The International Journal of Artificial Intelligence & Data Science (IJAIDS) aims to publish cutting-edge research that advances the theoretical foundations, practical applications, and interdisciplinary integration of Artificial Intelligence (AI) and Data Science. The journal provides a scholarly platform for researchers, academicians, and professionals to share innovative methodologies, emerging technologies, and real-world implementations.
IJAIDS welcomes original research articles, review papers, and case studies in (but not limited to) the following areas:
- Artificial Intelligence: Machine learning, deep learning, reinforcement learning, neural networks, evolutionary algorithms, knowledge representation, and reasoning.
- Data Science: Big data analytics, data mining, statistical modeling, data visualization, and data engineering.
- Natural Language Processing: Text mining, sentiment analysis, machine translation, speech recognition, and conversational AI.
- Computer Vision: Image and video processing, object detection, facial recognition, and visual scene understanding.
- Robotics & Intelligent Systems: Autonomous systems, AI in control systems, and human-robot interaction.
- AI Applications: Healthcare, finance, cybersecurity, education, smart cities, and industrial automation.
- Ethics & Societal Impact: Responsible AI, bias and fairness in AI, explainable AI, and the intersection of AI with policy and law.
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.