Aims, Objectives, and Scope

The Journal of Computing and AI (JCAI) is an international, peer-reviewed scientific journal committed to advancing research at the intersection of artificial intelligence (AI), computing, and intelligent systems. JCAI serves as a global platform for researchers, engineers, and academicians to share innovative findings, methodologies, and applications across a wide range of AI-driven technologies.

The journal emphasizes the growing convergence of AI and computing disciplines, with a particular focus on enhancing automation, intelligent decision-making, and optimization through AI-based tools, techniques, and frameworks. JCAI aims to foster interdisciplinary research that explores the application of machine learning, deep learning, data analytics, and computational intelligence across diverse domains of computing.

All submissions undergo a rigorous double-blind peer-review process to ensure academic excellence, technical depth, and originality. The journal also welcomes comprehensive review articles, position papers, and case studies that offer valuable insights into emerging trends and future directions in AI and computing.

Objectives of the Journal

To publish high-quality, peer-reviewed research contributions that advance the integration of artificial intelligence, machine learning, and computing.
To promote interdisciplinary research that leverages AI technologies in traditional and modern computing domains.
To encourage the development of innovative methodologies that improve software development, intelligent systems, decision support, and automation.
To support ethical, explainable, and human-centered applications of AI in real-world systems.

Scope

JCAI publishes original research articles, review papers, and case studies in areas including, but not limited to:

Artificial Intelligence and Software Engineering

AI and Machine Learning in Software Engineering
AI-assisted Software Development and Testing
Machine Learning-based Software Optimization
Automated Bug Detection and Fixing
Deep Learning for Code Generation and Understanding
Natural Language Processing in Software Engineering
Large Language Models (LLMs) for Software Systems
AI-powered Requirements Engineering and Software Design
AI-driven DevOps and Continuous Integration
Explainable AI in Software Engineering
AI-driven Software Maintenance and Evolution
Decision Support Systems using AI
AI and Ethics in Software Development

Computing and Intelligent Systems

Computational Intelligence and Knowledge-Based Systems
Software Engineering for Autonomous and Smart Systems
Big Data Analytics in Software and System Design
Cyber-Physical Systems and IoT with AI
Human-AI Collaboration and Interaction
AI-based Cybersecurity and Secure Software Engineering
Evolutionary Algorithms and Genetic Programming in Computing

Cross-Domain Applications

AI in Bioinformatics, Robotics, Computer Vision, and Image Processing
Machine Learning Applications in Healthcare, Education, and Industry
Software Engineering Applications in Interdisciplinary Domains