Paul Saves

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Institut de recherche en informatique de Toulouse (IRIT)

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Présentation

Doctor in AI for Climate -- Recipient of 2022 & 2024 AIAA best papers (MDO TC), 2026 IDA Frontier Prize (Springer), 2024 best thesis (Fondation ISAE-SUPAERO), 2025 Ministry of Research open science (Ouvrir la science), 2026 Artificial Intelligence (RéFIA) and 2026 Sustainable Mobility (Abertis France) best dissertation award, and 2026 Best AI Paper (JFMSA/AFIA). https://paul-saves.github.io/research/

My research aims at developing a unified framework for the analysis and decision-oriented exploration of complex simulation models using Frugal and Explainable AI. I combine surrogate modeling, active learning, and interpretable machine learning to transform computationally expensive black-box simulations into transparent tools for decision-making under uncertainty.

This work follows an iterative co-design paradigm, where modeling and interpretation are developed jointly with domain experts to enable actionable insights. I apply this framework to two main classes of systems: multidisciplinary engineering design (with an emphasis on sustainable aeronautics) and agent-based simulations for environmental and climate risk assessment.

Publications

	Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design Paul Saves , Edward Hallé-Hannan , Jasper Bussemaker , Youssef Diouane , Nathalie Bartoli Structural and Multidisciplinary Optimization, 2026, ⟨10.1007/s00158-026-04249-2⟩ Article dans une revue hal-05134630v2
	Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making Pramudita Satria Palar , Paul Saves , Muhammad Daffa Robani , Nicolas Verstaevel , Moncef Garouani et al. Archives of Computational Methods in Engineering, 2026, 2026 (2026), pp.1-65. ⟨10.1007/s11831-026-10600-z⟩ Article dans une revue hal-05371637v2
	Global Sensitivity Analysis for Engineering Design Based on Individual Conditional Expectations Pramudita Satria Palar , Paul Saves , Rommel Regis , Koji Shimoyama , Shigeru Obayashi et al. Aerospace Science and Technology, 2026, pp.112091. ⟨10.1016/j.ast.2026.112091⟩ Article dans une revue hal-05413969v3
	A distance for mixed-variable and hierarchical domains with meta variables Edward Hallé-Hannan , Charles Audet , Youssef Diouane , Sébastien Le Digabel , Paul Saves Neurocomputing, 2025, pp.131208. ⟨10.1016/j.neucom.2025.131208⟩ Article dans une revue hal-05014820v1
	System Architecture Optimization Strategies: Dealing with Expensive Hierarchical Problems Jasper H Bussemaker , Paul Saves , Nathalie Bartoli , Thierry Lefebvre , Rémi Lafage Journal of Global Optimization, 2024, ⟨10.1007/s10898-024-01443-8⟩ Article dans une revue hal-04462829v1
	SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes Paul Saves , Rémi Lafage , Nathalie Bartoli , Youssef Diouane , Jasper Bussemaker et al. Advances in Engineering Software, 2024, 188 (103571), pp.103571. ⟨10.1016/j.advengsoft.2023.103571⟩ Article dans une revue hal-04331916v1
	High-dimensional Bayesian optimization using both random and supervised embeddings Rémy Priem , Youssef Diouane , Nathalie Bartoli , Sylvain Dubreuil , Paul Saves AIAA Journal, 2024, 63 (1), pp.162-173. ⟨10.2514/1.J063488⟩ Article dans une revue hal-04793266v1
	High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft Paul Saves , Youssef Diouane , Nathalie Bartoli , Thierry Lefebvre , Joseph Morlier Structural and Multidisciplinary Optimization, 2024, 67 (5), pp.81. ⟨10.1007/s00158-024-03785-z⟩ Article dans une revue hal-04574274v1
	A mixed-categorical correlation kernel for Gaussian process Paul Saves , Y. Diouane , Nathalie Bartoli , T. Lefebvre , J. Morlier Neurocomputing, 2023, ⟨10.1016/j.neucom.2023.126472⟩ Article dans une revue hal-04130877v2

	Caractérisation de la complémentarité des détecteurs d'anomalies par l'analyse des contributions SHAP Jordan Levy , Paul Saves , Moncef Garouani , Nicolas Verstaevel , Benoit Gaudou Conférence Nationale en Intelligence Artificielle, AFIA, Jun 2026, Arras, France Communication dans un congrès hal-05686526v1
	Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis Matthieu Mastio , Paul Saves , Benoit Gaudou , Nicolas Verstaevel International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), May 2026, Paphos, Cyprus. ⟨10.65109/EXII2056⟩ Communication dans un congrès hal-05426172v2
	Efficient multidisciplinary design via Bayesian optimization Nathalie Bartoli , Thierry Lefebvre , Rémi Lafage , Paul Saves , Youssef Diouane et al. 17ème Colloque National en Calcul de Structures (CSMA 2026), CNRS; CSMA; ENS Paris-Saclay; CentraleSupélec, May 2026, Hyères, France. pp.685832 Communication dans un congrès hal-05636767v1
	Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity Jordan Levy , Paul Saves , Moncef Garouani , Nicolas Verstaevel , Benoit Gaudou Intelligent Data Analysis (IDA) 2026, Springer Nature and IDA, Apr 2026, Leiden (NL), Netherlands. pp.126-140, ⟨10.1007/978-3-032-23833-7_10⟩ Communication dans un congrès hal-05485124v3
	Black-box Active Learning for Discovering New Explanations in Complex System Exploration Paul Saves , Nicolas Verstaevel , Benoit Gaudou Third Derivative-Free Optimization Symposium, GERAD; Polytechnique Montréal; Mathematical Optimization Society, Jun 2026, Montréal (Québec), Canada Communication dans un congrès hal-05709862v1
	Caractérisation de la complémentarité des détecteurs d'anomalies par l'analyse des contributions SHAP Jordan Levy , Paul Saves , Moncef Garouani , Nicolas Verstaevel , Benoit Gaudou Rencontres des Jeunes Chercheurs en IA, AFIA, Jun 2026, Arras, France Communication dans un congrès hal-05686534v1
	From Model-Based Screening to Data-Driven Surrogates: A Multi-Stage Workflow for Exploring Stochastic Agent-Based Models Paul Saves , Matthieu Mastio , Nicolas Verstaevel , Benoit Gaudou MABS 2026 - The 27th International Workshop on Multi-Agent-Based Simulation @AAMAS, IFAAMAS, May 2026, Paphos (Cyprus), Cyprus Communication dans un congrès hal-05564415v1
	Agents adaptatifs dans des marchés spatialisés à double enchère pour la modélisation de l'émergence de symbioses industrielles Matthieu Mastio , Paul Saves , Benoit Gaudou , Nicolas Verstaevel Les 34èmes Journées Francophones sur les Systèmes Multi-Agents (JFSMA 2026), AFIA; Université d'Artois, Jul 2026, Arras, France Communication dans un congrès hal-05678237v1
	Modèles de Substitution pour les Modèles Basés Agents : Enjeux, Méthodes et Applications Paul Saves , Nicolas Verstaevel , Benoit Gaudou Les 33èmes Journées Francophones sur les Systèmes Multi-Agents (JFSMA 2025), Jun 2025, Dijon, France Communication dans un congrès hal-05035806v1
	SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration Mohammad Daffa Robani , Paul Saves , Lavi Rizki Zuhal , Pramudita Satria Palar , Joseph Morlier AIAA SciTech 2025, AIAA, Jan 2025, Orlando, FL, United States. ⟨10.2514/6.2025-0777⟩ Communication dans un congrès hal-04816698v2
	Sustainable Eco-Design of Hybrid-Electric Aircraft via Bayesian Optimization with Mixed Hierarchical Variables Paul Saves , Eric Nguyen Van , Nathalie Bartoli , Thierry Lefèbvre , Youssef Diouane et al. Towards Sustainable Aviation Summit, Airbus, Jan 2025, Toulouse, France Communication dans un congrès hal-05024204v1
	Prix de thèse de la Fondation ISAE-SUPAERO Paul Saves Docteur, raconte-moi ta thèse en 3 minutes !, Fondation ISAE-SUPAERO, Jan 2025, Toulouse, France Communication dans un congrès hal-05433538v1
	Bayesian optimization applied to constrained black-box problems for different aeronautical applications Nathalie Bartoli , Thierry Lefebvre , Rémi Lafage , Paul Saves , Youssef Diouane et al. Modeling and Optimization: Theory and Applications (MOPTA), AIMMS; MOPTA; PAOW, Jun 2025, Ponta Delgada (Açores), Portugal Communication dans un congrès hal-05616536v1
	Remise de prix science ouverte de la thèse, édition 2025 Paul Saves Assises nationales des données de la recherche (ANDOR 2025), Ministère de l’Enseignement supérieur, de la Recherche et de l’Espace (MESRE), Dec 2025, Saclay ENS, France Communication dans un congrès hal-05433479v1
	Frequency-aware Surrogate Modeling With SMT Kernels For Advanced Data Forecasting Nicolas Gonel , Paul Saves , Joseph Morlier AeroBest 2025, Instituto Superior Técnico of the University of Lisbon, Apr 2025, Lisbonne, Portugal Communication dans un congrès hal-05014823v1
	SMT: the Surrogate Modeling Toolbox : Explainability with mixed variables applied to multi-agent system Paul Saves ANR MIMICO 1st Workshop, IRIT, Mar 2025, Toulouse, France Communication dans un congrès hal-05024208v1
	Surrogate-Based Modeling and Optimization of Expensive System Architectures Problems using ONERA and DLR Softwares: An Integrated Framework Paul Saves , Jasper Bussemaker , Rémi Lafage , Nathalie Bartoli , Youssef Diouane et al. 4th workshop for Advances in Artificial Intelligence for Aerospace Engineering, DLR, the German Aerospace Center, Jun 2024, Braunscheiwg, Germany Communication dans un congrès hal-05024184v1
	A graph-structured distance for heterogeneous datasets with meta variables Edward Hallé-Hannan , Paul Saves , Charles Audet , Eric Nguyen Van , Jasper Bussemaker et al. AISSAI Heterogeneous Data and Large Representation Models in Science, Laboratoire des 2 infinis de Toulouse, Sep 2024, Toulouse, France Communication dans un congrès hal-05024197v1
	System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility Paul Saves , Jasper Bussemaker , Rémi Lafage , Thierry Lefebvre , Nathalie Bartoli et al. ODAS 2024: 24th joint ONERA-DLR Aerospace Symposium, DLR, Jun 2024, Brunschweig, Germany Communication dans un congrès hal-04590323v1
	Bayesian optimization to solve black box problems with hidden constraints Nathalie Bartoli , Thierry Lefèbvre , Rémi Lafage , Paul Saves , Youssef Diouane et al. Workshop ANR SAMURAI, Institut Henri Poincaré, Dec 2024, Paris, France Communication dans un congrès hal-05024340v1
	Gaussian process for Bayesian optimization with mixed hierarchical variables: Application to electric-hybrid aircraft eco-design Paul Saves , Eric Nguyen Van , Nathalie Bartoli , Thierry Lefèbvre , Youssel Diouane et al. Workshop on Bayesian optimization & related topics, Jun 2024, Paris, France Communication dans un congrès hal-04845948v1
	Surrogate-Based Optimization of System Architectures Subject to Hidden Constraints Jasper H Bussemaker , Paul Saves , Nathalie Bartoli , Thierry Lefebvre , Björn Nagel AIAA Aviation Forum and ASCEND co-located Conference Proceedings, Jul 2024, Las Vegas, United States. ⟨10.2514/6.2024-4401⟩ Communication dans un congrès hal-04462408v2
	High-dimensional efficient global optimization using both random and supervised embeddings Remy Priem , Nathalie Bartoli , Youssef Diouane , Sylvain Dubreuil , Paul Saves AIAA AVIATION 2023 Forum, American Institute of Aeronautics and Astronautics, Jun 2023, San Diego, United States. pp.10.2514/6.2023-4448, ⟨10.2514/6.2023-4448⟩ Communication dans un congrès hal-04123951v1
	Multidisciplinary design optimization with mixed categorical variables for aircraft design Paul Saves , Nathalie Bartoli , Youssef Diouane , Thierry Lefèbvre , Joseph Morlier et al. AIAA SciTech 2023, American Institute of Aeronautics and Aerospace, Jan 2023, National Harbor (Maryland), United States Communication dans un congrès hal-05022969v1
	Multi-objective bayesian optimization with mixed-categorical design variables for expensive-to-evaluate aeronautical applications Nathalie Bartoli , Thierry Lefebvre , Rémi Lafage , Paul Saves , Youssef Diouane et al. AEROBEST 2023, ECCOMAS, Jul 2023, Lisbonne, Portugal. pp.436 Communication dans un congrès hal-04170287v1
	A new mixed-categorical correlation kernel for Gaussian process Paul Saves MASCOT-NUM 2023, GdR RT-UQ, Apr 2023, Le Croisic (Loire Atlantique), France Communication dans un congrès hal-05022945v1
	Towards a unified Gaussian process kernel-based correlation matrix representation for mixed-categorical variables Paul Saves , Youssef Diouane , Nathalie Bartoli , Thierry Lefèbvre , Joseph Morlier Journées de l'optimisation, HEC Montréal, May 2022, Montréal (Québec), Canada Communication dans un congrès hal-05022901v1
	Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design Paul Saves , Eric Nguyen Van , Nathalie Bartoli , Thierry Lefebvre , Christophe David et al. AIAA SciTech 2022, Jan 2022, San Diego, United States. ⟨10.2514/6.2022-0082⟩ Communication dans un congrès hal-03514915v1
	A general square exponential kernel to handle mixed-categorical variables for Gaussian process Paul Saves , Youssef Diouane , Nathalie Bartoli , Thierry Lefebvre , Joseph Morlier AIAA AVIATION 2022 Forum, Jun 2022, Chicago, United States. ⟨10.2514/6.2022-3870⟩ Communication dans un congrès hal-03700850v1
	Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design Robin Grapin , Youssef Diouane , Joseph Morlier , Nathalie Bartoli , Thierry Lefebvre et al. AIAA AVIATION 2022, Jun 2022, Chicago, United States. ⟨10.2514/6.2022-4053⟩ Communication dans un congrès hal-03753674v1
	Présentation de la Toolbox SMT - L'I.A. pour les modèles de substitution Paul Saves SurDay @ ISAE-SUPAERO, ISAE-Supaero, Jul 2021, Toulouse, France Communication dans un congrès hal-05022608v1
	Constrained bayesian optimization over mixed categorical variables, with application to aircraft design Paul Saves , Nathalie Bartoli , Youssef Diouane , Thierry Lefebvre , Joseph Morlier et al. AeroBest 2021, Jul 2021, Lisbonne, Portugal Communication dans un congrès hal-03346341v1
	Enhanced Kriging models within a Bayesian optimization framework to handle both continuous and categorical inputs Paul Saves , Nathalie Bartoli , Youssef Diouane , Joseph Morlier , Thierry Lefebvre SIAM CSE21, Mar 2021, Fort Worth, United States Communication dans un congrès hal-03402296v1

	Towards frugal Bayesian optimization for environmental impact minimization of computer experiments Gaston Plat , Paul Saves , Nathalie Bartoli , Thierry Lefebvre , Joseph Morlier CNRS. MASCOT-NUM 2026 Conference, Apr 2026, Rennes, France. Proceedings of the MASCOT-NUM 2026 Conference, 2026, pp.15-16, 2026 Poster de conférence hal-05581361v1
	New advances in Multidisciplinary Design Optimization with Gaussian Process for Eco-design Aircraft Paul Saves , Youssef Diouane , Nathalie Bartoli , Thierry Lefèbvre , Joseph Morlier 3rd European MDO Workshop, Sep 2022, Bures sur Yvette, France Poster de conférence hal-05022920v1
	High dimensional multidisciplinary design optimization with Gaussian process for eco-design aircraft Paul Saves MascotNum Annual Conference, Apr 2021, Aussois (Savoie), France Poster de conférence hal-05022530v1

	Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration Paul Saves , Pramudita Satria Palar , Muhammad Robani , Nicolas Verstaevel , Moncef Garouani et al. 2025 Pré-publication, Document de travail hal-05321914v1
	Bayesian Optimization of a Lightweight and Accurate Neural Network for Aerodynamic Performance Prediction James Mingzhi Shihua , Paul Saves , Rhea P Liem , Joseph Morlier 2025 Pré-publication, Document de travail hal-05004649v1

	On adapting the Super-Efficient Global Optimization solver to handle mixed-variables, with applications in aircraft design Paul Saves European Comission. 2020 Rapport hal-05022524v1

	High-dimensional multidisciplinary design optimization for aircraft eco-design Paul Saves Computer Science [cs]. ISAE-SUPAERO, 2024. English. ⟨NNT : 2024ESAE0002⟩ Thèse tel-04439128v2

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Paul Saves

Présentation

Publications

Publications

Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

Global Sensitivity Analysis for Engineering Design Based on Individual Conditional Expectations

A distance for mixed-variable and hierarchical domains with meta variables

System Architecture Optimization Strategies: Dealing with Expensive Hierarchical Problems

SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes

High-dimensional Bayesian optimization using both random and supervised embeddings

High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft

A mixed-categorical correlation kernel for Gaussian process

Caractérisation de la complémentarité des détecteurs d'anomalies par l'analyse des contributions SHAP

Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis

Efficient multidisciplinary design via Bayesian optimization

Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity

Black-box Active Learning for Discovering New Explanations in Complex System Exploration

Caractérisation de la complémentarité des détecteurs d'anomalies par l'analyse des contributions SHAP

From Model-Based Screening to Data-Driven Surrogates: A Multi-Stage Workflow for Exploring Stochastic Agent-Based Models

Agents adaptatifs dans des marchés spatialisés à double enchère pour la modélisation de l'émergence de symbioses industrielles

Modèles de Substitution pour les Modèles Basés Agents : Enjeux, Méthodes et Applications

SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration

Sustainable Eco-Design of Hybrid-Electric Aircraft via Bayesian Optimization with Mixed Hierarchical Variables

Prix de thèse de la Fondation ISAE-SUPAERO

Bayesian optimization applied to constrained black-box problems for different aeronautical applications

Remise de prix science ouverte de la thèse, édition 2025

Frequency-aware Surrogate Modeling With SMT Kernels For Advanced Data Forecasting

SMT: the Surrogate Modeling Toolbox : Explainability with mixed variables applied to multi-agent system

Surrogate-Based Modeling and Optimization of Expensive System Architectures Problems using ONERA and DLR Softwares: An Integrated Framework

A graph-structured distance for heterogeneous datasets with meta variables

System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility

Bayesian optimization to solve black box problems with hidden constraints

Gaussian process for Bayesian optimization with mixed hierarchical variables: Application to electric-hybrid aircraft eco-design

Surrogate-Based Optimization of System Architectures Subject to Hidden Constraints

High-dimensional efficient global optimization using both random and supervised embeddings

Multidisciplinary design optimization with mixed categorical variables for aircraft design

Multi-objective bayesian optimization with mixed-categorical design variables for expensive-to-evaluate aeronautical applications

A new mixed-categorical correlation kernel for Gaussian process

Towards a unified Gaussian process kernel-based correlation matrix representation for mixed-categorical variables

Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design

A general square exponential kernel to handle mixed-categorical variables for Gaussian process

Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design

Présentation de la Toolbox SMT - L'I.A. pour les modèles de substitution

Constrained bayesian optimization over mixed categorical variables, with application to aircraft design

Enhanced Kriging models within a Bayesian optimization framework to handle both continuous and categorical inputs

Towards frugal Bayesian optimization for environmental impact minimization of computer experiments

New advances in Multidisciplinary Design Optimization with Gaussian Process for Eco-design Aircraft

High dimensional multidisciplinary design optimization with Gaussian process for eco-design aircraft

Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration

Bayesian Optimization of a Lightweight and Accurate Neural Network for Aerodynamic Performance Prediction

On adapting the Super-Efficient Global Optimization solver to handle mixed-variables, with applications in aircraft design

High-dimensional multidisciplinary design optimization for aircraft eco-design