Stochastic model reduction for polynomial chaos expansion of acoustic waves using proper orthogonal decomposition. - Nabil El Moçayd; M. Shadi Mohamed; Driss Ouazar; Mohammed Seaïd (Reliab. Eng. Syst. Saf., 2020)

A surrogate model for efficient quantification of uncertainties in multilayer shallow water flows. - Alia Al-Ghosoun; Nabil El Moçayd; Mohammed Seaïd (Environ. Model. Softw., 2021)

Non-intrusive polynomial chaos methods for uncertainty quantification in wave problems at high frequencies. - Nabil El Moçayd; M. Shadi Mohamed; Mohammed Seaïd (J. Comput. Sci., 2021)

Data-driven polynomial chaos expansions for characterization of complex fluid rheology: Case study of phosphate slurry. - Nabil El Moçayd; Mohammed Seaïd (Reliab. Eng. Syst. Saf., 2021)

Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models. - Nabil El Moçayd; Youssef Belhamadia; Mohammed Seaïd (Comput. Methods Programs Biomed., 2024)

Data-driven hybrid modelling of waves at mid-frequencies range: Application to forward and inverse Helmholtz problems. - Nabil El Moçayd; M. Shadi Mohamed; Mohammed Seaïd (J. Comput. Sci., 2024)

A Bernstein-Bézier finite element method with perfectly matched layer for refraction and diffraction of waves in coastal regions. - Saloua El Marri; Abdellah El Kacimi; Nabil El Moçayd; Mohammed Seaïd (J. Comput. Sci., 2025)