I am a Tenured Civil Servant in Computer Science at the UMI 209 UMMISCO (International Modeling and Simulation Unit) at Paris Sorbonne University. My work on high-dimensional multidisciplinary design optimization for eco-design was awarded the 2024 Best PhD Thesis Prize (Fondation ISAE-SUPAERO / French Ministry of Research), the 2025 National Open Science PhD Award from the French Ministry of Research, the 2026 International Artificial Intelligence PhD Award from the the Francophone Research Network on Artificial Intelligence (RéFIA) and the the 2026 Abertis France PhD Award, ranked 2nd in Sustainable Mobility from the Ecole Nationale des Ponts et Chaussées. I also received 4 additional Technical Best paper Awards at various conférences (AIAA*2, IDA, JFSMA) between 2022 and 2026. My research focuses on surrogate modeling, frugal AI, and explainable machine learning for computationally expensive simulations. I develop lightweight statistical and machine-learning models (including Gaussian processes and ensemble methods) to approximate complex systems, quantify uncertainty, and support decision-making. My work connects Explainable AI, Bayesian optimization, and scientific machine learning, with applications ranging from sustainable transport design to agent-based socio-environmental modeling.