ARTIFICIAL INTELLIGENCE VANGUARD JOURNAL

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About the Journal

Editorial Team

Ghada Mohammed Amer
Dean,Egypt

Shaoyong Han
Associate Professor,China

Manta P Elena Otilia
Associate Professor,Romania

Mohammad Khishe
Associate Professor,Iran (Islamic Republic of)

The Artificial Intelligence Vanguard Journal (AIVJ) is an international, peer-reviewed open access journal dedicated to publishing pioneering research in the field of artificial intelligence. Published by Boffin Access Limited, the journal serves as a trusted global platform for advancing knowledge, fostering innovation, and shaping the future of intelligent systems.

Led by a distinguished editorial board comprising leading scholars and industry experts, AIVJ upholds the highest standards of academic integrity through a rigorous double-blind peer review process. Each manuscript is evaluated for originality, scientific merit, and ethical compliance, ensuring the publication of only the most impactful contributions.

As a fully open access journal, AIVJ ensures unrestricted visibility, citation, and dissemination of published work across the global research community. The journal actively promotes cross-disciplinary collaboration, encourages debate on the ethical and societal implications of AI, and publishes special issues on frontier topics. In doing so, AIVJ not only documents progress in artificial intelligence but also guides its responsible development for the benefit of society.

Aims and Scope

The Artificial Intelligence Vanguard Journal (AIVJ) is an international, peer-reviewed open access journal published by Boffin Access Limited. It provides a premier platform for disseminating cutting-edge research and development in artificial intelligence.

The journal covers the full spectrum of AI science, methodologies, and applications, including but not limited to:

  • Machine Learning & Deep Learning – supervised, unsupervised, reinforcement learning

  • Natural Language Processing & Conversational AI – speech recognition, dialogue systems, text analytics

  • Computer Vision & Pattern Recognition – image analysis, object detection, scene understanding

  • Robotics & Intelligent Agents – autonomous systems, human–robot interaction, adaptive control

  • Trustworthy & Explainable AI – interpretable models, safety, security, and fairness in AI

  • Ethics, Law & Society – governance, policy, societal impact, and responsible innovation

  • Applied AI – healthcare, finance, transportation, education, manufacturing, and beyond

  • Next-Generation AI – cognitive computing, neuromorphic engineering, and brain-inspired architectures

AIVJ publishes a variety of contributions, including original research articles, technical notes, review papers, perspectives, and short communications that advance the state of the art in AI. The journal encourages cross-disciplinary collaboration among researchers, engineers, and practitioners to foster innovation and global knowledge exchange.

Beyond technical progress, AIVJ serves as a forum for debate on the ethical, societal, and policy dimensions of artificial intelligence. By promoting transparency, accountability, and responsible innovation, the journal seeks to shape the future of AI while ensuring its benefits are shared equitably across society.

Through this mission, the Artificial Intelligence Vanguard Journal aspires to be a leading resource for scholars, professionals, policymakers, and the wider public engaged with the transformative potential of artificial intelligence.

Subjects covered by the Artificial Intelligence Vanguard Journal

  • Machine learning
  • Reinforcement learning
  • Computer vision
  • Knowledge representation and reasoning
  • AI ethics and societal impacts
  • Decision making under uncertainty
  • Neural networks and neural computation
  • Evolutionary computation and genetic algorithms
  • Game theory and multi-agent systems
  • Ontologies and semantic web technologies
  • Human-robot interaction and collaboration
  • Fairness, accountability, and transparency in AI
  • AI for healthcare and medical applications
  • AI for education and learning applications
  • Intelligent virtual assistants and chatbots
  • Deep learning
  • Natural language processing
  • Robotics and autonomous systems
  • Human-computer interaction
  • Cognitive modeling and cognitive architectures
  • Bayesian networks
  • Fuzzy logic and fuzzy systems
  • Swarm intelligence and swarm robotics
  • Uncertainty modeling and reasoning
  • Rule-based systems and expert systems
  • Explainable AI and interpretability of models
  • Privacy and security in AI systems
  • AI for finance and business applications
  • AI for transportation and mobility applications
  • Social and affective computing

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