. JAIMLD covering a wide range of issues from the tools and languages of artificial intelligence (AI) to philosophical implications. The journal provides a vigorous forum for the publication of both theoretical and experimental research, as well as surveys and impact studies. We prioritize original research that presents new methods, techniques, or applications in AI, machine learning, and data science, as well as innovative interdisciplinary research that combines these fields with other disciplines such as mathematics, electrical and electronics engineering, biomedical engineering, mechanical engineering, AI ethics and psychology.

At our journal, we cover a broad range of topics, including but not limited to:

Deep learning and neural networks, Natural language processing and speech recognition, Computer vision and image processing, Reinforcement learning and decision-making, Data mining and knowledge discovery, Big data analytics, Cloud computing, Internet of Things (IoT), Robotics and autonomous systems, Human-computer interaction, Machine learning algorithms and techniques, Explainable AI and interpretability, AI applications in healthcare, finance, marketing, and other fields, Ethical and social implications of AI and machine learning, Ethics and social implications of AI, Bayesian inference, Statistical modelling, Algorithm design and optimization, Predictive modelling, Cloud computing, Internet of Things (IoT), Predictive modelling, Statistical learning. Cognitive computing, Machine Learning Algorithms and Models, Cybersecurity and Privacy, Social Network Analysis, Sensor Networks, Bayesian networks and probabilistic reasoning, Ethics and social implications of AI, Explainable AI and interpretability, AI algorithms and architectures, Optimization and decision making, Bayesian networks and probabilistic graphical models, Ethical, legal, and social implications of AI.

JAIMLD also operates a double-blind peer-review process, which ensures the impartiality and objectivity of the review process. Categories of contributions accepted for the journal are research articles, reviews, debates, short communications, reviews of books, perspectives.

In order to reach the worldwide community of artificial intelligence (AI), the Journal of Artificial Intelligence, Machine Learning & Data Science (JAIMLD) is dedicated to rapid dissemination of important research results.

About special issues: Journal of Artificial Intelligence, Machine Learning and Data Science (JAIMLD) runs special issues to create collections of papers on specific topics. The aim is to build a community of authors and readers to discuss the latest research and develop new ideas and research directions. Special Issues are led by Guest Editors who are experts in the subject and oversee the editorial process for papers. Papers published in a Special Issue will be collected together on a dedicated page of the journal website. For any inquiries related to a Special Issue, please contact the Editorial Office at [email protected].

Thank you for visiting JAIMLD, and we hope that our journal will serve as a valuable resource for the academic community and industry professionals interested in the latest developments in AI, machine learning, and data science.