Journal of Artificial Intelligence Practice (JAIP)
Journal of Artificial Intelligence Practice (JAIP) is a journal dedicated to promoting and accelerating the dissemination of new research findings. There is a vast array of exciting research activities in this field worldwide. The journal aims to provide academicians and scientists around the globe with a platform to share, promote, and discuss various emerging issues and developments in different areas of artificial intelligence.
Aims & Scope
Journal of Artificial Intelligence Practice (JAIP) is a journal dedicated to promoting and accelerating the dissemination of new research findings. There is a vast array of exciting research activities in this field worldwide. The journal aims to provide academicians and scientists around the globe with a platform to share, promote, and discuss various emerging issues and developments in different areas of artificial intelligence.
Aims
- To promote and accelerate the dissemination of new research findings across the field of artificial intelligence globally.
- To provide academicians and scientists worldwide with a platform to share, promote, and discuss emerging issues and developments in all areas of artificial intelligence research and practice.
- To foster academic exchange, collaboration, and innovation in interdisciplinary research addressing the evolving challenges and applications of artificial intelligence technologies.
- To advance knowledge and practical solutions for real-world AI applications through rigorous scholarly publication, bridging the gap between theoretical research and industry practice.
Scope
The journal covers a wide range of topics related to artificial intelligence, including but not limited to:
Core Artificial Intelligence Technologies
- Machine learning and deep learning, including supervised/unsupervised learning, reinforcement learning, and neural network architectures
- Natural language processing, including text mining, machine translation, sentiment analysis, and conversational AI
- Computer vision and pattern recognition, including image/video analysis, object detection, and visual understanding
- Knowledge representation and reasoning, including expert systems, semantic web, and logical reasoning
AI Applications and Practical Systems
- AI in industry and automation, including intelligent manufacturing, predictive maintenance, and industrial robotics
- AI in healthcare and life sciences, including medical imaging analysis, drug discovery, and clinical decision support
- AI for smart cities and urban systems, including traffic management, environmental monitoring, and public services optimization
- AI ethics, fairness, and responsible AI, including bias mitigation, privacy-preserving AI, and regulatory frameworks