Publications

Engineering Sciences

A Novel Meta-Learning-Based Spatio-Temporal Modeling Approach for Thermal Error Prediction of Multiple Machine Tools with Few Labeled Data

Chaochao Qiu, Qiongke Liang, Ling Yin, David Bassir, Lijuan Zhang, Weicheng Lin

SSRN Electronic Journal - 2025

Engineering Sciences

Local bond behavior of partially encased composite steel and recycled concrete structural members

Bond failure at the steel–concrete interface is a leading cause of performance degradation in partially encased composite (PEC) structural members. Compared with other composite structures, PEC structural members are more susceptible to bond failure…

Fubo Cao, Jialong Song, Chenxia Wang, Tian Su, Hexin Zhang, Shenghua Wu, David Bassir, Demin Jiang, Zhenjun He, Xiaoruan Song

Construction and Building Materials - 2025

Engineering Sciences

Fmoe-Yolo: A Fourier-Mixture of Experts Yolo Framework for Multi-Class Concrete Crack Segmentation with Visual Interpretability

Haochen Chang, David Bassir, Anicet Barrios, Gongfa Chen

SSRN Electronic Journal - 2025

Engineering Sciences

An Experimental Study of the Vortical Structures in Supersonic Steam Jet Impinged on to the Wall

Afrasyab Khan, Khairuddin Sanaullah, Pavel Alexandrovich Taranenko, Vladimir Vladimirovich Sinitsin, David Bassir, Ajmal Shah, Zafar Ahmed, Andrew Ragai Henry Rigit

Proceedings of The 7th International Conference on Mechanical, System and Control Engineering - 2025

Engineering Sciences

Smart monitoring of the expansion state of boiler water walls in coal-fired power plants using a digital twin model

This article presents an approach for monitoring the expansion state of water walls in coal-fired power plants using a digital twin (DT) model. The monitored boiler belongs to a 1000 MW ultrasupercritical power generating unit; it has been in…

L Luo, W Wang, Z Lei, S Bao, David Bassir, G Chen

Proceedings of the Estonian Academy of Sciences - 2025

Metric Geometry

Riemannian Metric Learning: Closer to You than You Imagine

Riemannian metric learning is an emerging field in machine learning, unlocking new ways to encode complex data structures beyond traditional distance metric learning. While classical approaches rely on global distances in Euclidean space, they often…

Samuel Gruffaz, Josua Sassen

Machine Learning

Personalized Convolutional Dictionary Learning of Physiological Time Series

Human physiological signals tend to exhibit both global and local structures: the former are shared across a population, while the latter reflect inter-individual variability. For instance, kinetic measurements of the gait cycle during locomotion…

Axel Roques, Samuel Gruffaz, Kyurae Kim, Alain O Durmus, Laurent Oudre

AISTATS 2025 - 2025

Methodology

Fusion of heterogeneous data for robust degradation prognostics

Assessing the degradation state of an industrial asset first requires evaluating its current condition and then to project the forecast model trajectory to a predefined prognostic threshold, thereby estimating its remaining useful life (RUL)…

Edgar Jaber, Emmanuel Remy, Vincent Chabridon, Mathilde Mougeot, Didier Lucor

Numerical Analysis

Selling's decomposition and the anisotropic wave equation

The design of efficient numerical schemes for anisotropic partial differential equations, featuring privileged directions in general not aligned with the coordinate axes, raises challenging discretization problems which can often be addressed with…

Malik Haloui, Ludovic Métivier, Jean-Marie Mirebeau

Analysis of PDEs

Towards an Optimal Collocation Point Strategy for PINNs

Chourouk El Hassanieh, Mathilde Mougeot

Le Consortium Recherche & Industrie CIROQUO - 2025