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Data Science is relevant for all disciplines, but there is great variation in the application of methods and techniques. Get a taste for what data science is, and let yourself be inspired by how data science methods are put into practice in our Data Science Seminar!
Event details of Data Science Seminar: Engineering Digital Twins of Critical Infrastructures
Date
11 June 2024
Time
11:00 -12:00
Room
L2.06

About the seminar presentation

Engineering Digital Twins of Critical Infrastructures

Speaker: Dr. Victoria Degeler, Assistant Professor at the Informatics Institute, Faculty of Science 

Conventional digital twins (DT) are widely used to model and simulate the system’s state, especially in the industrial systems and critical infrastructures. But fundamental environment changes bring challenges for DT adaptation to new conditions, and result in a progressively decreasing correspondence of the DT to its physical counterpart.

In this talk, we will introduce the DiTEC system, a Digital Twin for Evolutionary Changes in Water Distribution Networks (WDN). This framework combines a number of novel techniques, including semantic rule learning, graph neural network-based state estimation, and adaptive model selection, to ensure that changes are adequately detected, processed and the system is updated to the new state. We will also discuss the challenges that the real critical infrastructures face in adopting the digital twins, and show how the DiTEC system is being tested on the data from the water distribution network of the Dutch Oosterbeek region.

Registration

Everyone from all disciplines is welcome to attend! The presentation will take place in-person only, and there will be an opportunity to ask questions and engage in lively discussion on the day. 

About the speaker

Victoria Degeler is an Assistant Professor at the Informatics Institute of the University of Amsterdam. She is a member of the Intelligent Data Engineering Lab, Complex-Cyber Infrastructures group and the Data Science Centre. Victoria's research is focused on reasoning and decision making systems for smart environments, activity recognition, digital twins, pervasive systems and context modeling and representation, with particular interest in sustainable applications such as energy and water management.