collaborators

8 papers

cs.LG2026

Data-driven discovery of roughness descriptors for surface characterization and intimate contact modeling of unidirectional composite tapes

Sebastian Rodriguez, Mikhael Tannous, Jad Mounayer +3

Unidirectional tapes surface roughness determines the evolution of the degree of intimate contact required for ensuring the thermoplastic molecular diffusion and the associated int…

math.NA2026

Rank Reduction AutoEncoders for Mechanical Design: Advancing Novel and Efficient Data-Driven Topology Optimization

Ismael Ben-Yelun, Mohammed El Fallaki Idrissi, Jad Mounayer +2

This work presents a data-driven framework for fast forward and inverse analysis in topology optimization (TO) by combining Rank Reduction Autoencoders (RRAEs) with neural latent-s…

cs.CE2025

Generative Parametric Design (GPD): A framework for real-time geometry generation and on-the-fly multiparametric approximation

Mohammed El Fallaki Idrissi, Jad Mounayer, Sebastian Rodriguez +2

This paper presents a novel paradigm in simulation-based engineering sciences by introducing a new framework called Generative Parametric Design (GPD). The GPD framework enables th…

cs.LG2025

RRAEDy: Adaptive Latent Linearization of Nonlinear Dynamical Systems

Jad Mounayer, Sebastian Rodriguez, Jerome Tomezyk +2

Most existing latent-space models for dynamical systems require fixing the latent dimension in advance, they rely on complex loss balancing to approximate linear dynamics, and they…

cs.LG2025

Application of Reduced-Order Models for Temporal Multiscale Representations in the Prediction of Dynamical Systems

Elias Al Ghazal, Jad Mounayer, Beatriz Moya +3

Modeling and predicting the dynamics of complex multiscale systems remains a significant challenge due to their inherent nonlinearities and sensitivity to initial conditions, as we…

cs.LG2025

Variational Rank Reduction Autoencoders

Jad Mounayer, Alicia Tierz, Jerome Tomezyk +2

Deterministic Rank Reduction Autoencoders (RRAEs) enforce by construction a regularization on the latent space by applying a truncated SVD. While this regularization makes Autoenco…