Track 1: Intelligent Systems

Systems engineering methodologies for intelligent systems

Architecture of AI-enabled systems and systems of systems (SoS)

Model-based systems engineering (MBSE) for data-driven systems

Self-adaptive, autonomous, and resilient systems

Digital twins for complex systems

Verification, validation, and assurance of intelligent systems

System reliability, safety, and trustworthiness

Track 2: Cognitive Informatics & Human-Centered Systems

Cognitive architectures and computational cognition

Human-in-the-loop and human–AI collaboration

Explainable AI (XAI) for complex systems

Human factors and ergonomics in intelligent systems

Brain-inspired computing and neuromorphic systems

Cognitive digital twins

Adaptive interfaces and intelligent decision support

Track 3: Cyber-Physical Systems & System Intelligence

Data-driven modeling and control of CPS

AI for resilient and fault-tolerant systems

System security, privacy, and robustness

Edge–cloud intelligence for CPS

Sensor fusion and real-time system intelligence

Autonomous monitoring and predictive maintenance

Complex networked systems and infrastructure intelligence