Karim Cherifi is a researcher at the University of Wuppertal, Germany. His main research interests include model order reduction, data-driven modeling, Port Hamiltonian modeling, and modeling for digital twins. He obtained his Ph.D. in Control theory in 2019 from the Institute of Electrical and Electronic Engineering in Boumerdes (Algeria). Afterward, he was a postdoctoral researcher at the Max Planck Institute (MPI) for Dynamics of Complex Technical Systems in Magdeburg (Germany)and later at the Technical University of Berlin (Germany) where he was involved in the design of digital twins for Large Drive Applications within the project 'Elektrische Antriebe 2.0' as part of the Werner-von-Siemens Centre for Industry and Science in Berlin. Recently, he has been involved in multiple projects that implement digital twins in different domains: electrical machines, Building information modeling (BIM), and gas networks.

Bio Ion Victor Gosea is a senior scientist at the Max Planck Institute (MPI) for Dynamics of Complex Technical Systems in Magdeburg, Germany, in the Computational Methods in Systems and Control Theory Group led by Prof. Peter Benner. His main research interests include data-driven model reduction and reduced-order modeling of dynamical systems, system identification, rational approximation, and surrogate modeling for efficient and predictive digital twins. He obtained a Ph.D. in Electrical Engineering in 2017 at the Jacobs University Bremen, Germany. Afterward, he was a postdoctoral researcher at the MPI Magdeburg, specializing in frequency-domain data-driven methods. In the last years, he has been part of research endeavors and projects that aim at constructing digital twins for process, chemical, and electrochemical engineering applications, with an emphasis on developing green carbon processes in the context of the Power-to-X conversion framework.