Call for Paper

AIC-2027 welcomes original research papers, case studies, innovative applications, and industry-driven contributions from researchers, academicians, practitioners, policymakers, and technology leaders. The conference aims to provide a multidisciplinary platform for discussing recent advances, challenges, and future directions in Artificial Intelligence Computing. It seeks to foster collaboration among experts working at the intersection of intelligent computing, data-driven technologies, computational intelligence, and emerging digital ecosystems.

AIC-2027 invites original work from the following list of topics (but is not limited to):

1: Foundations of Artificial Intelligence and Computing

• Artificial Intelligence theories and models
• Computational Intelligence and Soft Computing
• Knowledge Representation and Reasoning
• Cognitive Computing Systems
• Intelligent Agents and Autonomous Systems
• Search, Planning, and Optimization Algorithms
• Symbolic and Sub-symbolic AI
• AI Architectures and Frameworks
• Explainable and Interpretable AI Models
• Hybrid Intelligence Systems

2: Machine Learning and Deep Learning

• Supervised, Unsupervised, and Semi-supervised Learning
• Reinforcement Learning and Adaptive Systems
• Deep Neural Networks and Architectures
• Transfer Learning and Meta-Learning
• Federated and Distributed Learning
• Generative AI and Foundation Models
• Self-supervised Learning Approaches
• Neural Architecture Search
• Continual and Lifelong Learning
• AI Model Optimization and Compression

3: Data Science and Intelligent Analytics

• Big Data Analytics and Mining
• Predictive and Prescriptive Analytics
• Data Visualization and Decision Support Systems
• Intelligent Business Analytics
• Time-Series Forecasting and Analysis
• Knowledge Discovery in Databases
• Data Engineering and Processing Frameworks
• Graph Analytics and Network Science
• Data Quality and Management
• AI-Powered Data Governance

4: Natural Language Processing and Generative AI

• Large Language Models (LLMs)
• Conversational AI and Intelligent Chatbots
• Text Mining and Information Retrieval
• Machine Translation Systems
• Sentiment and Opinion Mining
• Speech Recognition and Synthesis
• Question Answering Systems
• Multilingual and Cross-lingual AI
• Prompt Engineering and AI Alignment
• Generative AI Applications and Evaluation

5: Computer Vision and Multimedia Computing

• Image and Video Processing
• Object Detection and Recognition
• Facial Recognition and Biometrics
• Medical Image Analysis
• Vision-Language Models
• Augmented and Virtual Reality Systems
• Intelligent Surveillance Systems
• Remote Sensing and Geospatial Analytics
• Multimedia Retrieval Systems
• Visual Analytics and Pattern Recognition

6: AI Computing for Healthcare and Life Sciences

• AI-Assisted Disease Diagnosis
• Clinical Decision Support Systems
• Precision and Personalized Medicine
• Medical Data Analytics
• Wearable Health Monitoring Systems
• Drug Discovery and Bioinformatics
• AI in Public Health Management
• Healthcare Robotics and Automation
• Mental Health Analytics
• Ethical and Responsible Medical AI

7: Intelligent Systems, Robotics and Automation

• Autonomous Robots and Vehicles
• Human-Robot Interaction
• Swarm Intelligence and Multi-Agent Systems
• Industrial Automation and Smart Manufacturing
• Robotic Process Automation (RPA)
• Intelligent Control Systems
• AI for Industrial Internet of Things (IIoT)
• Smart Sensors and Embedded Intelligence
• Adaptive and Autonomous Computing Systems
• Edge Intelligence for Robotics

8: High-Performance, Cloud and Edge AI Computing

• Parallel and Distributed Computing for AI
• Cloud-Based AI Platforms
• Edge and Fog Computing
• AI Acceleration Hardware and Architectures
• GPU, TPU and Specialized AI Processors
• Resource-Efficient AI Computing
• Green and Sustainable AI Computing
• Serverless AI Infrastructure
• Scalable Computing Frameworks
• AI for Next-Generation Computing Systems

9: Cybersecurity, Privacy and Trustworthy AI

• AI for Cybersecurity and Threat Detection
• Privacy-Preserving Machine Learning
• Secure AI Systems and Applications
• Adversarial Machine Learning
• Trustworthy and Responsible AI
• AI Governance and Compliance
• Fairness, Accountability and Transparency
• Blockchain and AI Integration
• Digital Identity and Authentication Systems
• Secure Data Sharing Frameworks

10: Emerging Trends and Future Directions in AI Computing

• Quantum AI and Quantum Machine Learning
• Neuromorphic and Brain-Inspired Computing
• Digital Twins and Intelligent Simulation
• AI for Smart Cities and Sustainable Development
• AI in Climate and Environmental Applications
• Human-Centered AI Systems
• AI for Education and Learning Technologies
• Metaverse and Immersive Intelligent Environments
• AI for Social Good and Public Policy
• Future Computing Paradigms and Innovations