About the Journal

Aims & Scope

Artificial Intelligence and Big Data Computing(AIBDC) is an international, peer-reviewed, open-access journal committed to publishing high-quality, original research articles, review papers, and case studies at the intersection of artificial intelligence (AI) and big data computing. The journal aims to provide a premier platform for researchers, academicians, and industry professionals to share groundbreaking research, innovative methodologies, and practical applications that drive advancements in these dynamic fields.

Scope of the Journal:

  1. AI Algorithms and Techniques:

    • Machine learning and deep learning
    • Natural language processing
    • Computer vision and image analysis
    • Reinforcement learning and adaptive systems
    • AI-driven decision-making and predictive analytics

  2. Big Data Technologies and Infrastructure:

    • Scalable data storage and management
    • Distributed computing and cloud-based solutions
    • High-performance computing for big data
    • Data lakes and data warehouses
    • Real-time data processing and stream analytics

  3. Integration of AI and Big Data:

    • AI-driven big data analytics
    • Data mining and knowledge discovery
    • Big data for training AI models
    • AI and big data in the Internet of Things (IoT)
    • Edge computing and AI at the edge

  4. Applications of AI and Big Data:

    • AI and big data in healthcare and genomics
    • AI and big data in finance and economics
    • AI and big data in smart cities and urban planning
    • AI and big data in environmental monitoring and sustainability
    • AI and big data in cybersecurity

  5. Ethics and Governance:

    • Ethical considerations in AI and big data
    • Data privacy and security
    • Bias and fairness in AI algorithms
    • Policy and regulation for AI and big data
    • Transparency and explainability in AI systems

  6. Interdisciplinary Research:

    • AI and big data in social sciences and humanities
    • AI and big data in cognitive science and neuroscience
    • AI and big data in education and learning technologies
    • AI and big data in industrial applications
    • Cross-disciplinary applications and innovations

Submission Types: The journal welcomes a variety of submission types, including but not limited to:

  • Original research articles
  • Comprehensive review papers
  • Case studies and application reports
  • Technical notes and short communications

By fostering the exchange of ideas and advancements, the Artificial Intelligence and Big Data Computing journal aims to significantly contribute to the progress and practical implementation of AI and big data technologies.

Publication Frequency

The journal is published online continuously in annual general issues. Articles included in special issues are published at one time, and the issue is then closed to additional articles.

Peer Review Type

Double anonymized

Reviewer identity is not made visible to author, author identity is not made visible to reviewer, reviewer and author identity is visible to (decision-making) editor.

Open Access Type

Full Gold Open Access

The final version of an article is freely and permanently accessible for everyone, immediately after publication.
No subscription fees are charged for any part of a journal that is fully gold open access.

Archiving Policy

We focus on making content discoverable and accessible through indexing services. Content is also archived to ensure long-term availability. The journal is indexed by the following services:

Google Scholar, the journal is available for harvesting via OAI-PMH.

To ensure the permanency of the journal, we utilize the Portico archiving system to create permanent archives for the purposes of preservation and restoration.

If the journal is not indexed by your preferred service, please let us know by emailing:  office@esdpub.com

 

 

Detailed information on policies and guidelines regarding our open access policy, copyrights and licenses, etc. can be viewed in our resource list.