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Academic Journal

International Journal of Intelligent Systems and Data Science

ISSN: 3143-2328 Building robust, ethical, and scalable data-driven and intelligent systems requires an integrated approach that recognizes the close interdependence between data, analytics, computing infrastructure, and decision-making processes. Advances in data science, machine learning, and information systems increasingly influence decision-making across science, industry, governance, and society, making it essential to address not only technical performance but also reliability, transparency, and long-term sustainability. This includes developing methods that are resilient to data uncertainty, bias, and distributional shifts, as well as designing systems that can adapt to evolving real-world conditions. Achieving meaningful progress in data science and intelligent systems demands attention to foundational challenges such as data quality, model interpretability, computational efficiency, system scalability, and responsible deployment. Equally important are broader structural considerations, including access to data and computational resources, skills development, data governance, privacy, and the societal implications of data-driven technologies. Addressing these challenges requires collaboration across disciplines, combining theoretical advances with applied research and empirical validation. The International Journal of Intelligent Systems and Data Science (IJISDS) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from data science, analytics, information systems, machine learning, decision support systems, cloud and distributed computing, and allied domains to deepen understanding of how data-driven and intelligent systems can be designed, evaluated, optimized, and applied responsibly. IJISDS supports research that bridges theory and practice, encouraging contributions that demonstrate both methodological rigor and real-world relevance. Through its editorial standards and publishing practices, IJISDS actively promotes reproducibility, ethical responsibility, and transparent peer review. The journal also seeks to contribute to broader global priorities by supporting research aligned with sustainable development, digital innovation, responsible data practices, and trustworthy analytics, recognizing the critical role that data science and intelligent systems play in shaping resilient and equitable futures.

ISSN2589-0042
Publishing modelOpen Access
Latest IssueAug 26, Vol. 1, Issue 4
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Archives

Journal Cover Front

Vol. 1 No. 4 (2026)

Published: Aug 22, 2026

This issue brings together a broad range of research spanning artificial intelligence, machine learning, cybersecurity, enterprise systems, data engineering, blockchain, computer graphics, software testing, and computational science. The featured studies explore interpretable EEG-based stress classification, privacy-preserving machine learning, intelligent cyber incident response, SAP S/4HANA automation, anomaly detection, graph algorithms, sentiment analysis, decentralized identity, and advanced visualization and simulation techniques. Collectively, these contributions demonstrate how emerging computational methods can address complex challenges in intelligent systems, secure data management, enterprise decision-making, scientific computing, and the development of robust, scalable, and trustworthy digital technologies.

Journal Cover Front

Vol. 1 No. 3 (2026)

Published: Jun 29, 2026

This issue presents research at the intersection of artificial intelligence, data science, and modern computational systems. The contributions explore advances in large and small language models, distributed cognitive systems, blockchain technologies, cybersecurity, container orchestration, embedded systems, dynamic optimization, and machine learning applications in agriculture and audio synthesis. Combining theoretical innovations with practical implementations, the articles highlight the growing convergence of intelligent algorithms and scalable computing infrastructures, reinforcing the importance of interdisciplinary research in addressing complex scientific and engineering challenges.

Journal Cover Front

Vol. 1 No. 2 (2026)

Published: Jun 1, 2026

This issue presents research advancing intelligent computing, data science, cloud infrastructure, cybersecurity, and autonomous systems. The featured articles explore machine learning optimization, scalable Bayesian methods, DevOps automation, virtualized infrastructure evaluation, enterprise SaaS architectures, and AI-driven anomaly detection. Additional contributions address collaborative robotics, automated analytical workflow generation, computational performance optimization, cloud access-control verification, container security, healthcare interoperability security, and scientific mobility analysis. Collectively, these studies highlight innovative approaches for building secure, scalable, and intelligent systems that support modern data-driven technologies and decision-making.

Journal Cover Front

Vol. 1 No. 1 (2026)

Published: Apr 25, 2026

This issue of the International Journal of Intelligent Systems and Data Science (IJISDS) presents a curated selection of research focused on the optimization and security of modern computational frameworks. The featured papers investigate a diverse range of technical challenges, including the efficacy of sandboxing environments, entropy-constrained semantic modeling, and the orchestration of virtualized storage infrastructures.

Furthermore, this collection explores practical applications in environmental forecasting, swarm robotics, and distributed AI, offering modular solutions for collaborative learning and robust data processing in complex ecosystems.