About the Journal

The Journal of Intelligent Computing and Data Systems (JICDS) is a peer-reviewed international journal dedicated to publishing high-quality, original research advancing the theory, methodology, and applications of artificial intelligence, computer science, and data-driven systems. The journal aims to promote innovative research in intelligent computing and modern data systems that address complex scientific, engineering, and societal challenges. It provides a global platform for interdisciplinary work that integrates computation, intelligence, and data-centric approaches to real-world problem-solving.

JICDS seeks to: advance foundational and applied research in artificial intelligence and intelligent systems, promote rigorous, scalable, and reproducible computational and data-driven methodologies, support the development of intelligent systems for real-world decision-making, bridge computer science, data science, engineering, and applied domains, and encourage ethical, transparent, and responsible use of intelligent technologies. The journal welcomes research that explores the interactions between algorithms, data, computation, and intelligent decision systems, with emphasis on real-world impact, system performance, and innovation.

The Journal of Intelligent Computing and Data Systems aims to publish high-quality, innovative, and policy-relevant research that advances understanding of artificial intelligence, machine learning, data science, and intelligent systems in addressing complex real-world challenges across science, engineering, health, environment, and society.

The journal seeks to:

• advance theoretical and applied research in artificial intelligence and data science

• promote rigorous, transparent, and reproducible computational methodologies

• support the development of intelligent, data-driven decision systems

• bridge research, technology, policy, and real-world applications

• encourage responsible, ethical, and human-centered AI innovation

JAIDSS encourages research that examines interactions, trade-offs, and synergies between data, algorithms, computation, and decision-making systems. The journal recognizes that modern AI systems are shaped by interconnected technological, statistical, computational, ethical, and societal processes.

The journal accepts interdisciplinary and systems-based studies and welcomes high-quality disciplinary research where findings have broader implications for AI performance, scalability, robustness, interpretability, fairness, and real-world deployment.

Core Areas of Interest

The Journal of Intelligent Computing and Data Systems publishes original research articles, reviews, technical papers, perspectives, and case studies that advance the theory and practice of intelligent computing and data-driven systems. The journal welcomes contributions in Artificial Intelligence and Machine Learning, including deep learning, neural networks, reinforcement learning, generative AI, explainable AI, pattern recognition, and intelligent decision support systems. It also covers Data Science and Data Systems, with emphasis on big data analytics, data engineering, data mining, predictive and statistical modelling, data integration, scalable data systems, and time-series forecasting.

The journal further considers research on Intelligent Computing Systems, focusing on autonomous and adaptive systems, edge, cloud, and distributed intelligence, cyber-physical systems, IoT-enabled intelligence, human–AI interaction, and smart computing architectures. In addition, it includes foundational and applied work in Algorithms and Computer Systems, such as computational theory, parallel and distributed computing, high-performance computing, software systems for intelligent applications, and system architecture and optimization.

Applied Artificial Intelligence is a key focus area, particularly studies demonstrating real-world deployment in healthcare, finance, agriculture, environmental and climate systems, cybersecurity, and intelligent transportation. The journal also strongly emphasizes Responsible and Ethical AI, encouraging research on fairness, transparency, accountability, privacy-preserving learning, AI governance, bias mitigation, and the broader societal impacts of intelligent systems.

Distinguishing Features of Journal of Intelligent Computing and Data Systems include:

The Journal of Intelligent Computing and Data Systems is distinguished by:

• A strong interdisciplinary focus integrating artificial intelligence, computing, and data systems

• Emphasis on both theoretical advances and real-world applications

• Commitment to reproducibility, transparency, and methodological rigor

• Focus on scalable and deployable intelligent systems in real environments

• Promotion of innovative computational approaches across diverse domains

• Encouragement of research addressing system-level performance, reliability, and impact

• Support for ethical, responsible, and human-centered AI development

Target Audience of Journal of Intelligent Computing and Data Systems serves

The Journal of Intelligent Computing and Data Systems serves a global audience of:

• Computer scientists and AI researchers

• Data scientists and machine learning engineers

• Software and systems engineers

• Academics and graduate researchers

• Industry practitioners and technology developers

• Policy makers and digital transformation experts

JICDS operates a continuous publication model. Articles are published online immediately after acceptance, production, and author proof approval. The journal publishes articles continuously and compiles them into annual volumes.