Track 1: Artificial Intelligence & Computational Intelligence

• Machine learning
• Deep learning
• Generative Artificial Intelligence
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• Explainable Artificial Intelligence (XAI)
• Human-Centered Artificial Intelligence
• Federated Learning
• Robotics and Intelligent Systems
• Evolutionary Computing
• Bio-inspired Computing

Track 2: IoT and Sensor Networks

• Wireless Sensor Networks
• Internet of Things (IoT) Architectures and Protocols
• Edge–Cloud Integration for IoT
• Energy-Efficient IoT Systems
• Industrial Internet of Things (IIoT)
• Smart Cities and Smart Infrastructure
• IoT Security and Privacy
• Sensor Fusion Techniques
• Blockchain-Enabled IoT
• Smart Agriculture and Precision Farming

Track 3: Cybersecurity and Privacy in Intelligent Systems

• Secure System Architectures
• Cryptography and Cryptographic Protocols
• Privacy-Preserving Artificial Intelligence
• Intrusion Detection and Prevention Systems
• Cyber Forensics and Incident Response
• Blockchain and Distributed Ledger Security
• Identity and Access Management
• Cloud and Virtualization Security
• Cyber Resilience and Risk Management
• Ethical, Legal, and Regulatory Aspects of Cybersecurity

Track 4: Electronics and Embedded Systems for Smart Technologies

• Low-Power and Energy-Efficient Electronics
• VLSI and System-on-Chip (SoC) Design
• Embedded Systems Design
• Hardware–Software Co-Design
• FPGA-Based Systems
• Micro-Electro-Mechanical Systems (MEMS)
• Power Electronics and Drives
• Wearable Electronics and Biomedical Devices
• Reliable and Fault-Tolerant Hardware Design

Track 5: Sustainable Computing and Emerging Paradigms

• Green and Energy-Efficient Computing
• Sustainable Communication Networks
• Energy-Efficient Data Centers
• Carbon-Aware Cloud Computing
• Quantum Computing
• Neuromorphic Computing
• Sustainable Artificial Intelligence
• Edge Computing for Sustainability
• Computing Lifecycle Assessment and Circular Economy

Track 6: Data Science, Cloud, and Edge Computing

• Big Data Analytics
• Cloud-Native Systems and Microservices
• Edge and Fog Computing
• Data Mining and Knowledge Discovery
• Scalable Machine Learning Systems
• Real-Time and Stream Processing
• Distributed Storage Systems
• AI-Driven Cloud Resource Optimization
• Hybrid and Multi-Cloud Architectures