by Dietmar Hömberg, WIAS, Berlin Dear colleagues, the ECMI blog is launching a new blog column entitled “Opinion” — a space for thoughtful reflection, personal
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Year: 2026
AI in Decision Making at NTNU
Snow Ploughing and AI: A Case Study in Decision-Making In late January, the AiD – Center for AI in Decision Making at Norwegian University of Science and Technology(NTNU)
Read moreTrondheim. Designing Fairer Futures: How CHAIN Uses Data to Reduce Global Health Inequality
By Terje Andreas Eikemo, Sara Martino and Andrea Riebler Around the world, education and health shape each other in powerful ways. People with more years
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Trondheim. The Geometry of Data – Why Machine Learning Needs Signatures
By Kurusch Ebrahimi-Fard and Fabian Harang Introduction Think of scribbling a digit on a digital tablet. You might write the number ’3’ slowly, with hesitations,
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Trondheim. The 2nd Ethiopian Study Group with Industry
By Dietmar Hömberg (NTNU/WIAS), Zerihun Kinfe Birhanu (Hawassa University) and Anne Kværnø (NTNU) The 2nd Ethiopian Study Group with Industry took place at Addis Ababa University of
Read moreTrondheim. Midnight Sun Summit in Mathematics and Engineering
This conference will take place on June 15-19, 2026in Narvik, Norway with the following objectives: Confirmed speakers of this summit include: For more information see https://uit.no/tavla/artikkel/881164/midnight_sun_summit_in_mathematics_and_engineering
Read moreTrondheim. Structure as a Guiding Principle for Computation
by Kurusch Ebrahimi-Fard, Hans Munthe-Kaas and Cordian Riener For much of the twentieth century, mathematics evolved along two largely separate trajectories.On one side stood abstraction:
Read moreTrondheim. Patterns from instability: How 1D soliton breaks dimensions to find 2D surfaces
By Wei Lian NTNU Norwegian University of Science and Technology In engineering, “instability” is often viewed as a failure—a bridge buckling in the wind or
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Trondheim. Learning Differential Equations via Chen–Fliess series
This article presents an accessible overview of how Chen–Fliess series can be combined with modern learning techniques to model and analyze nonlinear dynamical systems. The
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Trondheim. Affinization of Reduced Basis Methods
by Trond Kvamsdal NTNU Norwegian University of Science and Technology Background Reduced-basis methods (RBMs) offer an efficient framework for computing real-time approximations of parameterized PDEs.
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