Open Invited Track
Data-Driven Model Reduction and System Identification: Bridging Learning, Approximation, and Dynamical Systems

Data-driven model reduction and system identification have traditionally developed as distinct yet closely related areas within dynamical systems and control. While system identification aims to construct accurate models from data, model reduction seeks to obtain low-complexity representations that retain the essential input-output behavior of dynamical systems. Recent advances increasingly blur this distinction, with data-driven techniques being used for model reduction and reduction principles being incorporated into identification methods. This open invited track aims to bring together researchers working at the intersection of these fields, with a particular focus on data-driven approaches to obtaining accurate, computationally efficient, and interpretable reduced- order models.

Contributions are invited on topics including, but not limited to:

• Data-driven model order reduction and identification of reduced-order models
• Joint or integrated system identification and model reduction
• Learning-based and machine-learning approaches to model reduction
• Structure-, physics-, and stability-preserving data-driven reduction
• Identification and reduction of nonlinear, large-scale, and complex dynamical systems
• Error bounds, performance guarantees, and uncertainty quantification for data-driven reduced models
• Data-efficient approaches to identifying low-complexity dynamical models
• Identification of reduced-order representations suitable for control, prediction, and real-time applications

The track is intended to encourage contributions from both the system identification and model reduction communities. In particular, it aims to highlight complementary methodologies, establish connections between existing approaches, and stimulate new research directions at their interface.

• Anyone is welcome to submit a paper in this open invited track!
• Write your paper in the IFAC coneference template (available here)
• Submit through PaperPlaza as "Open Invited Track paper" using code to be announced
• For any questions, you can contact the organizers.

• Mohammad Fahim Shakib, Department of Mechanical Engineering, Eindhoven University of Technology
• Alessio Moreschini, Department of Electrical and Electronic Engineering, University College London
• Pauline Kergus, CNRS researcher at Laboratory Plasma and Energy Conversion, Université de Toulouse