Digital twins are virtual representations of physical systems or processes that are used for modeling, simulation, and control. They enable a wide range of applications, from product design and optimization to predictive maintenance and smart cities. With the increasing availability of data and computational resources, digital twins are becoming more powerful and versatile, and are transforming many industries.

A digital twin must accurately represent the physical object, system, or process it is modeling. This requires gathering data from sensors, machines, and other sources in real-time and integrating it into a cohesive digital model. They have to monitor and analyze real-time data to provide insights and predict future behavior. This requires advanced analytics and machine learning algorithms that can process large volumes of data and identify patterns and anomalies. Finally, a digital twin should be designed to be interoperable with other systems and platforms. This allows data to be shared and integrated with other systems and tools, enabling more efficient workflows and better decision-making.

“Digital twins have the potential to enable safer and more efficient engineering systems, a greater understanding of the natural world around us, and better medical outcomes for all of us as individuals.”

– Karen Willcox

Topics and Objectives

This workshop aims to bring together researchers and practitioners working on digital twins to share their ideas, experiences, and challenges.


19 Oct. 2023 – The book of abstracts is available here.

21 Sep. 2023 – The final program of the workshop is available here.