E-mail

miguel.munoz-zuniga@ifpen.fr

Contacter
En résumé

2026: HDR, ED MSTII, Grenoble. 
Contribution to the field of learning with frugal data and uncertainty quantification, 

2013 - now: senior research engineer in the applied mathematics department of IFPEN
main research topic : uncertainty quantification and numerical optimization.

2012 - 2013: Post-doctoral fellow at IRSN (Institut de Radioprotection et Sûreté Nucléaire).
main research topic : meta-modelling and optimization of models with functional inputs

2011 - 2012: Post-doctoral fellow at Imperial College.
main research topic : sensitivity analysis and meta-modelling.

2010 - 2011: A.T.E.R. University Paris Diderot – Paris VII.

PhD in applied mathematics (University Paris Diderot – Paris VII) 
Stochastic methods for the controlled estimation of small probabilities on complex physical models. Application to the nuclear domain. 
Supervisor : Josselin Garnier. Industrial Partner : EDF R&D.

Master degree in applied mathematics (Paris-Est university)

Champs disciplinaires IFPEN
Sujets de recherches
Stochastic algorithms
Sensitivity Analysis
Chance constraint optimization
Probability estimation
meta-modelling (Gaussian process , Polynomial Chaos...)
Dimension reduction
Optimization / inversion under uncertainties
Mixed integer continuous optimization
Active learning algorithm and analysis
Stochastic calculus applied to UQ
SDE, Gaussian process and physic informed modelling in infinite dimension
Projets

Collaborative projects

UPCOMING COLLABORATIVE PROJECT

  • 2027 - 2030: Partner in the HORIZON-JU-EUROHPC European project LBM4HPC.
    2 years postdoctoral grant on inverse problem and uncertainty quantification for atmospheric pollutant emissions detection.
    Members: FAU Erlangen-Nürnberg (Coordinator), KIT - Karlsruher institut für Technologie (Partner), CNRS (Partner),  Université de Perpignan (Affiliated), IFP Energies nouvelles (Partner), VSB - Technical university of Ostrava (Partner), CS GROUP - France (Partner), University of Győr (Associated).
  • 2027: Partner in the IEA-Wind TCP IDeA project.
    Enhanced Bayesian quadrature approaches for reliability assessments.
  • 2027 - 2030: PhD supervision with DGEC (Grant proposal).
    Modelling uncertainties in the optimisation of energy systems. Application to the biomass sector for biofuels in France.
  • 2027 - 2030: PhD supervision with ONERA (Grant proposal).
    Towards Informed operator for functional reliability analysis.
  • 2027 - 2030: PhD supervision with SIEMENS (Grant proposal).
    Machine learning based calibration of P2D/DFN thermo-electrochemical models incorporating ageing.
  • 2027 - 2030: PhD supervision with INRIA (Grant proposal).
    Design of numerical experiments and quantification of uncertainties for calibration based on modal analysis and taking modelling errors into account.
  • 2027-: Cost Action - STOCHASTICA.

CURRENT COLLABORATIVE PROJECT

  • 2025 - 2028: Joint head in 2027 with Guillaume Perrin (University Gustave-Eiffel) and Mickael Binois (INRIA) and Christophette Blanchet-Scalliet of the French consortium CIROQUO-2 (Consortium Industriel de Recherche en Optimisation et QUantification d'incertitudes pour les données Onéreuses) organised by the École Centrale de Lyon. 
    Partner and member of the steering committee throughout the entire period.
    Members: EMSE, Centrale Lyon, INRIA Côte d'Azur, Université Toulouse III, INRIA Saclay, UGA, Ecole polytechnique, IFPEN, BRGM, CEA, ASNR, Michelin, Stellantis, Liebherr, EDF.
  • 2015 - ongoing: Member of the Executive Committee in the French CNRS research network RT-UQ. 

PAST COLLABORATIVE PROJECT​​​​​​

  • 2024 - 2025: Collaboration with Mathilde Mougeot - ENS Saclay and Teddy Virin - Michelin.
    Dealing with multimodality and missing variables in data based modelling. 
  • 2025 - 2026: Collaboration with Dario Azzimonti - IDSIA.
    Skew Gaussian process models for preference learning of bicycle routing.
  • 2021 - 2024: Partner in and member of the steering committee of the consortium CIROQUO 
    Consortium Industriel de Recherche en Optimisation et QUantification d'incertitudes pour les données Onéreuses.
    Members: EMSE, Centrale Lyon, CNRS, UCA, Université Toulouse III, INRIA, UGA, Ecole polytechnique, IFPEN, BRGM, CEA, IRSN, Storengy, Stellantis.
  • 2021 - 2024: Partner and workpackage leader in the ANR project SAMOURAI.
    Simulation Analytics and Meta-model-based solutions for Optimization, Uncertainty and Reliability AnalysIs. 
    Members: CEA, CentraleSupelec, EDF, EMSE, IFPEN, Polytechnique Montréal, Safran.
  • 2021 - 2024: Partner in the H2020 European project HIPERWIND (Highly advanced Probabilistic design and Enhanced Reliability methods for high-​value, cost-​efficient offshore WIND. 
    Members: DTU, EDF, IFPEN, EPRI, DNV, University of Bergen, ETH Zurich.
  • 2020 - 2023: Leader of a programme Samuel de Champlain project.
    Dealing with categorical inputs in black-box models optimization.
    Members: GERAD - Ecole Polytechnique de Montréal (S. Le Digabel, C. Audet), IFPEN.
  • 2016 - 2019: Partner in the applied mathematics Chaire OQUAIDO  
    Optimisation et QUAntification d'Incertitude pour les Données Onéreuses.
    Members: EC Lyon, UPS, EMSE, CNRS/UNICE, CEA, SAFRAN, ISFA, BRGM, IRSN, UGA, Storengy.
  • 2016: Partner in Joint Industrial Projects STARWACS (flow assurance of crude oil transport). Developments in sensitivity analysis.
    Sponsor: Alyeska Pipeline and TotalEnergies.
  • 2015 - 2016: Construction and co-leader of a PGMO projects.  
    Optimization under probabilistic constraints of complex systems – Application to the anchoring of offshore wind-turbines.
    Members: EDF, UniversitätDuisburh-Essen, Paris-Diderot University, IFPEN. 
  • 2015 - 2017: Partner in the Joint Industrial Projects ERMES in reservoir engineering
    Enhanced unceRtainty and optiMization mEthodologieS: surrogate modelling, sensitivity analysis and optimization.
    Members: Petrobras, ENGIE, IFPEN.
  • 2014 - 2015: Partner in the ANR MODNAT 
    Probabilistic reliability in high dimension.
  • 2013 - 2015: Partner in the consortium ReDICE 
    Novative mathematical methods for the design and analysis of computer experiments.

IFPEN project management and responsabilities

  • 2026-ongoing: Organiser of the applied mathematics department advanced working group LUQI (Learning – UQ – optImisation).
  • 2026-ongoing: Coordinator of the IFPEN DeTOCS research project.
    Design Tools for Optimisation and Control of Complex Systems.
  • 2022-2024: Co-chair of one of the nine IFPEN scientific challenges: Optimisation and Control of Complex Systems.
  • 2020-ongoing: Work-packages leader in the IFPEN DeTOCS research project.
    Design Tools for Optimisation and Control of Complex Systems.

Project reviews, committees and expertises

  • 2026 - Expertise for the Beicip Franlab tool: CougarFlow.
  • 2026 - Four-yearly evaluation of the INRIA team PLATON with co-assessors K.E. Willcox and D. Ginsbourger.
  • 2024 - Expertise on data analysis and culstering: Rock-Eval® measurements of Guano.
  • 2024 - Expertise in statistics: Ground analysis with Rock-Eval® around solar panels installation. IFPEN / Total Energies.
  • 2024 - Expertise in statistics : Rock-Eval® data analysis and standard results sheet construction.
  • 2024 - Expertise for the Beicip Franlab tool: CougarFlow.
  • 2021 - Expertise sharing with Elias Fekhari (EDF) for his PhD on the topic of expectation estimation with metamodelling and active learning.
  • 2019 - Expertise for the Autorité de Sécurité Nucléaire Défense - ASND - on design of experiments, sensitivity analysis and modelling.
  • 2018 - Member of the scientific committee for the conference DataSciEn'2018 Learning from Scientific Data in Energy.
  • 2018 - CITEPH project evaluation : Collaborative & Innovative Technology Program in Exploration and Production of Hydrocarbons.

Conference organization

Conference Invitation

  • 2026 - STOCHASTICA directions workshop, April, 27-29, UCC, Cork, Ireland
    Quantification and reduction of uncertainty in complex 'black-box'' numerical models analysis using Gaussian processes.
  • 2023 - Data science pour les risques côtiers (LMBA, LHYMAR IFREMER), 13-15, November, Roscoff, France.
    Extreme and fatigue reliability analysis of a wind turbine simulator. Dealing with high dimensional environmental conditions.
  • 2022 - SIAM conference on uncertainty Quantification, 12-15 April Atlanta, Georgia US (visio). 
    A two-step procedure for time-dependent reliability-based design optimization involving piece-wise stationary Gaussian processes.
  • 2021 - RESIM 2021 : 13th International Workshop on Rare-Event Simulation. 18-21 Mai Paris. 
    A reformulated chance constraint optimization problem for the fatigue design of an offshore wind turbine mooring system.
  • 2020 - Journée de la conception robuste et fiable - 7eme edition 29 Janvier - SIGMA Clermont-Ferrand.
    Reliability based design optimization and uncertainty quantification for offshore wind turbines.
  • 2019 - Atelier de modélisation de l'Atmosphère (AMA) - 11 mars 2019- Météo-France, Toulouse.
    Optimization and Bayesian approaches for model calibration.
  • 2017 - International workshop on nuclear data covariances - 02 october 2017 - CEA Cadarache and NEA, Aix en Provence.
    Optimization and Bayesian approaches for model calibration, link with oil and gas field management.

Post-doctoral collaboration

  • Valentin Breaz : Jan. 2023 - June 2024
    Sequential surrogate and gradient based dimension reduction for high dimensional rare event probability estimation
    Supervision: O. Zahm (INRIA), M. Munoz Zuniga (IFPEN).
  • Stephane Jacquet : Janv. 2023 - Janv. 2024
    Integrating hidden constraints within NOMAD optimizer and improving mixed inputs optimizer.
    Supervision: M. Menz (IFPEN), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Morgane Menz : Dec 2021 - Dec 2022
    Learning Hidden constraints for optimization and metamodelling.
    Supervision: D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Achille Murangira : April 2014 - Oct 2015
    Extreme mechanical response prediction and failure probability estimation of a floating wind turbine submitted to wind time variant random processes.
    Supervision: T. Perdrizet (IFPEN), M. Munoz Zuniga (IFPEN).

PhD supervision

  • Ghislain Vallet-Degremont: April 2026 - April 2029
    Hybrid modelling and uncertainty quantification in industrial processes.
    Supervision: F. Gamboa (Institut de Mathématiques de Toulouse, Université Paul Sabatier), C. Helbert (Centrale Lyon), P. Bussetta (Michelin), M. Munoz Zuniga (IFPEN).
  • Lorenzo Calzolari:  Nov. 2024 - Nov. 2027
    Functional experimental designs: extension of sampling based on the maximin and MMD principles to infinite-dimensional spaces.
    Supervision: C. Prieur (LJK, Université Grenoble Alpes) and C. Helbert (Centrale Lyon), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Enikő Bartók:  Nov. 2022 - Nov. 2025 
    Variance based sensitivity analysis in high dimension from Gaussien fields models.
    Supervision: E. Vazquez (Central Supelec), N. Bonfils (IFPEN), M. Munoz Zuniga (IFPEN).
  • Adama Barry: Janv. 2022 - Janv. 2025 
    Optimal design of physical and numerical experiments for computer code calibration
    Supervision: C. Prieur (LJK, Université Grenoble Alpes) and F. Bachoc (Institut de Mathématiques de Toulouse, Université Paul Sabatier), S. Bouquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Clément Duhamel: Oct. 2020 - Oct. 2023 
    Estimation d'ensembles d'excursion par processus gaussiens pour des fonctions boîtes noires à valeurs scalaires ou vectorielles.Application à la calibration d'un simulateur numérique éolien,
    Supervision: C. Prieur (LJK, Université Grenoble Alpes) and C. Helbert (Centrale Lyon), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Erwan Rondeaux: Sept. 2019 - Sept. 2022
    Calage bayesien et machine learning pour accelerer la calibration de modèles CFD.
    Supervision: C. Angelberger (IFPEN), A. Poubeau (IFPEN), M. Munoz Zuniga (IFPEN).
    Partner: R. Paoli (Univ. Illinois).
  • Alexis Cousin: Sept. 2018 - Sept. 2021
    Chance constraint optimization of a complex system. Application to the design of a floating offshore wind turbine.
    Supervision: J. Garnier (Ecole Polytechnique), M. Guiton (IFPEN), M. Munoz Zuniga (IFPEN).
  • Adrien Hirvoas: Aout 2018 - Aout 2021
    Assimilation de données de capteur d'eoliennes pour la mise à jour en continue de modèles fidèles.
    Supervision: C. Prieur (Univ. Grenoble Alpes) and E. Arnaud (Univ. Grenoble Alpes), F. Caleyron (IFPEN), M. Munoz Zuniga (IFPEN).
  • Reda El Amri: Aout 2016 - Aout 2019
    Robust inversion of models with functional inputs. Application to a car pollution control system.
    Supervision: C. Prieur (Univ. Grenoble Alpes) and C. Helbert (Ecole centrale Lyon), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).
  • Ivana Aleksovska: sept 2015 - Mars 2017
    Statistical reformulation of  the probabilities of damage and feasability constraints of an offshore wind turbine mooring line.
    Supervision: J. Garnier (Ecole Polytechnique), M. Guiton (IFPEN), M. Munoz Zuniga (IFPEN).

Internship and training surpervision

2027

  • Student TBA
    Robust optimal sensor placement for Bayesian inverse problems governed by PDEs
    Supervision: J-L Pfister (IFPEN), M. Munoz Zuniga (IFPEN)
    Collaboration: C. Gauchy (CEA Saclay), A. Quintin (CEA DAM)
  • Student TBA
    Error compensation in simulation chains and modular approaches
    Supervision: C. Gauchy (CEA Saclay), A. Quintin (CEA DAM)
    Collaboration: J-L Pfister (IFPEN), M. Munoz Zuniga (IFPEN)

2024

  • Chloé Contant - ENSAI (15 Avril / 15 Oct.) 
    Quantification d’incertitudes et modélisation Multimodale pour la prédiction de propriétés physico-chimiques de mélanges
    Supervision: M. Mougeot (ENS Paris-Saclay), D. Sinoquet (IFPEN), T. Virin (MICHELIN), M. Munoz Zuniga (IFPEN).
  • Mahmoud Aharmouch - Université Toulouse III - MAp13 (10 Mars / 6 Sept.)
    Space-filling design in a functional space for meta-modelling
    Supervision: C. Prieur (UGA), C. Helbert (Centrale Lyon), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).

2022

  • Lydia Hamoum - Université Paris-Saclay - M2 Computer & Network Systems 
    Meta-modelling the fatigue of a riser.
    Supervision: E. Roguet (IFPEN), F. Delbos (IFPEN), M. Munoz Zuniga (IFPEN).
  • Soufian Echabarri - Centrale Supélec
    Meta-modelling functional outputs from a simulator. Application to the fatigue estimation of an offshore wind turbine.
    Supervision: E. Vazquez (Centrale Supélec), F. Delbos (IFPEN), N. Bonfils (IFPEN), M. Munoz Zuniga (IFPEN).

2021

  • Jarod Foucaud - Université Gustave Eiffel
    Design of experiments for the calibration of numerical simulators.
    Supervision: L. Pronzato (I3S), M.J. Rendas  (I3S), S. Bouquet (IFPEN), M. Munoz Zuniga (IFPEN).

2020

  • Clément Duhamel - Université Claude Bernard Lyon 1 
    Stochastic inversion.
    Supervision: C. Prieur (Université Grenoble Alpes), C. Helbert (Ecole Centrale Lyon), D. Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).

2019

  • Mouhamed Ba - Alternance ISUP-Sorbonne Université (2019-2020) 
    Gaussian Process modelling with large data sets and GP based mixed optimization.
    Supervision: M. Munoz Zuniga (IFPEN).
  • Jingang Qu - Sorbonne Université  
    Study of the hidden constraints of a black-box simulator with machine learning.
    Supervision with Frederic Delbos (IFPEN), M. Munoz Zuniga (IFPEN).
  • Mouhamadou Sow - INSA Rouen  
    Non-stationnary Gaussian process modelling.
    Supervision: M. Munoz Zuniga (IFPEN).
  • Erwan Rondeaux - INSA Rouen  
    Evaluation of the machine learning potential for CFD models predictions.
    Supervision: Adèle Poubeau (IFPEN), M. Munoz Zuniga (IFPEN).

2017

  • Adrien Hirvoas - Université Blaise Pascal
    Global sensitivity analysis of an offshore wind turbine.
    Supervision: Fabien Caleyron (IFPEN), M. Munoz Zuniga (IFPEN).
  • Konstantinos Varelas - Paris Saclay University
    Multi-objectives optimization with constraints.
    Supervision: Delphine Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).

2016

  • Giulia Cavenago - Politecnico Milano
    Surrogate models with mixed qualitative and quantitative variables: application in reservoir engineering.
    Supervision: Delphine Sinoquet (IFPEN), M. Munoz Zuniga (IFPEN).

2012

  • Gulnara Abdrakhmanova-Aitzhanova - Imperial College
    Sensitivity analysis.
    Supervision: M. Munoz Zuniga (IFPEN).
  • Student - IFMA / école d'ingénieurs SIGMA Clermont
    Generalized Polynomial Chaos modelling.
    Supervision: M. Munoz Zuniga (IFPEN).

Courses

  • 2024 - 2027 Lecture - Optimization - Master 2 Mécanique des structures et des systèmes couplés, CNAM, 75h.
  • 2021 - 2025 Lecture - Introduction to probablity and statistics - Master HPC-IA, Mines Paris-Tech, 93h.
  • 2023 - 2024 Lecture - Unsupervised dimension reduction and clustering - IFPSCHOOL, 3h. 
  • 2021 - 2023 Lecture - Introduction to linear regression and neural network - IFPSCHOOL, 14h. 
  • 2019 - 2020 Lecture - Advanced introduction to kernel based dimension reduction with and without gradients - IFPEN, 4h. 
  • 2016 - 2018 Lecture - Advanced topics in statistics, uncertainty treatment and optimization - IFPEN, 35h.
  • 2013 - 2014 Teaching assistant - Numerical analysis - EPF Sceaux, 120h.
  • 2011 - 2012 Supervision of 2 MS student, Imperial College London.
  • 2010 - 2011 Teaching assistant - Statistics, analysis, linear algebra - Bachelor’s degrees, Diderot University (Paris 7), 80h .
  • 2008 - 2010 Lecture - Numerical statistics and data analysis, Ecole Nationale des Ponts et Chaussées, 40h.
  • 2008 - 2010 Teaching assistant - Probability, analysis, linear algebra - Bachelor’s degrees, Sorbonne University (Paris 6), University Gustave Eiffel and the Ecole Supérieure d’Ingénieurs en Electrotechnique et Electronique (engineering), 140h.
  • 2003 - 2007 Undergraduate teaching assistant - analysis, linear algebra - preparation to Bachelor’s degrees, University Gustave Eiffel , 100h.
Publications

2026

  • Munoz Zuniga, M.
    Enhanced active learning with stochastic calculus for probabilistics numerics and uncertainty quantification.
    IFPEN internal report
  • Cousin, A., Munoz Zuniga, M.
    Malliavin calculus for active learning in Bayesian quadrature of non-stationary, constrained and stochastic simulators.
    IFPEN internal report.
  • Cousin, A., Khvoenkova, N., Munoz Zuniga, M.
    Malliavin calculus for active learning in Bayesian quadrature of non-stationary and constrained simulators with application to wind turbine structural damage assessment.
    IFPEN internal report.
  • Calzolari, L, Helbert, C., Munoz Zuniga, M., Prieur, C, Sinoquet, D.
    Maximin functional experimental designs over the unit ball of a Reproducing Kernel Hilbert Space.
    Submitted in June 10 to Statistics and Computing.
  • Breaz, V., Munoz Zuniga, M., Wilkinson, R., Zahm, O.
    A new gradient-free active subspace estimation method with application to rare event probability estimation.
    Submitted in January 30 to ESAIM Probability and Statistics.
  • Barry, A., Bachoc, F., Bouquet, S., Munoz Zuniga, M., Prieur, C.
    Design of experiments for computer code calibration.
    International Journal of Uncertainty Quantification.
  • Duhamel, C., Helbert, C., Munoz Zuniga, M., Prieur, C, Sinoquet, D.
    Active learning strategies for the estimation of a feasible set defined from a vector output black-box simulator.
    SMAI Journal of Computational Mathematics.

2025

  • Menz, M., Munoz Zuniga, M., Sinoquet, D.
    Estimation of simulation failure set with active learning based on Gaussian process classifiers and random set theory.
    Structural Safety.

2024

  • Cousin, A., Del´epine, N., Guiton, M., Munoz Zuniga, M., Perdrizet, T.
    Advanced adaptive design of experiments for computing the fatigue life of an offshore wind turbine
    Structural Safety.
  • Angelberger, C., Poubeau, A., Rondeaux, E., Munoz Zuniga, M.
    Exploring the potential and the pratical usability of a machine learning approach for improving wall friction predictions of RANS wall functions in non-equilibrium turbulent flows.
    Flow, Turbulence and Combustion.

2023

  • El Amri, M.R., Helbert, C., Munoz Zuniga, M., Prieur, C. and Sinoquet, D.
    Feasible set estimation under functional uncertainty by Gaussian Process modelling.
    Physica D: Nonlinear phenomena, special Issue – Uncertainty Quantification in Complex Dynamical Systems.
  • Duhamel, C., Helbert, C., Munoz Zuniga, M., Prieur, C, Sinoquet, D.
    A SUR version of the Bichon criterion for excursion set estimation.
    Statistics and Computing.

2022

  • Cousin, A., Garnier, J., Guiton, M. and Munoz Zuniga, M. 
    A two-step procedure for time-dependent reliability-based design optimization.
    Structural and Multidisciplinary Optimization.
  • Arnaud, E., Caleyron, F., Hirvoas, A., Munoz Zuniga, M., and Prieur, C.
    Wind turbine quantification and reduction of uncertainties based on a data-driven data assimilation approach.
    Journal of Renewable and Sustainable Energy.

2021

  • Arnaud, E., Caleyron, F., Hirvoas, A., Munoz Zuniga, M., and Prieur, C.
    Quantification and reduction of uncertainties in a wind turbine numerical model based on global sensitivity analysis and recursive Bayesian inference approach.
    International Journal for Numerical Methods in Engineering.
  • Munoz Zuniga, M.
    A Gaussian Process based Stepwise Uncertainty Reduction strategy for the estimation of a structure cumulated damage
    IFPEN internal report.
  • Munoz Zuniga, M.
    Review of criteria for sequential enrichment of a design of experiments in the context of Gaussian process based meta-modelling
    IFPEN internal report.

2020

  • Cousin, A., Garnier, J., Guiton, M. and Munoz Zuniga, M. 
    Chance constraint optimization of a complex system - Application to the fatigue design of a floating offshore wind turbine mooring system.
    Proceedings in 14th World Congress on Computational Mechanics (WCCM) - ECCOMAS Congress 2020
    (Virtual Congress) 11-15 January. F. Chinesta, R. Abgrall, O. Allix and M. Kaliske (Eds)
  • Murangira, A., Munoz Zuniga, M., Perdrizet, T.
    Structural reliability assessment through metamodel based importance sampling with dimension reduction.
    Reliability Engineering & System Safety.

2019

  • Munoz Zuniga, M., and Sinoquet, D.,
    Global Optimization for mixed categorical-continuous variables based on Gaussian process models with a randomized categorical space exploration step,
    Information Systems and Operational Research, 2019.
  • El Amri, M.R., Helbert, C., Lepreux, O., Munoz Zuniga, M., Prieur, C. and Sinoquet, D.,
    Datadriven stochastic inversion under functional uncertainties,
    Statistics and Computing, 2019.

2018

  • van Ackooij, W., Aleksovska, I., Munoz Zuniga, M.,
    (Sub-)Differentiability of Probability Functions with Elliptical Distributions,
    Set-Valued and Variational Analysis Volume 26, Issue 4, pp 887-910, 2018.
  • Munoz Zuniga, M., Guiton, M., Wahl, F.,
    Surface de réponse pour Deeplines en houle irrégulière, 
    IFPEN internal report.

2017

  • Munoz Zuniga, M.,
    Generation of a space-filling design of experiments in a constrained and disconnected Euclidean space, IFPEN internal report.
  • Munoz Zuniga, M., Guiton, M.,
    Résultats préliminaires pour la surface de réponse de Deeplines en houle irrégulière,
    IFPEN internal report.

2016

  • Munoz Zuniga, M. and Benali, A.,
    Functional principal component analysis for the Bayesian calibration of a numerical simulator with functional output,
    IFPEN internal report.
  • Lameiras Franco Da Costa V., Lameiras Franco Da Costa V.R., Munoz Zuniga M., Dallerit V.,
    Etude de l'incertitude en modèle linéaire et Krigeage,
    IFPEN internal report.

2015

  • Munoz Zuniga, M. and Ben Gharbia, I.,
    A numerical comparison of an adaptive Generalized Polynomial Chaos method and an adaptive Gaussian Process metamodel. Proposition of an improved adaptive Gaussian Process approach,
    IFPEN internal report.
  • Munoz Zuniga, M.,
    Analyse de sensibilité d’un modèle à entrées dépendantes et plan d’expérience optimal construit à partir de mesures de dépendances (Partie 1),
    IFPEN internal report.

2014

  • Caron, V., Guyader, A. Munoz Zuniga, M., Tuffin, B.,
    Some recent results in rare event estimation,
    ESAIM: Proceedings 44, 239-259, 2014.
  • M. Munoz Zuniga and Y. Richet,
    Global optimization of a computer based model with functional data inputs,
    IRSN internal report.

2013

  • M. Munoz Zuniga and S. Kucherenko,
    Low cost estimates of total sensitivity indices based on metamodels,
    Imperial College internal report.
  • M. Munoz Zuniga and S. Kucherenko, N. Shah,
    Metamodelling with independent and dependent inputs,
    Computer Physics Communications.

2011

  • M. Munoz Zuniga, J. Garnier, E. Remy and E. de Rocquigny,
    Analysis of adaptive directional stratification for the controlled estimation of rare event probabilities, Statistics and Computing.
  • M. Munoz Zuniga, J. Garnier, E. Remy and E. de Rocquigny,
    Adaptative Directional Stratification for controlled estimation of the probability of a rare event,
    Reliability Engineering & System Safety.

2010

  • M. Munoz Zuniga, J. Garnier, E. Remy and E. de Rocquigny,
    Adaptative Directional Stratification: an adaptive directional simulation method in a stratified space, Safety, Reliability and Risk of Structures, Infrastrutures and Engineering Systems, Taylor & Francis Group, London.

2008

  • M. Munoz Zuniga, J. Garnier, Y. Lefebvre,
    Controlled estimation of the probability of rare event for a complex physical model - examination of monotoneous variation models,
    Congrès Lambda-Mu 16, Avignon.

Computational developments:

  • Development of algorithms in IFPEN uncertainty treatment and optimization softwares : COUGAR, ATOUT, HubStat.
  • Package Generalized Polynomial Chaos (GPC) published on the Comprehensive R Archive Network (CRAN),
  • Implementation of the Brent algorithm in the IRSN platform Prométhée.
  • Implementation of a Quasi Random Sampling-High dimensional model representation in an Imperial College plateform,
  • Development of the prototype of the Adaptive Directional Sampling Monte Carlo technique implemented in OpenTurns (an Open source initiative for the Treatment of Uncertainties Risks’N Statistics).