In a few words

Maxime Moreaud is responsible for deploying fundamental research in Artificial Intelligence in R&I business applications, he is project manager for IFPEN's Scientific Division, and a researcher in applied deep learning within the Digital Sciences and Technologies division. He holds a PhD from Ecole des Mines de Paris (2006) in mathematical morphology, an engineering degree from Telecom Saint Etienne (2002) in electronics-optics, and an Accreditation to Supervise Research (French HDR) in engineering sciences (ED 488 SIS, 2017). He has worked on a variety of fundamental topics from image processing for materials science and has developed a strong expertise in deep learning with over 60 papers, more than 10 patents, and the supervision of 12 PhD students. He also works on the computational design of materials, focusing on the optimization of microstructure according to targeted textural properties and applications. He was a research associate at the Center of Mathematical Morphology of Mines Paris PSL from 2016 to 2022. He was a visiting researcher at the CERVO Brain research center (2021-2022), a laboratory of excellence in neurophotonics at Laval University, Quebec, Canada, where he worked on improving the quality of conventional digital holographic microscopy images using AI. This project was awarded the H2020 label of excellence. 

His research in image processing has led to methods for noise reduction, image restoration, texture characterization and a deep learning strategy with a limited data set. He is also the creator and lead developer plug im! platform from IFPEN.

He is responsible for the deployment of fundamental research in artificial intelligence in research and innovation business applications, assisting in the guidance and selection of appropriate AI approaches, and supporting users in implementation and skill development.

photo profile credit: D. Guillaume.

IFPEN’s disciplinary fields
Research subjects
Image processing with material science applications
Morphological random models
Deep learning

Project leader Data Driven Design for New Materials

Leading an innovative and comprehensive strategy (see figure) for accelerated digital materials design.

Objectives: synthesis of sodium-ion and all-solid-state battery electrodes, synthesis of hierarchical alumina supports, design of metallic and ceramic foams.

Tools: multiscale microstructure models, aggregation model and numerical characterizations (tortuosity, percolation), FFT homogenization schemes. Deep learning to optimize microstructures, accelerate models and/or increase their accuracy

The project team is also involved in ANR ARTEMIA and PEPR batterie with the BATMAN project.

26 scientific publications, 2 patents, 15 modules via plug im!


Figure: Realistic 3D microstructure (center) linked to synthesis/manufacturing parameters by physical models (left). On the right, texture and performance characterizations calculated from virtual microstructures to target functionalities. The microstructure is then optimized by deep learning.

plug im!

Creator of plug im! IFP Energies nouvelles' open access platform offering implementations of our solutions in deep learning, image processing and digital material design.

plug im! : le logiciel en open access d’IFP Energies nouvelles pour la visualisation et le traitement de signaux, images et volumes.




Potential Energy Surface-Based Descriptors for Nanoporous Materials and its Applications to Classification and CO2 Gas Adsorption into Zeolites, C Nieto-Draghi, B Creton, X Martin, J Chaniot, M Moreaud, ACS Applied Engineering Materials, 2024.

Deep learning ancient map segmentation to assess historical landscape changes, T Martinez, A Hammoumi, G Ducret, M Moreaud, R Deschamps, H Piegay, Jean-François Berger, Journal of Maps 19 (1), 2225071, 2023.

Less-than-one shot 3D segmentation hijacking a pre-trained Space-Time Memory network, C Li, C Ducottet, S Desroziers, M Moreaud, Advanced Concepts for Intelligent Vision Systems. ACIVS 2023. Lecture Notes in Computer Science, vol 14124. Springer, Cham. 2023.

Computing Surface Reaction Rates by Adaptive Multilevel Splitting Combined with Machine Learning and Ab Initio Molecular Dynamics, T Pigeon, G Stoltz, M Corral-Valero, A Anciaux-Sedrakian, M Moreaud, Tony Lelièvre, Pascal Raybaud, Journal of Chemical Theory and Computation 19 (12), 3538-3550, 2023.

Method of Detecting at Least One Geological Constituent of a Rock Sample, S Desroziers, M Feraille, V Clochard, A Bouziat, Y Hamon, M Moreaud, US Patent App. 17/919,319, 2023.

Boehmite agglomeration through experimental and model approaches: From colloidal system to porous solid, G Ferri, S Humbert, M Digne, M Moreaud, JM Schweitzer, Chemical Engineering Journal Advances 14, 2023.

Toward few pixel annotations for 3D segmentation of material from electron tomography, C Li, C Ducottet, S Desroziers, M Moreaud, International Conference on Computer Vision Theory and Applications, VISAPP 2023.

Small-angle X-ray scattering intensity of multiscale models of spheroids, P Duchêne, S Humbert, L Sorbier, M Moreaud, Journal of Applied Crystallography 56 (1), 237-246, 2023.

plug im! software for comprehensive two-dimensional gas chromatography with vacuum ultraviolet detection–A tutorial, A Lelevic, V Souchon, C Geantet, C Lorentz, M Moreaud, Chemometrics and Intelligent Laboratory Systems 231, 2022.

Accelerating a Morphology-Preserving Adsorption Model by Deep Learning, A Hammoumi, M Moreaud, E Jolimaitre, T Chevalier, M Klotz, A Novikov, 2022 IEEE International Conference on Image Processing (ICIP), 1851-1855, 2022.

Quantification and morphological characterization of microfibers emitted from textile washing, M Dreillard, CDF Barros, V Rouchon, C Emonnot, V Lefebvre, M Moreaud, Denis Guillaume, Fabrice Rimbault, Frédéric Pagerey, Science of The Total Environment 832, 2022.

A novel physisorption model based on mathematical morphology operators preserving exact pore morphology and connectivity, A Hammoumi, M Moreaud, D Jeulin, E Jolimaitre, T Chevalier, L Sorbier, Michaela Klotz, Alexey Novikov, Microporous and Mesoporous Materials 337, 2022.

Mass fractal dimension from 2D microscopy images via an aggregation model with variable compactness, G Ferri, S Humbert, JM Schweitzer, M Digne, V Lefebvre, M Moreaud, Journal of Microscopy 286 (1), 31-41, 2022.

Scalable morphological accessibility of complex microstructures, J Chaniot, M Moreaud, L Sorbier, JM Becker, T Fournel,Computational Materials Science 203, 2022.

Advanced data preprocessing for comprehensive two‐dimensional gas chromatography with vacuum ultraviolet spectroscopy detection, A Lelevic, V Souchon, C Geantet, C Lorentz, M Moreaud, Journal of Separation Science 44 (22), 4141-4150, 2021.

Adding geodesic information and stochastic patch-wise image prediction for small dataset learning, A Hammoumi, M Moreaud, C Ducottet, S Desroziers, Neurocomputing 456, 481-491, 2021.

Quantitative analysis of hydrocarbons in gas oils by two-dimensional comprehensive gas chromatography with vacuum ultraviolet detection, A Lelevic, C Geantet, M Moreaud, C Lorentz, V Souchon, Energy & Fuels 35 (17), 2021.

Simulation of Large Aggregate Particles Systems with a New Morphological Model, G Ferri, S Humbert, M Digne, JM Schweitzer, M Moreaud, Image Analysis & Stereology 40, 71-84, 2021.

Graph-Based M-tortuosity Estimation, A Hammoumi, M Moreaud, E Jolimaitre, T Chevalier, A Novikov, M Klotz, International Conference on Discrete Geometry and Mathematical Morphology, DGMM 2021. Lecture Notes in Computer Science(), vol 12708, 2021. 

Image Analysis Method for the Characterization of Trichoderma reesei During Fermentations, N Hardy, M Moreaud, F Ben Chaabane, Trichoderma reesei: Methods and Protocols, 119-13, 2021.

Efficient pore network extraction method based on the distance transform, A Hammoumi, M Moreaud, E Jolimaitre, T Chevalier, A Novikov, M Klotz, Artificial Intelligence and Industrial Applications. A2IA 2020. Lecture Notes in Networks and Systems, vol 144. Springer, Cham. 2021.

Quantitative performance of forward fill/flush differential flow modulation for comprehensive two-dimensional gas chromatography, A Lelevic, V Souchon, C Geantet, C Lorentz, M Moreaud,Journal of Chromatography A 1626, 2020.

Heterogeneity assessment based on average variations of morphological tortuosity for complex porous structures characterization, J Chaniot, M Moreaud, L Sorbier, D Jeulin, JM Becker, T Fournel, Image Analysis and Stereology 39 (2), 111-128, 2020.

Atomic scale insight into the formation, size, and location of platinum nanoparticles supported on γ-alumina, ATF Batista, W Baaziz, AL Taleb, J Chaniot, M Moreaud, C Legens, A Aguilar-Tapia, Ol Proux, JL Hazemann, F Diehl, C Chizallet, AS Gay, O Ersen, P Raybaud, ACS Catalysis 10 (7), 2020.

Small-angle X-ray scattering intensity of multiscale models of spheres, L Sorbier, M Moreaud, S Humbert,  Journal of Applied Crystallography 52 (6), 2019.

Investigation of the 3D crystalline network impact on the elastic properties of Semi-Crystalline Polymers from a multi-scale modelling approach, E Roguet, K Akhan, N Brusselle-Dupend, V Le Corre, M Sidhom, L Cangemi, M Moreaud, G Clavier, V Lachet, B Rousseau, Computational Materials Science 167, 77-84, 2019.

Method of segmenting the image of an object reconstructed by three-dimensional reconstruction, M Moreaud, F Wahl, US Patent 10,290,123, 2019.

Tortuosimetric operator for complex porous media characterization, J Chaniot, M Moreaud, L Sorbier, T Fournel, JM Becker, Image Analysis & Stereology 38 (1), 25-41, 2019.

Modelling of the microstructure of mesoporous alumina constrained by morphological simulation of nitrogen porosimetry, H Wang, D Jeulin, F Willot, L Sorbier, M Moreaud, Colloids and Surfaces A: Physicochemical and Engineering Aspects 553, 378-396, 2018.

Impact of Citric Acid on the Impregnation of CoMoP/γ-Al2O3 Catalysts: Time and Spatially Resolved MRI and Raman Imaging Study, L Catita, AA Quoineaud, M Moreaud, D Espinat, C Pichon, O Delpoux, Topics in Catalysis 61, 1474-1484, 2018.

Multi-scale stochastic morphological models for 3D complex microstructures, M Moreaud, J Chaniot, T Fournel, JM Becker, L Sorbier, 2018 17th Workshop on Information Optics (WIO), Quebec, QC, Canada, 2018.

ARFBF morphological analysis-Application to the discrimination of catalyst active phases, Z Tan, M Moreaud, O Alata, AM Atto, Image Analysis and Stereology 37 (1), 21-34, 2018.

Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques, G Franchi, J Angulo, M Moreaud, L Sorbier, Journal of microscopy 269 (1), 94-112, 2018.

Numerical modeling of the effective ductile damage of macroporous alumina, V Le Corre, N Brusselle-Dupend, M Moreaud, Mechanics of Materials 114, 161-171, 2017.

The reachable volume fraction in porous media in the vicinity of percolation threshold: a numerical approach used on multi-scale Boolean schemes, J Chaniot, M Moreaud, T Fournel, JM Becker, 2017 16th Workshop on Information Optics (WIO), 2017.

Advanced digital image analysis method dedicated to the characterization of the morphology of filamentous fungus, N Hardy, M Moreaud, D Guillaume, F Augier, A Nienow, C Béal, F Ben Chaabane, Journal of Microscopy 266 (2), 126-140, 2017.

Numerical simulation of hindered diffusion in γ-alumina catalyst supports, H Wang, F Willot, M Moreaud, M Rivallan, L Sorbier, D Jeulin, Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles 72 (2), 8, 2017.

BARCHAN: blob alignment for robust chromatographic analysis, C Couprie, L Duval, M Moreaud, S Hénon, M Tebib, V Souchon, Journal of Chromatography A 1484, 65-72, 2017.

Sparse stereo disparity map densification using hierarchical image segmentation, S Drouyer, S Beucher, M Bilodeau, M Moreaud, L Sorbier, Mathematical Morphology and Its Applications to Signal and Image Processing: 13th International Symposium, ISMM 2017.

A morphological approach for texture detection, application to SEM stereo reconstruction, S Drouyer, S Beucher, M Bilodeau, M Moreaud, L Sorbier, European Microscopy Congress 2016: Proceedings, 579-580, 2016.

Mean penetration depth of metals in hydrodemetallation catalysts, L Sorbier, F Bazer-Bachi, M Moreaud, V Moizan-Basle, Chemical Engineering Science 155, 186-193, 2016.

Use of the Distance Transform for Integration of Local Measurements: Principle and Application in Chemical Engineering, L Sorbier, F Bazer-Bachi, Y Blouët, M Moreaud, V Moizan-Basle, Microscopy and Microanalysis 22 (2), 422-431, 2016.

Quantitative two-dimensional (2D) morphology–selectivity relationship of CoMoS nanolayers: A combined high-resolution high-angle annular dark field scanning transmission electron microscopy (HR HAADF-STEM) and density functional theory (DFT) study, B Baubet, M Girleanu, AS Gay, AL Taleb, M Moreaud, F Wahl, V Delattre, E Devers, A Hugon, O Ersen, P Afanasiev, P Raybaud ACS Catalysis 6 (2), 1081-1092, 2016.

Modelling mesoporous alumina microstructure with 3D random models of platelets, H Wang, A Pietrasanta, D Jeulin, F Willot, M Faessel, L Sorbier, M Moreaud, Journal of microscopy 260 (3), 287-301, 2016.

ARFBF model for non stationary random fields and application in HRTEM images, Z Tan, AM Atto, O Alata, M Moreaud, 2015 IEEE International Conference on Image Processing (ICIP), 2651-2655, 2015.

Flowing bilateral filter: definition and implementations, M Moreaud, F Cokelaer, Image Analysis & Stereology 34 (2), 101-110, 2015.

Image processing for materials characterization: Issues, challenges and opportunities, L Duval, M Moreaud, C Couprie, D Jeulin, H Talbot, J Angulo, 2014 ieee international conference on image processing (icip), 4862-4866, 2014.

Non-stationary texture synthesis from random field modeling, AM Atto, Z Tan, O Alata, M Moreaud, 2014 IEEE International Conference on Image Processing (ICIP), 2014.

Fast algorithm for dilation and erosion using arbitrary flat structuring element: Improvement of urbach and wilkinson's algorithm to GPU computing, M Moreaud, F Itthirad, 2014 International Conference on Multimedia Computing and Systems (ICMCS), 2014.

Inverse problem approach for the alignment of electron tomographic series, VD Tran, M Moreaud, É Thiébaut, L Denis, JM Becker, Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles 69 (2), 279-291, 2014.

Experimental hydrodynamic study of valve trays, R Brahem, A Royon-Lebeaud, D Legendre, M Moreaud, L Duval, Chemical engineering science 100, 23-32, 2013.

Measurement of palladium crust thickness on catalysts by optical microscopy and image analysis, L Sorbier, AS Gay, A Fécant, M Moreaud, N Brodusch, Microscopy and Microanalysis 19 (2), 293-299, 2013.

Robust registration of electron tomography projections without fiducial markers, VD Tran, M Moreaud, É Thiébaut, L Dénis, JM Becker, Computational Imaging XI 8657, 190-198, 2013.

Measurement of palladium crust thickness on catalyst by EPMA, L Sorbier, AS Gay, A Fécant, M Moreaud, N Brodusch, IOP Conference Series: Materials Science and Engineering 32 (1), 012023, 2012.

TEM image analysis and modelling: application to boehmite nanoparticles, M Moreaud, D Jeulin, V Morard, R Revel, Journal of microscopy 245 (2), 186-199, 2012.

Estimations of the critical percolation threshold from the zeros of connectivity number, M Moreaud, D Jeulin, S Youssef, 3th International Congress of Stereology, Beijing, China, 2011.

Quantitative characterization of soot nanostructure from hrtem images, M Moreaud, N Lamharess, S Zinola, J Lavy, 13th International Conference of Stereology, Beijing, China, 2011.

Innovative characterizations and morphology control of γ-AlOOH boehmite nanoparticles: towards advanced tuning of γ-Al2O3 catalyst properties, M Digne, R Revel, M Boualleg, D Chiche, B Rebours, M Moreaud, B Celse, C Chaneac, J-P Jolivet, Studies in Surface Science and Catalysis 175, 127-134, 2011.

Size of boehmite nanoparticles by TEM images analysis, M Moreaud, R Revel, D Jeulin, V Morard, Image Analysis and Stereology 28 (3), 187-19, 2011.

A quantitative morphological analysis of nanostructured ceria–silica composite catalysts, M Moreaud, D Jeulin, A Thorel, JY Chane‐Ching, Journal of microscopy 232 (2), 293-305, 2008.

Analysis of the accessibility of macroporous alumino-silicate using 3D-TEM images, M Moreaud, B Celse, F Tihay, Proceedings of Materials Science & Technology 2008 Conference and Exhibition: MS&T, 2008.

Three-dimensional microtomographic study of Widmanstätten microstructures in an alpha/beta titanium alloy, N Vanderesse, E Maire, M Darrieulat, F Montheillet, M Moreaud, D Jeulin, Scripta materialia 58 (6), 512-515, 2008.

Segmentation of 2D and 3D textures from estimates of the local orientation, D Jeulin, M Moreaud, Image Analysis and Stereology 27 (3), 183-192, 2008.

Statistical representative volume element for predicting the dielectric permittivity of random media, D Jeulin, M Moreaud, 11th International Symposium on Continuum Models and Discrete Systems CMDS 11, 2007.

Percolation of random cylinder aggregates, D Jeulin, M Moreaud, Image Analysis and Stereology 26 (3), 121-127, 2007.

Percolation d'agrégats multi-échelles de sphères et de fibres–Application aux nanocomposites, D Jeulin, M Moreaud, Matériaux 2006, 341-348, 2006.

Percolation of multi-scale fiber aggregates, D Jeulin, M Moreaud, SS4G (Stereology, Spatial Statistics and Stochastic Geometry) 6th International Conference, Prague, Republique Tchèque, 2006.

Volume élémentaire représentatif pour la permittivité diélectrique de milieux aléatoires, D Jeulin, M Moreaud, Matériaux 2006.

Multi-scale simulation of random spheres aggregates-application to nanocomposites, D Jeulin, M Moreaud, 9th European Congress on Stereology and Image Analysis, Zakopane, 2005.

Mesure tridimensionnelle de champs cinématiques par imagerie volumique pour l'analyse des matériaux et des structures, M Bornert, JM Chaix, P Doumalin, JC Dupré, T Fournel, D Jeulin, É Maire, M Moreaud, H Moulinec, Instrumentation, Mesure, Métrologie 3, 43-88, 2004.