Physics-informed machine learning for real-world decision making

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Building on the previous talk in the seminar series, this presentation goes further into some specific methods within physics-informed machine learning (PIML) and the broader field of scientific machine learning (SciML).

Over the past eight years, the Analytics and AI group in SINTEF Digital has built considerable competency in this area, both through our own method development and through collaboration with internationally leading groups in the field, which are also well represented in aiD.

In this talk I will present a selection of these methods, both ours and those of our collaborators, with pointers to and demonstrations of their application to decision-making tasks. Hopefully, this will highlight directions where further work and collaboration within aiD look especially promising.

Presented by: Sølve Eidnes, Senior Research Scientist, SINTEF