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.
