Solving Time Alignment Issue of Multimodal Data for Accurate Prognostics with CNN-Transformer-LSTM Network. - Sagar Jose; Raymond Houé Ngouna; Khanh T. P. Nguyen; Kamal Medjaher (CoDIT, 2022)

Fault detection and diagnostics in the context of sparse multimodal data and expert knowledge assistance: Application to hydrogenerators. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (Comput. Ind., 2023)

Bridging expert knowledge and sensor measurements for machine fault quantification with large language models. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (AIM, 2024)

Advancing multimodal diagnostics: Integrating industrial textual data and domain knowledge with large language models. - Sagar Jose; Khanh T. P. Nguyen; Kamal Medjaher; Ryad Zemouri; Mélanie Lévesque; Antoine Tahan (Expert Syst. Appl., 2024)

Prognostics of complex machinery with sparse multilabel multimodal run-to-failure data: A graph neural network approach. - Sagar Jose; Ryad Zemouri; Khanh T. P. Nguyen; Kamal Medjaher; Mélanie Lévesque; Antoine Tahan (Adv. Eng. Informatics, 2025)