Manifest

I develop certified digital twin methodologies for complex engineering systems, with a focus on uncertainty quantification, surrogate model reliability, and hybrid scientific machine learning.

Talks

03/2026 SMM Group Seminar, ETH Zürich, Switzerland - slides, video
10/2025 UQSay#89, online - slides
08/2025 Mathematical Foundations of Digital Twins, CIRM, Marseille, France - slides
07/2025 UNCECOMP 2025, Rhodos, Greece - slides
06/2025 INI institute, Cambridge, U.K - slides, video
04/2025 SAMO 2025, Grenoble, France - poster
02/2025 DTE&AICOMAS 2025, Paris, France - slides
09/2024 ETICS 2024, Saissac, France - slides (in French)
02/2024 SIAM Conference on Uncertainty Quantification 2024, Trieste, Italy - slides
12/2023 PhD day, EDF Lab Chatou - slides
10/2023 ETICS 2023, Lège Cap-Ferret - slides
09/2023 CJC-MA 2023, CentraleSupélec - poster
04/2023 MASCOT-NUM 2023, Le Croisic, France - poster
11/2022 Modelling research group seminar, Centre Borelli, ENS Paris-Saclay
10/2022 PSPP seminar, EDF Lab Chatou

Publications

Jaber, E. et al., Digital twin-based hybrid framework for steam generator clogging prognostics, Manuscript in preparation.
Jaber, E. et al., Fusion of heterogeneous data for robust degradation prognostics, Reliability Engineering & System Safety, 2026, 112435, 10.1016/j.ress.2026.112435
Jaber, E., Blot, V. et al., Conformal approach to Gaussian process surrogate evaluation with marginal coverage guarantees, Journal of Machine Learning for Modeling and Computing, 6(3), 2025. 10.1615/JMachLearnModelComput.2025054687
Jaber, E. et al., Sensitivity analyses of a multi-physics long-term clogging model for steam generators, International Journal of Uncertainty Quantification, 15(1), 2025. 10.1615/Int.J.UncertaintyQuantification.2024051489

Misc

PhD thesis: Hybrid prognostics using simulation codes and statistical models - Application to the study of steam generators clogging.

Msc thesis (in French): Removable singularities for bounded vector field solutions of certain first order PDEs.