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    \textbf{Organizers:} Alice Smith$^{1}$, Bob Johnson$^{2}$, and Carol Lee$^{3}$ \\[0.3em]
    $^{1}$Department of Civil and Environmental Engineering, University A, Country \\
    $^{2}$Institute of Applied Mathematics, University B, Country \\
    $^{3}$Department of Mechanical Engineering, University C, Country \\
    \texttt{alice.smith@univ-a.edu, bob.johnson@univ-b.edu, carol.lee@univ-c.edu}
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\textbf{Keywords:} Key1, Key2, Key3, Key4, Key5

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\section*{Summary}

The proposed minisymposium aims to unite researchers who believe that the perfect model lies somewhere between physics, data, and a healthy amount of regularization. As machine learning continues to promise that “no PDE shall remain unsolved,” and reduced-order modelling assures us that “fewer modes are always better,” it seems timely to bring everyone together to compare notes—and error estimates.

Topics include the assimilation of data that stubbornly refuse to fit the model, the creation of surrogates that perform beautifully until extrapolated, and the development of digital twins that sometimes behave like distant cousins. Contributions combining elegant mathematics with slightly desperate parameter tuning are particularly encouraged.

The minisymposium will also feature discussions on reproducibility, interpretability, and the eternal question: *should we trust the neural network or the Navier–Stokes equations today?* We expect lively debates, gentle disagreements about stability conditions, and at least one slide showing a mysterious loss function that “just works.”

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\section*{References}

\begin{enumerate}
    \item Von Neumann, J. (1947). \textit{Various techniques used in connection with random digits.} Notes by Ulam, because Monte Carlo needed a name cooler than “guessing smartly.”  
    \item Trefethen, L.N. (1992). \textit{Spectral methods in MATLAB — and why they don’t like discontinuities.} SIAM Review, 34(3), 387–391, after three weeks of debugging.  
    \item Anonymous Reviewer \#2 (2024). \textit{On why your mesh is still too coarse.} Journal of Unsolicited Numerical Advice, 1(1), 1–$\infty$.  
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    \small
    \textit{GIMC SIMAI young 2026, Pisa, Italy}
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