Research Interests
My work primarily focuses on the following topics :
- Metamodeling via Gaussian processes with complex data (dependent and functional data).
- Sensitivity analysis (Sobol indices, DGSM, ...).
- Bayesian optimization.
- Application to environmental models (water ressources, pesticide transports).
Recent Publications
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2025
Gradient-based Active Learning with Gaussian Processes for Global Sensitivity Analysis
Guerlain Lambert, CĂ©line Helbert, Claire Lauvernet.
Preprint (under review).
[Link] | [Repo]
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2024
Quantization-Based Latin Hypercube Sampling for Dependent Inputs With an Application to Sensitivity Analysis of Environmental Models
Guerlain Lambert, CĂ©line Helbert, Claire Lauvernet.
Applied Stochastic Models in Business and Industry.
[Link]
Awards
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2026
Best Oral presentation Award
RT-UQ / MASCOT-NUM 2026
ENSAI, Rennes, France
"Gradient-based Active Learning with Gaussian Processes for Global Sensivity Analysis".
[PDF]
-
2025
Best Poster presentation Award
RT-UQ / MASCOT-NUM 2025
Giens, France
Teaching
174h in total
@ Centrale Lyon
-
2026
Machine Learning and Applications — tutorials (8h)
M1 Centrale Lyon
-
2025
Probability-Statistics — tutorials (34h)
L3 Centrale Lyon
Statistics for Engineers — tutorials (12h)
M2 Centrale Lyon
-
2024
Probability-Statistics — tutorials (40h)
L3 Centrale Lyon
Statistics for Engineers — tutorials (16h)
M2 Centrale Lyon
Machine Learning and Applications — tutorials (8h)
M1 Centrale Lyon
-
2023
Probability-Statistics — tutorials (16h)
L3 Centrale Lyon
Numerical Analysis — tutorials (30h)
L3 Centrale Lyon
Applied Analysis — tutorials (4h)
L3 Centrale Lyon
Machine Learning and Applications — tutorials (6h)
M1 Centrale Lyon
Curriculum Vitae
For more details about my academic background, please see my full CV (version : April, 7 2026):
Curriculum Vitae
