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Explores the Random Feature Method for solving PDEs using machine learning algorithms to approximate high-dimensional functions efficiently.

Explores Computational Molecular Design, emphasizing Mathematical Theory, High Performance Computing, and In Vivo Experiments.

Delves into unitary operators, self-adjoint properties, and spectral theorems in linear algebra.

Explores sampling algorithms for constrained systems, emphasizing the work of Benedict Leimkuhler from the University of Edinburgh.

Explores the periodic table of elements and Assyr Abdulle's significant contributions to numerical analysis.

Explores reciprocal space, Bragg condition, and X-ray diffraction in crystal lattices.