Aims and Scope
The "Journal of Interdisciplinary Studies in Artificial Intelligence" by Baqir al-Olum University (AS) publishes original scientific-research and review articles focusing on Artificial Intelligence and its interdisciplinary applications across various sciences (including Humanities, Islamic Sciences, Management, Engineering, Medicine, and Arts). All submissions undergo a rigorous peer-review process and are published Open Access (free for readers and without article processing charges for authors).
The primary audience for this journal includes researchers, university professors, postgraduate students, industry professionals, and policymakers interested in the theoretical and practical advancements of Artificial Intelligence and its impact on society and diverse scientific disciplines.
The main Aims of the Journal are:
- Providing a Scientific-Research Platform: To gather, evaluate, and disseminate the latest scientific findings, innovative research articles, and in-depth analyses from researchers, scholars, and experts in academia and industry across all fields related to Artificial Intelligence and its interdisciplinary studies.
- Promoting and Deepening AI Knowledge: To contribute to expanding the frontiers of knowledge in Artificial Intelligence, from theoretical foundations and algorithms to practical applications and ethical/social considerations.
- Strengthening Interdisciplinary Links: To create a space for dialogue and scientific collaboration between AI specialists and researchers from other disciplines to solve complex problems and offer innovative solutions.
- Offering AI-Based Solutions: It is hoped that by publishing high-quality articles, this journal can contribute to providing solutions for theoretical and practical challenges facing the development and application of responsible and ethical AI in Iran and globally.
- Establishing a Reputable Scientific Reference: To become a recognized and credible scientific reference at national and international levels for researchers in the field of interdisciplinary AI studies.
Scope of the Journal:
Given the interdisciplinary nature of Artificial Intelligence, the "Journal of Interdisciplinary Studies in Artificial Intelligence" welcomes articles from a wide range of subject areas, including but not limited to:
- Theoretical Foundations and Algorithms of AI:
- Machine Learning (Supervised, Unsupervised, Reinforcement)
- Deep Learning and Neural Networks
- Natural Language Processing and Understanding
- Computer Vision and Image Processing
- Pattern Recognition
- Expert and Knowledge-Based Systems
- Fuzzy Logic and Soft Computing
- Evolutionary Algorithms and Optimization
- Interdisciplinary Applications of AI:
- AI in Humanities and Social Sciences (e.g., Sociology, Psychology, Political Science, History, Linguistics)
- AI in Islamic Sciences and Religious Studies
- AI in Management and Business (e.g., Business Analytics, Smart Marketing, Supply Chain Management)
- AI in Medical Sciences and Healthcare (e.g., Disease Diagnosis, Personalized Medicine, Medical Robotics)
- AI in Engineering (e.g., Intelligent Control Systems, Industrial Robotics, Smart Cities)
- AI in Education and Learning
- AI in Arts and Creativity
- AI in Environmental Sciences and Agriculture
- Philosophical, Ethical, and Social Issues of AI:
- Ethics of AI and Responsible AI
- Transparency, Explainability, and Interpretability of AI Models
- Fairness and Bias in AI
- Data Privacy and Security in Intelligent Systems
- Social and Economic Impacts of AI
- The Future of AI and Human-Machine Coexistence
- Legal and Regulatory Issues related to AI
Types of Accepted Articles:
The journal accepts the following types of articles (after peer review):
- Original Research Articles: Reporting new and original research findings.
- Review Articles: Comprehensive and critical analysis of research conducted in a specific specialized area, presenting new perspectives.
- Short Communications/Letters: Presenting significant and concise research results that require rapid dissemination.
- Conceptual/Theoretical Papers: Presenting and developing new theoretical and conceptual frameworks.
- Case Studies: In-depth analysis of one or more specific cases to extract lessons learned and practical outcomes.
- Technical Notes: Describing new and practical methods, tools, or software.
- Book Reviews: (If decided by the Editorial Board)
