aims&scop

Applied Data Science and Intelligent Systems (ADSIS) is an international, double-blind peer-reviewed interdisciplinary journal dedicated to advancing the theory, methodology, and application of data science, artificial intelligence, and intelligent systems across diverse scientific and professional domains.

The journal provides a platform for high-quality research that develops novel computational methods, data-driven models, intelligent algorithms, and analytical frameworks for solving complex real-world problems. ADSIS welcomes both methodological innovations and impactful applications where data science, machine learning, artificial intelligence, or computational intelligence constitute the primary scientific contribution.

Recognizing that intelligent technologies increasingly transcend disciplinary boundaries, the journal encourages interdisciplinary research integrating computational methods with domain knowledge in engineering, healthcare, business, economics, environmental sciences, education, agriculture, public policy, and other scientific and societal applications.

Priority is given to studies that demonstrate methodological rigor, reproducibility, analytical transparency, practical relevance, and clear scientific contributions. The journal particularly encourages submissions that release reproducible methodologies, benchmark datasets, open-source implementations, or validated computational frameworks that facilitate future research and real-world adoption.

Research Areas

The scope of the journal is organized into four complementary areas.

1. Core Data Science and Artificial Intelligence Methodologies

This area focuses on the development of novel computational methods, algorithms, and theoretical advances in data science and artificial intelligence, including but not limited to:

  • Artificial Intelligence
  • Machine Learning and Deep Learning
  • Statistical Learning
  • Data Mining and Knowledge Discovery
  • Predictive Analytics
  • Big Data Analytics
  • Data Engineering and Data Integration
  • Explainable and Interpretable AI
  • Responsible, Fair, and Trustworthy AI
  • Generative AI and Foundation Models
  • Large Language Models (LLMs)
  • Multimodal AI
  • Federated and Distributed Learning
  • Graph Learning and Graph Neural Networks
  • Reinforcement Learning
  • Causal Inference and Causal AI
  • Optimization and Metaheuristic Algorithms
  • Decision Intelligence
  • Intelligent Decision Support Systems

2. Intelligent Computing and Digital Technologies

This area covers intelligent computational infrastructures and enabling technologies that support modern AI-driven systems, including:

  • Intelligent Systems
  • Internet of Things (IoT)
  • Smart Systems
  • Cyber-Physical Systems
  • Digital Twins
  • Robotics and Autonomous Systems
  • Computer Vision
  • Signal, Image, Video, and Speech Processing
  • Natural Language Processing
  • Edge, Cloud, and Distributed Computing
  • Intelligent Cybersecurity
  • Human–AI Interaction
  • Smart Manufacturing and Industry 4.0
  • Smart Cities and Urban Intelligence
  • Sustainable Intelligent Computing

3. Data-Driven Applications Across Scientific and Societal Domains

The journal welcomes innovative applications of computational intelligence and data science across diverse disciplines where methodological contribution remains central, including:

  • Healthcare and Medical AI
  • Biomedical Informatics
  • Precision Medicine
  • Bioinformatics and Computational Biology
  • Public Health Analytics
  • Financial Analytics and FinTech
  • Business Analytics
  • Marketing Analytics
  • Supply Chain and Operations Analytics
  • Economic Modeling and Forecasting
  • Computational Social Science
  • Educational Data Mining and Learning Analytics
  • Environmental and Climate Analytics
  • Agricultural Data Science
  • Energy Systems Analytics
  • Transportation and Smart Mobility
  • Digital Government and Policy Analytics
  • Urban Analytics
  • Computational Linguistics
  • Digital Humanities
  • Cultural Analytics

4. Emerging Topics and Future Intelligent Systems

The journal particularly encourages research addressing rapidly evolving directions in artificial intelligence and data science, including:

  • Agentic AI
  • Autonomous Intelligent Systems
  • AI for Scientific Discovery
  • Human-Centered AI
  • AI Governance
  • Privacy-Preserving AI
  • Secure and Confidential Machine Learning
  • Green AI and Sustainable Computing
  • AI Ethics and Regulatory Frameworks
  • Digital Transformation
  • Intelligent Decision Ecosystems
  • AI for Sustainable Development Goals (SDGs)
  • Next-Generation Intelligent Information Systems

Types of Contributions

ADSIS welcomes the following categories of submissions:

  • Original Research Articles
  • Methodological Papers
  • Interdisciplinary Studies
  • Benchmark Studies
  • Reproducibility Studies
  • Review Articles
  • Application-Oriented Research

Submitted manuscripts should clearly demonstrate methodological novelty, computational rigor, experimental validation, and practical significance. Purely descriptive studies or domain-specific applications without substantial contributions to data science or artificial intelligence are generally outside the scope of the journal.