Burgiede Liu is Granta Design Assistant Professor at the University of Cambridge. Prof Liu’s research interest includes data-driven mechanics; uncertainty quantification of materials; micro-mechanics of metals, function space learning method as well as quantum computing. He was a postdoc in Department of Mechanical and Process Engineering at ETH Zurich (2019) and a postdoctoral fellow in Mechanical and Civil Engineering at California Institute of Technology (2019-2021).

Prof Markovsky Ph.D. is in electrical engineering from the Katholieke Universiteit Leuven, Belgium. From 2006 to 2012 Prof Markovsky was a lecturer at the School of Electronics and Computer Science of the University of Southampton, U.K. and from 2012 to 2022 a research professor at the Vrije Universiteit Brussel, Belgium. His expertise is in system identification and data-driven control. In 2010, Prof Markovsky was awarded an ERC starting grant for a structured low-rank approximation approach to data-driven control. Current topics of interest are data-driven methods for nonlinear, time-varying, and distributed systems.

Fehmi Cirak is a Professor of Computational Mechanics and the head of CSMLab for computational mechanics and design in Cambridge. Prof. Cirak's research focuses on statistical finite elements for digital twinning, Bayesian inference, isogeometric analysis, and, more recently, quantum computing. He joined Cambridge in March 2006 after serving as a Senior Scientist at the Center for Advanced Computing Research at the California Institute of Technology for five years. He has a PhD in Computational Mechanics from the University of Stuttgart. Amongst others, Prof Cirak was previously a Postdoctoral Fellow in Aeronautics at the California Institute of Technology and a Visiting Professor at the University of Illinois Urbana-Champaign.

Elías Cueto is a Professor of continuum and computational mechanics, Universidad de Zaragoza. His research interests include the development of numerical methods for computational mechanics in its broadest sense. Prof Cueto has worked on finite element and meshless methods or model order reduction techniques, with applications on forming process simulation, real-time simulation, haptics, computational surgery, and, more recently, on data-intensive computational mechanics, thermodynamics-informed neural networks and augmented/mixed Reality.

Prof. Icíar Alfaro is a researcher and an associate professor with the University of Zaragoza, belonging to the Applied Mechanics and Bioengineering (AMB) research group. Throughout her career, she has followed several lines of research on numerical methods for solving complex engineering problems associated with solid mechanics. To successfully conduct these simulations, it has been necessary to employ innovative mathematical methods such as model order reduction techniques and physics-informed neural networks. These techniques are being used to perform real-time simulations, which are essential for the creation of digital and hybrid twins

David González is a Professor with the Department of Mechanical Engineering at the University of Zaragoza, where he teaches undergraduate and master's degree courses in the fields of Engineering and Architecture. Professor González holds a PhD in Applied Mathematics and his research interests focus on model reduction, real-time computational simulations and the study of data-driven computational mechanics using physics-informed artificial intelligence. He develops all this research within the Applied Mechanics and Bioengineering (AMB) group of the Aragon Engineering Research Institute of the University of Zaragoza.