On 29 June 2026, Hub researchers convened the Digital Twins and Intelligent Edge Services Workshop as part of the IEEE International Conference on Mobile Data Management (MDM 2026), bringing together researchers from Australia, Europe, North America and industry to discuss emerging innovations in Digital Twins, distributed AI and intelligent cyber-physical systems.

Workshop Leadership

The workshop was organised by:

• Prem Prakash Jayaraman, Swinburne University of Technology
• Dimitrios Georgakopoulos, Swinburne University of Technology
• Federico Montori, University of Bologna, Italy
• Devki Nandan Jha, Newcastle University and University of Oxford, UK

The workshop was further supported by an international Technical Program Committee comprising experts from leading universities, research organisations and industry across Australia, Europe and North America.

Keynote Presentation

Iordanis Koutsopoulos, Professor, Department of Informatics, Athens University of Economics and Business, delivered the opening keynote:

Distributed Machine Learning and Network Resource Allocation for Intelligent Edge Services

The keynote explored the foundations of intelligent and trustworthy services operating at the network edge, where computing resources are constrained but demands for real-time AI continue to grow.

Topics included:

• Large Language Models (LLMs) running across distributed edge devices.
• Split Federated Learning architectures.
• Personalised federated learning.
• Explainable and trustworthy AI.
• Continual learning in networked environments.
• Intelligent resource allocation.
• Digital twins for wireless networking testbeds.
• Emerging opportunities in agentic AI.

The presentation highlighted the growing convergence of AI, networking and Digital Twins in enabling intelligent services across manufacturing, energy, healthcare, transportation and robotics.

Research Presentations

The workshop featured cutting-edge research from international contributors addressing key challenges in next-generation Digital Twin systems.

TwinLoop: Simulation-in-the-Loop Digital Twins for Online Multi-Agent Reinforcement Learning

Researchers presented approaches for combining simulation environments and Digital Twins to support adaptive decision-making using

multi-agent reinforcement learning.

Integrating Heterogeneous Digital Twins in Federated Ecosystems

This presentation explored methods for enabling interoperability between Digital Twins operating across multiple organisations and platforms, an important step towards scalable Digital Twin ecosystems.

IoT-Integrated Hybrid Machine Learning for Short-Term Raw Water Quality Forecasting

Researchers demonstrated how IoT technologies and hybrid machine learning models can improve forecasting accuracy and support operational decision-making in complex environments.

Key Themes

Several important themes emerged throughout the workshop:

• Digital Twins are evolving from simulation tools into intelligent operational platforms.
• AI and Digital Twins are becoming increasingly interconnected.
• Edge computing is critical for delivering low-latency intelligence.
• Federated architectures are enabling collaboration across distributed systems.
• Trustworthy, explainable and energy-efficient AI remains a key research priority.
• International collaboration is accelerating innovation in Digital Twin technologies.

Awards

International Collaboration

The workshop demonstrated the ARC Digital Manufacturing Hub’s growing international research leadership and its commitment to building global partnerships in Digital Twins and Artificial Intelligence.

By bringing together researchers from universities, research institutes and industry, the event created new opportunities for collaboration and knowledge exchange across disciplines and geographic boundaries.

Looking Forward

Digital Twins are rapidly becoming a foundation technology for the future of manufacturing, infrastructure, energy and smart systems. Workshops such as this help bridge the gap between fundamental research and practical deployment, fostering the collaborations needed to address increasingly complex industrial challenges.