About the Journal

About the Journal

The International Journal of AI and Data Science Application (IJAIDSA) is an international scholarly journal dedicated to advancing research, innovation, and practical applications in the rapidly evolving fields of Artificial Intelligence (AI), Machine Learning, Data Science, Big Data, and Intelligent Computing.

The journal provides a multidisciplinary platform for researchers, academicians, industry professionals, practitioners, and students to share original research, innovative methodologies, experimental findings, case studies, and emerging developments that contribute to the advancement of AI and data-driven technologies.

IJAIDSA particularly encourages research that demonstrates the application of artificial intelligence and data science to real-world problems across diverse domains, including healthcare, education, finance, business, agriculture, manufacturing, engineering, cybersecurity, smart cities, social sciences, environmental sciences, transportation, communication, and other emerging areas.

The journal welcomes research covering both the theoretical foundations and practical implementation of intelligent systems. Areas of interest include, but are not limited to, machine learning, deep learning, natural language processing, computer vision, generative AI, reinforcement learning, data mining, predictive analytics, statistical learning, big data analytics, intelligent systems, knowledge representation, recommender systems, robotics, Internet of Things (IoT), explainable AI, responsible AI, and AI-driven decision support systems.

IJAIDSA also recognizes the growing importance of responsible and trustworthy artificial intelligence. Research addressing AI ethics, fairness, transparency, explainability, privacy, security, governance, human-AI interaction, and the societal impact of intelligent technologies is therefore encouraged.

The journal aims to facilitate the exchange of knowledge between academia and industry and to promote research that translates innovative concepts into meaningful technological and societal applications. By bringing together contributions from different disciplines and geographical regions, IJAIDSA seeks to contribute to the development of reliable, innovative, and responsible AI and data science solutions.

Scope of the Journal

The journal welcomes original research and scholarly contributions in areas including:

  • Artificial Intelligence and Intelligent Systems

  • Machine Learning and Deep Learning

  • Generative Artificial Intelligence and Large Language Models

  • Natural Language Processing

  • Computer Vision and Image Processing

  • Speech and Language Technologies

  • Data Science and Data Analytics

  • Big Data Technologies and Analytics

  • Data Mining and Knowledge Discovery

  • Predictive and Prescriptive Analytics

  • Statistical and Computational Methods

  • Reinforcement Learning

  • Explainable and Trustworthy AI

  • Responsible and Ethical AI

  • AI Security, Privacy, and Governance

  • Recommender and Decision Support Systems

  • Intelligent Automation and AI Agents

  • Robotics and Autonomous Systems

  • Internet of Things and Edge AI

  • AI in Healthcare and Biomedical Applications

  • AI in Education and Learning Analytics

  • AI in Finance, Business, and Economics

  • AI in Agriculture and Smart Farming

  • AI in Manufacturing and Industry 4.0

  • AI in Cybersecurity

  • AI for Smart Cities and Infrastructure

  • AI for Environmental and Sustainability Applications

  • Social Computing and Human-AI Interaction

  • Multimodal AI and Emerging AI Technologies

  • Applied Data Science and Domain-Specific AI Solutions

The journal considers original research articles, review articles, systematic reviews, case studies, application-oriented studies, methodological contributions, and other scholarly works that meet the journal's standards of academic quality and relevance.

IJAIDSA is committed to promoting rigorous research, meaningful knowledge exchange, and responsible innovation in artificial intelligence and data science.