ERC Advanced Research Project
Data-Driven Modeling in Dynamic Networks
Welcome to SYSDYNET
Modern demands on engineering systems require the ability to model, monitor, optimize and control dynamic systems that are spatially interconnected as networks of systems. Examples can be found e.g. in distributed (smart) power systems, industrial production processes, and transportation networks. In this research project we develop methods and tools for the mathematical modelling of interconnected dynamic systems on the basis of measured data. To this end we base our research on contributions from the fields of system identification, machine learning, data analytics and statistical modelling, to come up with effective and scalable tools for data-driven modelling in dynamic networks. Potential domains of application extend beyond the engineering domain, including biomedical science and econometrics. Data-driven modeling tools for dynamic networks are expected to become essential tools in the high-level future ICT environment for monitoring, control and optimization of cyber-physical systems of systems, as well as in many other domains of science.
Prof. Paul Van den Hof,
ERC Advanced Research Grant holder
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A prototype dynamic network in the module framework
Recent News items
3-day PhD Course on Dynamic Network Identification
From Wednesday 4 – Friday 6 March 2026, a three-day PhD course on Dynamic Network Identification will be…
Rudolf Kalman Award 2024
Paul Van den Hof receives the Rudolf Kalman Award 2024 out of the hands of Prof. Jozsef Bokor,…
PhD thesis of Lizan Kivits on Physical Network Identification
On February 22, 2024, Lizan Kivits successfully defended her PhD thesis entitled: “Modelling and identification of physical linear…
