Journal of Computer and Information Sciences - Impact Factor

Journal of King Saud University - Computer and Information Sciences | 2024 Impact Factor:6.9 | Cite Score:6.9 | Q1

Journal of King Saud University - Computer and Information Sciences - Impact Factor

Impact Factor and Journal Rank of Journal of Computer and Information Sciences

About: The Journal of King Saud University - Computer and Information Sciences (JKSUCIS) is a respected academic journal that focuses on publishing high-quality research in the fields of computer science and information technology. It is affiliated with King Saud University in Saudi Arabia and published by Elsevier. The journal serves as an international platform for researchers, practitioners, and academics to share their findings and advancements in various areas of computer and information sciences.
Content Types: Original research papers presenting new theories, methodologies, and empirical findings in the field of computer and information sciences. In-depth reviews and surveys that summarize the current state of research, highlight significant trends, and suggest future research directions.
High Standards and Impact: The journal maintains rigorous peer-review standards to ensure the publication of high-quality and impactful research. It is indexed in several major databases, making it widely accessible and recognized in the global research community.
Global Reach: JKSUCIS attracts contributions from a diverse range of researchers and practitioners worldwide, promoting a global exchange of ideas and innovations.
Significance: It is a leading academic journal that significantly contributes to the advancement of computer and information sciences. Its wide-ranging scope, rigorous standards, and international reach make it an essential resource for researchers, practitioners, policymakers, and educators dedicated to exploring and shaping the future of this rapidly evolving field.

Journal Home: Journal Homepage

Editor-in-Chief: Professor Nasser-Eddine Rikli

Scope: The Journal of King Saud University - Computer and Information Sciences (JKSUCIS) is a scholarly journal that publishes high-quality, peer-reviewed research articles in the fields of computer science and information technology. The journal aims to disseminate original research, innovative methodologies, and practical applications across a broad range of topics within these disciplines.
The scope of the journal includes, but is not limited to, the following key areas:
Artificial Intelligence and Machine Learning: Research on AI and machine learning algorithms, applications, and systems, including neural networks, deep learning, reinforcement learning, and natural language processing.
Data Science and Big Data Analytics: Studies on data mining, big data analytics, data visualization, and data-driven decision-making, including techniques for handling large-scale datasets.
Computer Networks and Communications: Research on computer networking, network protocols, network security, wireless communication, and the Internet of Things (IoT).
Software Engineering: Advances in software development methodologies, software testing, software project management, and software quality assurance.
Cybersecurity and Information Security: Studies on cryptography, network security, cyber defense, privacy protection, and secure computing environments.
Cloud Computing and Distributed Systems: Research on cloud computing architectures, services, virtualization, distributed computing, and edge computing.
Human-Computer Interaction (HCI): Studies on the design, evaluation, and improvement of user interfaces, user experience, and interaction techniques for computing systems.
Computer Graphics and Visualization: Research on computer graphics, visualization techniques, virtual reality (VR), augmented reality (AR), and visual analytics.
Robotics and Autonomous Systems: Advances in robotic systems, autonomous vehicles, robotic perception, control, and human-robot interaction.
Bioinformatics and Computational Biology: Studies on the application of computational techniques to biological and medical data, including genome analysis, protein structure prediction, and health informatics.