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The International Conference on Interdisciplinary Research in Artificial Intelligence & Machine Learning (ICIRAIML 2025) is a prestigious event aimed at bringing together researchers, practitioners, and industry experts to explore the integration and application of Artificial Intelligence (AI) and Machine Learning (ML) across various interdisciplinary fields.
ICIRAIML 2025 focuses on the convergence of AI and ML with other domains such as healthcare, economics, education, robotics, data science, environmental sciences, and social sciences. The conference aims to foster cross-disciplinary collaborations that can push the boundaries of AI and ML technologies while solving complex real-world problems.
Showcasing Interdisciplinary Applications: Highlighting the innovative ways AI and ML are being applied in various disciplines beyond traditional computer science, such as in healthcare, climate change, public policy, and social good.
Promoting Collaborative Research: Encouraging collaboration between AI/ML experts and professionals from diverse fields to create more holistic and effective solutions.
Exploring Emerging Trends: Delving into cutting-edge trends in AI and ML, such as reinforcement learning, explainable AI, federated learning, and their potential applications in solving global challenges.
Addressing Ethical, Legal, and Social Issues: Providing a forum to discuss the ethical implications of AI in interdisciplinary contexts, such as fairness, accountability, transparency, and the societal impact of intelligent systems.
AI and ML in Healthcare: Exploring AI-driven solutions for diagnostics, personalized medicine, medical imaging, and health monitoring.
AI and Education: How AI can revolutionize education through intelligent tutoring systems, personalized learning, and adaptive learning technologies.
AI in Environmental Sustainability: AI’s role in addressing climate change, renewable energy solutions, and environmental monitoring.
AI in Robotics and Automation: Exploring the integration of AI and ML in autonomous robots and systems for industries like manufacturing, agriculture, and logistics.
Data Science and Analytics: Leveraging AI and ML techniques in big data analytics, predictive modeling, and decision support systems.
Ethical AI: Examining the challenges of fairness, bias, transparency, and accountability in AI and ML systems across different sectors.
ICIRAIML 2025 provides an interdisciplinary platform for sharing innovative ideas, best practices, and solutions to foster the adoption and responsible use of AI and ML technologies in tackling complex, global challenges.
All Engineering Disciplines such as Computer Science Engineering, Civil Engineering, Communication Engineering, Electrical Engineering, Electronics & AI.
Augmented Reality & Virtual Reality, Cognitive Computing, Machine Learning Techniques, Deep Learning, Robotic Process Automation, Robotics, Internet of Things, Data Visualization, Natural Language Processing, Geometric Modelling, Programming for Problem-Solving, Python, Web Technology, Computer Communication Networks, Cryptography and Network Security, Data Structures, Database Management Systems, Distributed Computing, Information Security Analysis, Risk Analysis and etc.
| Sno | Papers Title | Author |
|---|---|---|
| 1. | AI Agents for Autonomous Task Execution Systems | Dr. Harish Narayanan, Keerthika Raj |
| 2. | Self-Reasoning Generative AI for Smart Decision Making | Naveena Prakash, Arjun Dev |
| 3. | OmniAI Models for Unified Text, Audio and Vision Processing | Dr. Lavanya Menon, Rohit Anand |
| 4. | AI-Powered Autonomous Digital Workforce Systems | Dr. Vishal Kumar, Sneha Paul |
| 5. | Hyper-Personalized Generative AI for Human Interaction | Dr. Meera Suresh, Ashwin Rao |
| 6. | Neural AI Operating Systems for Future Smart Devices | Karthikeyan R, Divya Menon |
| 7. | AI-to-AI Communication Frameworks for Autonomous Networks | Dr. Priyadharshini V, Mohammed Irfan |
| 8. | Autonomous Generative AI for Real-Time Problem Solving | Sandeep Iyer, Aarthi Krishnan |
| 9. | Cognitive AI Memory Systems for Human-Like Intelligence | Arun Prakash, Daniel Joseph |
| 10. | Spatial Intelligence AI for Mixed Reality Applications | Nivetha Balan, Pooja Raman |
| 11. | Self-Learning AI Ecosystems for Industry 5.0 | Raghul Krishna, Kiran Patel |
| 12. | Generative World Models for Autonomous Robotics | Janani Vel, Harini Das |
| 13. | Adaptive AI Reasoning Engines for Complex Analytics | Venkatesh Raman, Naveen George |
| 14. | AI-Powered Synthetic Human Behavior Modeling | Bhavana Nair, Rithika Sharma |
| 15. | Universal Multimodal AI for Intelligent Automation | Sanjana Devi, Vishnu Raj |
| 16. | AI-Driven Digital Brain Architectures for Smart Computing | Abhishek Kumar, Gayathri S |
| 17. | Autonomous AI Collaboration Using Swarm Intelligence | Keerthi Mohan, Suraj Menon |
| 18. | Predictive AI Agents for Next-Generation Cyber Defense | Dr. Ashok Prabhu, Jennifer Roy |
| 19. | Human-Aware AI Systems for Personalized Smart Services | Dr. Lakshmi Narayanan, Akshay Verma |
| 20. | NeuroAdaptive AI Frameworks for Cognitive Computing | Dr. Monisha Ravi, Shreya Paul |
| 21. | AI-Generated Simulation Systems for Smart Research | Dr. Deepak Sharma, Rohan Iyer |
| 22. | Self-Healing Intelligent Networks Using Autonomous AI. | Kavin Raj, Aishwarya Menon |
| 23. | AI-Powered Reality Fusion Systems for Virtual Environments. | Shalini Verghese, Aditya Krishna |
| 24. | Machine Reasoning Models for Autonomous Enterprise Intelligence | Dr. Pradeep Narayan, Keerthana Iyer |
| 25. | Intelligent AI Mesh Networks for Smart Infrastructure Dr. | |
| 26. | Generative AI Memory Architectures for Long-Term Learning | Anupama R, Nisha Kapoor |
| 27. | AI-Based Dynamic Knowledge Systems for Future Computing | Rajeshwari Devi, Siddharth Jain |
| 28. | Autonomous Multimodal Intelligence for Smart Ecosystems Dr. | Vinod Krishnan, Pavithra Nair |