Join IEEE

IEEE SSCI 2027

2027 IEEE Symposium on CI in Engineering / Cyber Physical Systems (IEEE CIES)

IEEE CIES focuses on computational intelligence for engineering and cyber-physical systems.

Aerial view of Gold Coast high-rises and coastline at dusk

Symposium Chairs

  • A/Prof. Hai Dong, RMIT
  • Prof. Yi Mei, Victoria University of Wellington

Technical Co-Chairs

  • Pengcheng Zhang, Hohai University, China
  • Xiaoyu Shaw Xia, RMIT University, Australia
  • Yahui Jia, South China University of Technology, China
  • Meng Yuan, Victoria University of Wellington, New Zealand

Publicity Co-Chairs

  • Handing Wang, Xidian University, China
  • Hemant Singh, University of New South Wales, Australia
  • Terry Yang, RMIT University, Australia
  • Yu Zhang, Macquarie University, Australia
  • Tiehua Zhang, Tongji University, China
  • Yue Xie, Loughborough University, United Kingdom
  • Huiying Jin, Nanjing University of Posts and Telecommunications, China
  • Tong Guo, Nanyang Technological University, Singapore

Scope

In an era marked by rapid technological advancements, Computational Intelligence (CI) continues to evolve the widespread computational paradigms of Artificial Intelligence (AI) to match these needs. The intersection of computational intelligence (CI) with engineering and cyber-physical systems (CPS) has thus emerged as a critical area of research and innovation.

This symposium aims to serve as a leading forum for researchers, technologists, and industry experts to exchange ideas, share advancements, and shape the future of this interdisciplinary field. Indeed, the fusion of CI with engineering and CPS is revolutionizing the way we interact with our physical world, making systems smarter, more efficient, and more adaptive. The application of CI and machine learning (ML) in these domains is not just enhancing existing technologies but is also paving the way for novel paradigms in design, operation, and services.

This symposium is organized into two distinct yet interconnected thematic axes: 'Computational Intelligence (CI) for Technologies/Systems' and 'Systems/Technologies for Computational Intelligence'. The first axis explores how computational intelligence drives and enhances various technological domains and systems, while the second focuses on the technological foundations and advancements that enable and enhance computational intelligence. By exploring these two thematic axes this symposium aims to bring together researchers, practitioners, and industry experts to share insights, experiences, and advancements in the field of Computational Intelligence for Engineering and Cyber-Physical Systems. Through these two thematic axes, the event will foster discussions that cross the traditional boundaries of technology and computational intelligence, paving the way for innovative solutions and future collaborations.

We are seeking contributions that address either theoretical developments or practical applications in these fields. Further, the Symposium aims to promote collaboration and the sharing of knowledge to develop the field of CI in Engineering/Cyber Physical Systems.

Topics of Interest

Topics of interest include, but are not limited to:

Artificial Intelligence for CPS

  • Explainable AI for Engineering Systems
  • Trustworthy AI and Responsible AI
  • Foundation Models for Engineering Applications
  • Generative AI for Design and Optimization
  • Agentic AI Systems
  • Multi-Agent Systems and Swarm Intelligence
  • Human-AI Collaboration
  • AI for Scientific Discovery

Cyber-Physical Systems

  • Intelligent Cyber-Physical Systems
  • CPS Security and Resilience
  • Autonomous Cyber-Physical Systems
  • Distributed CPS Architectures
  • Edge AI for CPS
  • Real-Time CPS Analytics
  • Self-Adaptive and Self-Healing CPS
  • Safety-Critical CPS

Industry 5.0 and Smart Manufacturing

  • Industry 5.0 Technologies
  • Human-Centric Manufacturing
  • Cognitive Manufacturing Systems
  • Smart Factories
  • Autonomous Production Systems
  • AI-Driven Process Optimization
  • Predictive Maintenance
  • Sustainable Manufacturing

Digital Twins and Simulation Intelligence

  • AI-Enhanced Digital Twins
  • Digital Twin Federations
  • Physics-Informed Digital Twins
  • Hybrid Digital Twins
  • Simulation-Based Optimization
  • Real-Time Digital Twin Synchronization
  • Digital Engineering

Infrastructure and Smart Cities

  • Smart Infrastructure Monitoring
  • Intelligent Transportation Systems
  • Smart Buildings and Smart Cities
  • Critical Infrastructure Protection
  • Urban Digital Twins
  • Infrastructure Resilience and Recovery
  • Sustainable Infrastructure Systems

Energy and Sustainability

  • Smart Grids and Energy Systems
  • Renewable Energy Optimization
  • Intelligent Energy Management
  • Carbon-Aware Computing
  • Sustainable AI and Green Computing
  • Energy-Aware CPS

Autonomous Systems and Robotics

  • Autonomous Vehicles
  • Autonomous Drones and UAV Systems
  • Collaborative Robotics (Cobots)
  • Multi-Robot Coordination
  • Human-Robot Interaction
  • Robot Learning and Adaptation
  • AI for Industrial Robotics

Security, Privacy, and Trust

  • AI for Cybersecurity
  • Security of Industrial Control Systems
  • Privacy-Preserving Intelligence
  • Federated Learning for CPS
  • Adversarial Machine Learning
  • Blockchain for CPS and IoT
  • Trust Management in Distributed Systems

Data-Driven Engineering

  • Engineering Knowledge Graphs
  • Industrial Data Analytics
  • Industrial Large Language Models
  • Time-Series Intelligence
  • Graph Machine Learning for Engineering Systems
  • Uncertainty Quantification
  • Physics-Informed Machine Learning

Emerging Topics

  • Quantum Computing for Engineering Optimization
  • Neuromorphic Computing
  • Edge-Cloud Continuum Intelligence
  • Digital Ecosystems
  • Intelligent Space Systems
  • Smart Agriculture and Precision Farming
  • AI for Climate and Environmental Systems
  • Intelligent Healthcare Engineering
  • Metaverse and Industrial Metaverse
  • Decentralized Autonomous Systems