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The International Conference on Interdisciplinary Trends on Artificial Intelligence & Data Science (ICITAIDS - 2026) serves as a global platform for knowledge exchange across emerging AI and data-driven disciplines. It brings together researchers, academicians, industry professionals, and innovators from diverse domains. The conference emphasizes interdisciplinary approaches that bridge artificial intelligence with real-world applications. Participants will explore cutting-edge research, methodologies, and technological advancements. ICITAIDS-2026 encourages collaborative thinking to address complex societal and industrial challenges. The event promotes innovation through paper presentations, keynote talks, and technical discussions. It aims to foster meaningful academic–industry interactions in the evolving digital ecosystem. The conference will be conducted in virtual mode, ensuring global accessibility and participation. The scheduled date for the conference is 07 January 2026. ICITAIDS-2026 aspires to inspire future research directions and impactful technological solutions.
The International Conference on Interdisciplinary Trends on Artificial Intelligence & Data Science (ICITAIDS - 2026) covers a broad spectrum of research integrating AI with data-centric technologies. It focuses on theoretical foundations, computational models, and practical implementations across disciplines. The conference scope includes AI-driven solutions in healthcare, finance, education, smart systems, and sustainability. It encourages interdisciplinary research combining computer science, engineering, management, and social sciences. Emphasis is placed on ethical AI, data privacy, security, and responsible innovation. ICITAIDS-2026 provides a platform for presenting innovative ideas that shape future intelligent systems.
| Sno | Papers Title | Author |
|---|---|---|
| 1. | World Foundation Models for Autonomous Physical Intelligence in Next-Generation Smart Systems | Dr. Arjun Menon¹, Priya Sharma |
| 2. | Self-Evolving Agentic AI Through Recursive Test-Time Learning for Autonomous Decision Intelligence | Dr. Michael Anderson, Rahul Krishnan, Dr. Sneha Iyer |
| 3. | Memory-Augmented Large Reasoning Models for Long-Horizon Autonomous Task Planning | Dr. Kavin Raj, Emily Johnson |
| 4. | Neuro-Symbolic World Models for Explainable Scientific Discovery and Autonomous Knowledge Reasoning | Dr. Ethan Walker, Divya Nair |
| 5. | Spatial Intelligence Framework for Real-Time Human-AI Collaboration in Physical Environments | Dr. Harish Kumar, John Peterson, Ananya Rao |
| 6. | Universal AI Operating Systems for Coordinating Autonomous Multi-Agent Ecosystems | Dr. Sophia Carter, Vikram Singh |
| 7. | Hybrid Quantum-Agentic Computing Architecture for High-Performance Scientific Problem Solving | Dr. Naveen Babu, Keerthana Raj |
| 8. | Self-Verifying Foundation Models for Reliable Autonomous Research and Decision Making | Dr. William Harris, Riya Patel |
| 9. | Cognitive Digital Organisms: Self-Adaptive Artificial Intelligence for Autonomous Computing Networks | Dr. Suresh Narayanan, Jennifer Brown, Dr. Daniel Lee |
| 10. | Embodied Foundation Models for Intelligent Human-Robot Collaboration in Industry 6.0 | Dr. Rohit Verma, Olivia Martinez |
| 11. | Synthetic Universe Generation for Training Autonomous Physical Artificial Intelligence Systems | Dr. Akash Reddy, Sophia Wilson |
| 12. | Hierarchical Multi-Agent Intelligence Framework for Autonomous Enterprise Workflow Optimization | Dr. Benjamin Clark, Nithya Lakshmi |
| 13. | Adaptive Neural Memory Networks for Lifelong Continual Learning in Foundation Models | Dr. Karthik Srinivasan, Grace Thomas, Aravind Raj |
| 14. | Trust-Calibrated Agentic Artificial Intelligence for Human-Centered Decision Support Systems | Dr. Rachel Moore, Pranav Nair |
| 15. | Physics-Grounded World Models for Autonomous Navigation in Unknown Dynamic Environments | Dr. Lakshmi Prasad, Jacob Miller |
| 16. | Energy-Adaptive Green Foundation Models for Sustainable Artificial Intelligence Infrastructure | Dr. David Wilson, Meena Krishnan, Dr. Vivek Sharma |
| 17. | Test-Time Knowledge Editing Framework for Continually Learning Large Language Models | Dr. Arun Prakash, Jessica Taylor |
| 18. | Collective Swarm Intelligence Using Cooperative Agentic AI for Distributed Autonomous Systems | Dr. Christopher Evans, Aishwarya Menon |
| 19. | Cross-Reality Artificial Intelligence Integrating Physical, Digital, and Spatial Computing Ecosystems | Dr. Senthil Kumar, Ethan Roberts |
| 20. | Autonomous AI Scientists for Scientific Hypothesis Generation and Experimental Validation | Dr. Abigail Scott, Rahul Desai, Dr. Kavya Raman |
| 21. | Self-Healing Artificial Intelligence Infrastructure Using Autonomous Multi-Agent Orchestration | Dr. Mohan Raj, Sarah Thompson |
| 22. | Foundation Models for Universal Scientific Simulation Across Interdisciplinary Research Domains | Dr. Noah Mitchell, Pooja Kapoor |
| 23. | Causal World Models for Autonomous Decision Intelligence in Complex Dynamic Systems | Dr. Gokul Krishna, Emily Davis, Arjun Patel |
| 24. | Xeromorphic Argentic Computing for Ultra-Efficient Next-Generation Artificial Intelligence | Dr. Robert Green, Harini Suresh |
| 25. | World Model-Based Autonomous Cyber Defense Using Intelligent Multi-Agent Threat Reasoning | Dr. Vinay Kumar, Laura White |
| 26. | Large Reasoning Models for Explainable Scientific Computing Beyond Conventional Large Language Models | Dr. Andrew Collins, Deepika Iyer |
| 27. | AI-Native Autonomous Computing Platforms for Future Intelligent Digital Ecosystems | Dr. Praveen Natarajan, Kevin Brooks |
| 28. | Human-Centered Artificial General Intelligence Framework for Safe and Responsible Autonomous Systems | Dr. Matthew Robinson, Shruthi Narayanan, Dr. Rajesh Kumar |