International Journal of Artificial Intelligence & Data Science [IJAIDS]

Aim of the Journal

The journal encourages interdisciplinary work that integrates AI and data science with fields such as biology, physics, medicine, linguistics, social sciences, and environmental studies.

By bridging academic theory with real-world challenges, IJAIDS seeks to foster the responsible and impactful development of intelligent systems and data-driven solutions.

Scope of the Journal

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Reinforcement Learning
  • Neural Networks
  • Explainable Artificial Intelligence (XAI)
  • Generative AI and Large Language Models (LLMs)
  • Knowledge Representation and Reasoning
  • Expert Systems
  • Intelligent Agents and Multi-Agent Systems
  • Data Science
  • Big Data Analytics
  • Data Mining
  • Predictive Analytics
  • Statistical Learning
  • Data Engineering
  • Data Visualization
  • Data Governance and Data Quality
  • Natural Language Processing (NLP)
  • Text Mining and Sentiment Analysis
  • Speech Recognition and Processing
  • Conversational AI and Chatbots
  • Information Retrieval
  • Computer Vision
  • Image Processing
  • Video Analytics
  • Pattern Recognition
  • Biometric Systems
  • Robotics and Intelligent Systems
  • Autonomous Systems
  • Human–Computer Interaction (HCI)
  • Human–Robot Interaction
  • AI in Healthcare and Bioinformatics
  • AI in Finance and FinTech
  • AI in Education and E-Learning
  • AI in Cybersecurity
  • AI for Smart Cities
  • AI in Agriculture and Environment
  • Industrial AI and Automation
  • Internet of Things (IoT) and AIoT
  • Edge AI and Cloud-Based AI
  • Cyber-Physical Systems
  • Ethical AI and Responsible AI
  • AI Fairness, Transparency, and Bias
  • AI Security and Privacy
  • AI Policy, Governance, and Societal Impact
  • Interdisciplinary Applications of AI and Data Science