Smart mobility solutions are increasingly driven by AI and continuous interaction with the physical world. From autonomous vehicles and industrial transport, and logistics, to military drones and earth observation systems, next-generation solutions require tight integration between Digital Twins, Physical (dependency-aware) AI, and related platforms that combine these in a highly productive and cost-effective manner. Digital Twins digitally represent complex physical entities, such as sophisticated machines, supplies, products and people involved. Physical AI enables learning and intelligence grounded in physical dynamics, spatial context, and real-world constraints. Together, they form a closed-loop cyber-physical paradigm that critically depends on robust, scalable, and trustworthy data management to support the emerging needs of mission-critical applications in areas such as smart factories, cities, transportation and health.

The workshop aims to bring together researchers and practitioners from data management, artificial intelligence, robotics, and cyber-physical systems to explore foundations, systems, and applications towards smart mobility systems. 

Topics of interest include, but are not limited to:

• Digital twins for smart mobility systems 

• Physical dependencies aware AI models 

• Platforms for physical AI and Digital Twin-based  systems for smart mobility solutions

• Real-time/closed-loop decision support

• Multimodal data management (sensor, trajectory, spatial-temporal, V2X, video)

• Urban- and infrastructure-scale for physical AI and Digital Twin-based  solutions

• Data-driven modelling, simulation, and co-simulation in Digital Twins

• Digital Twin discovery, integration, and coordination for smart mobility

• Scalability, latency, and performance challenges in Digital Twins and Physical AI

• Physical AI for perception, prediction, planning, and control

• Agentic and multi-agent AI for smart mobility systems

• Explainable, robust, and trustworthy AI for safety-critical mobility

• Privacy, security, and governance of mobility and industrial data

• Open datasets and experimental platforms

• Industrial deployments and case studies (e.g., autonomous vehicles, smart transportation, logistics, robotics, manufacturing)

Submission Guidelines

Workshop papers should be at most 6 pages in the IEEE template (available here: https://www.ieee.org/conferences/publishing/templates.html). It will not be possible to purchase additional pages for the camera-ready version. The publication chairs will make details about camera-ready versions available in due time on the conference website.

All papers must be submitted using EasyChair at the following link: https://easychair.org/conferences/?conf=digitwinsai2026

Committees

Organizing Committee

• Prem Prakash Jayaraman
• Federico Montori
• Dimitrios Georgakopoulos
• Devki Nandan Jha

Technical Program committee

• Luigi Atzori, University of Cagliari, Italy

• Paolo Bellavista, University of Bologna, Italy

• Matthias Hirth, Technische Universit¨at Ilmenau, Germany

• Yingying Chen, Stevens Institute of Technology, USA

• Dong Zhao, Beijing University of Post and Telecommunications, China

• Jerker Delsing, Lule˚a University of Technology, Sweden

• Burak Kantarci, University of Ottawa, Canada

• Marco Levorato, University of California at Irvine, USA

• Bin Guo, Northwestern Polytechnical University, China

• Rong Zheng, McMaster University, Canada

• Rajiv Ranjan, Newcastle University, UK

• Omer Rana, Cardiff University, UK.

• Aditya Indoori, Amazon, USA

• Martin Higgins, Concordia University of Edmonton, Canada

• Abhik Banerjee, Swinburne University of Technology

• Kewen Liao, Deakin University

• Shaleeza Sohail, The University of Newcastle, Sydney

• Chiara Renso, CNR, Italy

• Luca Bedogni, University of Modena and Reggio Emilia, Italy

• Christine Bassem, Wellesley College, USA

• Rafaella Gravina, University of Calabria, Italy

Contact

All questions about submissions should be emailed to dev.jha@ncl.ac.uk.