Call for Papers
Paper Guidelines
The Organizing Committee of ICAIDS 2026 invites researchers, academicians, industry professionals, and students to submit original research papers and review articles for presentation at the conference.
Submission Guidelines:
- Maximum length: 12 pages (single-column format)
- Review articles: Must include expanded findings and comparative analyses; prolonged literature reviews alone are not accepted
- Novelty: Papers should present new concepts, ideas for further development, detailed analyses, and clear conclusions
- Originality: Manuscripts must not be under review or published elsewhere
Template & Format:
Manuscript templates are available in .docx and .pdf formats in the Downloads section of the conference website submissions should include,
- Novel research concepts
- Ideas for further development
- Detailed analyses, conclusions, and outcomes
Author Information Required:
- Names and affiliations of all authors
- Name and email of the corresponding author
Submission Instructions:
- Prepare manuscripts using the required template
- Submit soft copies in both .doc and .pdf formats via email to: icaids2026@gmail.com
Conference Topics
Artificial Intelligence & Machine Learning
- Deep Learning, Reinforcement Learning, and Neural Networks
- Explainable AI (XAI) and Interpretable Models
- AI for Decision Support and Automation
Data Science & Big Data Analytics
- Data Mining and Knowledge Discovery
- Predictive Analytics and Forecasting
- Data Visualization and Interpretation
Natural Language Processing & Computer Vision
- Text Analytics, Sentiment Analysis, and Chatbots
- Image Recognition, Object Detection, and Video Analysis
- Multimodal AI Applications
AI in Industry & Society
- AI for Healthcare, Finance, and Smart Cities
- AI in Manufacturing and Robotics
- Ethical AI, Data Privacy, and Responsible AI Practices
Emerging Technologies & Tools
- Internet of Things (IoT) and Edge AI
- Cloud Computing and Distributed AI Systems
- AI-Driven Optimization and Automation Techniques
Applications & Case Studies
- AI and Data Science in Education, Environment, and Agriculture
- Real-world Case Studies of AI Implementation
- Innovative Solutions for Societal Challenges
