Publications

Engineering Sciences

Failure prognostics under sensor degradation: A comparative study of online and batch Bayesian inference

Accurate failure prognostics and Remaining Useful Life (RUL) prediction are critical for prognostics and health management, but remain challenging when sensor degradation and stochastic dependencies are present. This study compares two Bayesian…

Hai-Canh Vu, Mitra Fouladirad, David Bassir, Thao Nguyen-Trang

Reliability Engineering and System Safety - 2027

Machine Learning

Unbiased Open World Regularization for Fair Self-Supervised Learning

Despite recent advances, self-supervised learning (SSL) models and Joint-Embedding Predictive Architectures (JEPAs) remain susceptible to learning spurious biases in the dataset. These techniques rely on regularization, which prevents representation…

Léo Nicollier, Marc Pic, Pablo Musé, Enric Meinhardt-Llopis, Gabriele Facciolo

Signal and Image processing

Detecting Moving Vehicles on Sentinel-2 Imagery Using Semi-Automatic Labeling From S2A/S2C Tandem Phase

During the commissioning phase of ESA’s Sentinel-2C, tandem images with Sentinel-2A were acquired with a delay of 30 seconds. We present a novel, automated method for labeling moving vehicles in Sentinel-2 images, leveraging the temporal offset…

Guillaume Buthmann, Florentin Poucin, Jérémy Anger

XXV ISPRS Congress 2026 - 2026

Machine Learning

Deep Generative Models for Complex Multi-component Industrial System Generation

This thesis studies deep generative modeling for constrained multi-component industrial design, using tire architecture generation as a representative case study. The core difficulty is not only to generate plausible components, but to produce…

Fouad Oubari

Machine Learning

Synthetic data for open medical research: what practitioners should know

Publicly releasing research data is at the core of the open science principles. In medical research, however, this practice conflicts with confidentiality requirements for the collected data. One appealing solution to this dilemma is to release…

Rémy Chapelle, Bruno Falissard, Mohammed Sedki

Engineering Sciences

MobileNetV3 for Pipeline Welding Defect Detection: A Computer Vision Approach on Noisy RGB Images

Weld defect detection plays a central role in pipeline inspection because it directly influences structural reliability and operational safety.Conventional manual inspection methods suffer from several limitations, including high labor demands,…

Ata Jahangir Moshayedi, Amir Sohail Khan, Ming Jun Zhang, Shuxin Yang, David Bassir

2026 International Conference on Artificial Intelligence in Energy and Infrastructure (AIEI 2026) - 2026

Machine Learning

Synthetic data for open medical research: current challenges and perspectives

Open science practices have many advocated benefits. At their core is the sharing of open data, especially open research data. Although their value is widely recognized, such data are rarely available in the healthcare domain. One of the main…

Rémy Chapelle, Bruno Falissard, Mohammed Sedki

Machine Learning

Parallel gradient boosting for flexible estimation of conditional distributions

Boosting is one of the most successful learning techniques for standard classification and regression tasks. Its extension to multi-output prediction problems has found an increasing number of applications in recent years. Among them is the…

Rémy Chapelle, Nicolas Vayatis, Bruno Falissard, Mohammed Sedki

Ocean, Atmosphere

Representation of meteotsunamis in km-scale regional simulations coupled at high frequency

Meteorological tsunamis, or meteotsunamis, are anomalous waves triggered by atmospheric disturbances such as thunderstorms, gravity waves, squalls, or cyclones. While meteotsunamis have been studied extensively in regions like the Mediterranean and…

Nefeli Makrygianni, Ségolène Berthou, David L A Flack, Cindy Lebeaupin Brossier, Jonathan Beuvier, Juan Manuel Castillo, Emiliano Renzi, Clare O'Neill, Daniel Peláez-Zapata, Frederic Dias, Huw Lewis, Diego Bruciaferri

Natural Hazards and Earth System Sciences - 2026

Engineering Sciences

Camera-Lidar Fusion for Road Detection: A Vision Transformer-Based Study

Autonomous vehicles require accurate road detection for safe navigation, and often fuse Camera and LiDAR sensors to enhance perception capabilities. While previous studies suggested that fusing Camera with LiDAR yields enhanced performance over…

Anthony Sigama, Baohua Guo, James Chakwizira, Tendayi Gondo, David Bassir, Sen Wang, Weifan Gu

Pattern Recognition - 2026