Hubert Curien Laboratory

The Hubert Curien Laboratory is a joint research unit (UMR 5516) within Jean Monnet University in Saint Etienne (UJM), the Scientific National Research Centre (CNRS) and Institut d’Optique Graduate School (IOGS). The Hubert Curien Laboratory is the most important of all Saint-Etienne’s university research Lab with more than 240 people, with strong connections with other scientific structures within the University of Lyon or at national and international levels.


The Hubert Curien laboratory is addressing scientific challenges on both fundamental and applicative aspects in (1) Optics-Photonics-Surfaces with longstanding skills on radiation/laser - matter interaction and micro and nano structuration, including ultrafast laser processing and aiming at both modifying beams to functionalize or structure the matter, and structuring matter to manipulate the light in (2) Computer science, Image and Security with an expertise in the formation, understanding and analysis of images, in machine learning and complex data analysis, as well as in hardware security.
The research activity is supported by several high-tech shared technical platforms and is developed within 6 teams: Functional materials and surfaces, Laser-Matter Interaction, Materials for Optics and Photonics in Extreme Radiative Environments, Image Science & Computer Vision, Data Intelligence, and Secure Embedded Systems & Hardware Architectures. All teams are involved in Manutech-SLEIGHT Graduate School, as described below.

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    Stéphanie Reynaud, researcher engineer at the Hubert Curien Lab © UJM
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    Hubert Curien lab (UJM, CNRS, IOGS) © @UJM
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    Functional Materials and Surfaces © Hubert Curien Laboratory
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    Laser-Matter Interaction © Hubert Curien Laboratory
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    Secure Embedded Systems & Hardware Architectures © Hubert Curien Laboratory
    LabHC_illus_team_Secure Embedded Systems & Hardware Architectures
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    Optics-photonics activities © LabHC - Jean Monnet University
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    © Hubert Curien Laboratory
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    Optics-phonotics research activities © LabHC - Jean Monnet University
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    Optics equipment © LabHC - Jean Monnet University
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    Nano Saint-Etienne Platform © LabHC - Jean Monnet University
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    Nano Saint-Etienne Platform © LabHC - Jean Monnet University
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    Laboratoire Hubert Curien © UdL
    Laboratoire Hubert Curien
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    Stéphanie Reynaud, researcher engineer at the Hubert Curien Lab © UJM
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    Yaya Lefkir, researcher engineer at the Hubert Curien lab © UJM



The Hubert Curien Laboratory is a member of three laboratories of excellence (LabEx):
  • LabEx Manutech-SISE, specialised in Surface and Interface Science and Engineering;
  • LabEx PRIMES, dedicated to research in Physics, Radiobiology, Medical Imaging and Simulation;
  • LabEx MILYON, working on problematics linked to Mathematics and Informatics, on the Lyon-Saint-Etienne site.
The Hubert Curien Laboratory contributed greatly to the creation of the EquipEx Manutech-USD (Equipment of Excellence, Ultrafast Surface Design), the LabEx Manutech-SISE and the Manutech-SLEIGHT Graduate School and are coordinating both of the latter.
The laboratory acts as an active member of the EquipEx Manutech-USD with activity transfer on laser surfaces processing and beam shaping. Strong connections and common interests with the SAINBIOSE and BiiO laboratories also exist on bio-engineering, with for instance the cofounding of the company Keranova or the recent European Innovation Council funding for the LaserImplant project. The Hubert Curien Laboratory is also a co-founder of the joint laboratory LabH6 with the company iXblue.

The Hubert Curien Laboratory participates in or leads many national ANR programs and European projects, and is a member of three CNRS research federations:
  • Inge'LySE, the Lyon - Saint-Etienne engineering research federation;
  • FRAMA, André-Marie Ampère research federation;
  • FIL, the Lyon informatics federation.
The Hubert Curien Laboratory participates in several national research groups and is coordinating the GDR APPAMAT (CNRS research group), aiming at addressing challenges at the interface of different disciplinary fields around the appearance of materials, surfaces and objects.
The laboratory is involved in many international partnerships, including the Center of Research in Photonics of the University of Ottawa (Canada), University of Berkeley's laboratories (USA), the University Nova-Gorica (Slovenia), the University of Palermo (Italy), Politecnico Bari (Italy), Max-Born Institute (Germany), Yale University (USA), University of Alberta (Canada), KU Leuven (Belgium), to cite a few.


The Manutech-SLEIGHT Graduate School covers the whole spectrum of scientific topics addressed by the Hubert Curien Laboratory, from the radiation-matter interaction and micro and nano structuration to the formation, understanding and analysis of images, machine learning, data mining, as well as hardware security. Therefore, the teams of the laboratory are involved in the three scientific axes of the graduate school.


The work of the team is centered on the structuring of materials at the subwavelength scale and their interaction with electromagnetic waves to realise optical or high-frequency devices. Multi-functional and multi-material approaches are used to address various applications: polarisation control of laser sources, data marking for identity security, photocatalytic devices for indoor treatment, solar absorbers, sensors, isolators, imaging or nondestructive control, efficient energy converter.
Such developments are based on the design and the electromagnetic modelling of the interaction between waves and micro-nano-structures. Realisations classically employ common planar photolithography and associated techniques.
  1. N. Sharma, M. Vangheluwe, F. Vocanson, A. Cazier, M. Bugnet, S. Reynaud, A. Vermeulin, N. Destouches, Laser-driven plasmonic gratings for multiple image hiding, Materials Horizons, (2019) - IF: 12.319 (Q1)
  2. M. Esposito, F. Todisco, S. Bakhti, A. Passaseo, I. Tarantini, M. Cuscunà, N. Destouches, V. Tasco, Symmetry Breaking in Oligomer Surface Plasmon Lattice Resonances, Nano Letters, (2019) - IF: 12.08 (Q1)
  3. A. Ushkov, I. Verrier, T. Kampfe, Y. Jourlin, Subwavelength diffraction gratings with macroscopic moiré patterns generated via Laser Interference Lithography, Optics Express (2020) – IF: 3.7 (Q1)
  4. L. Bsawmaii, É. Gamet, F. Royer, S. Neveu, D. Jamon, Longitudinal magneto-optical eect enhancement with high transmission through a 1D all-dielectric resonant guided mode grating, Optics Express, (2020) – IF: 3.669 (Q1)
  5. N. Sharma, N. Destouches, C. Florian, R. Serna, J. Siegel, Tailoring metal-dielectric nanocomposite materials with ultrashort laser pulses for dichroic color control, Nanoscale, vol. 11(40), pp. 18779- 18789 (2019) - IF: 6.97 (Q1)
More about the Functional Materials and Surfaces team's work


The result of interaction between energetic laser radiation and materials allows to locally deposit energy and usually leads to a permanent alteration of the material on surfaces (surface structuring) and in the bulk (3D processing). This effect is the base of current laser processing techniques. Notably on ultrashort timescales where the interaction is confined in space and time, the strong energy localisation unravels a high potential for laser structuring and fabrication. The prospect is the achievement of new levels of accuracy and reliability using a novel generation of ultrashort pulsed lasers. In this frame, the research theme “Laser-matter interaction” focuses on laser irradiation effects in condensed matter which are pertinent for material processing, functionalisation, and fabrication. The team developed pioneering activities on adaptive texturing of materials using ultrafast laser beam shaping techniques from more than 20 years.
The thrust is to investigate laser-induced phenomena on ultimate scales, spatially and temporally, and to explore the possibilities of practical applications, accompanying their transfer in industrial environments, namely in mechanics, optics, sensing, or counterfeiting.

  1. R. Stoian, J. P. Colombier, Advances in ultra- fast laser structuring of materials at the nanoscale, Nanophotonics, (2020) - IF: 7.491 (Q1)
  2. Rudenko, A. Abou-Saleh, F. Pigeon, C. Mauclair, F. Garrelie, R. Stoian, J. P. Colombier, High-frequency periodic patterns driven by non-radiative fields coupled with Marangoni convection instabilities on laser-excited metal surfaces, Acta Materialia, (2020) - IF: 7.656 (Q1)
  3. Saleh, A. Rudenko, S. Reynaud, F. Pigeon, F. Garrelie, J. P. Colombier, Sub-100 nm 2D nanopatterning on a large scale by ultrafast laser energy regulation, Nanoscale, pp. 6609-6616 (2020) - IF: 6.895 (Q1)
  4. Y. Bleu, V. Barnier, F. Christien, F. Bourquard, A. S. Loir, F. Garrelie, C. Donnet, Dynamics of carbon dilusion and segregation through nickel catalyst, investigated by in-situ XPS, during the growth of nitrogen- doped graphene, Carbon, vol. 155(), pp. 410-420 (2019) - IF : 8.821 (Q1)
  5. R. Stoian, M. Bhuyan, A. Rudenko, J. P. Colombier, G. Cheng, High-resolution material structuring using ultrafast laser non-diractive beams, Advances in Physics-X, vol. 4(1), pp. 1659180 (2019) - IF: 6.805 (Q1)
  6. Rudenko, C. Mauclair, F. Garrelie, R. Stoian, J. P. Colombier, Self-organization of surfaces on the nanoscale by topography- mediated selection of quasi-cylindrical and plasmonic waves, Nanophotonics, (2019) - IF: 7.491 (Q1)


The objective of this team is a better understanding of the fundamental mechanisms of degradation in harsh environments of optical materials, components and optical and photonic systems. The knowledge and know-how acquired, through this multi-physics approach combining experiments and multi-scale simulations, are used to control these mechanisms and thus optimise the responses under radiative sollicitation according to the targeted environments and applications, such as nuclear instrumentation, space radiation or in situ dosimetry. This fundamental research has strong application benefits, facilitating the qualification and rapid deployment of breakthrough solutions in the most extreme environments.
  1. Lagrange et al. 2020, Unveiling the b Pictoris system, coupling high contrast imaging, in- terferometric, and radial velocity data, Astronomy and Astrophysics - A&A, vol. 642(), pp. A18 (2020) - IF: 5.636 (Q1)
  2. L. Giacomazzi, L. Martin-Samos, A. Alessi, N. Richard, A. Boukenter, Y. Ouerdane, S. Girard, M. Valant, S. De Gironcoli, v-P2O5 micro-clustering in P-doped silica studied by a first-principles Raman investigation, Scientific Reports, vol. 9(1), (2019) - IF: 3.998 (Q1)
  3. C. Hoehr, A. Morana, O. Duhamel, B. Capoen, M. Trinczek, P. Paillet, C. Duzenli, M. Bouazaoui, G. Bouwmans, A. Cassez, Y. Ouerdane, A. Boukenter, H. El Hamzaoui, S. Girard, novel Gd 3+ -doped silica-based optical ber material for dosimetry in proton therapy, Scientific Reports, (2019) - IF: 3.998 (Q1)
  4. T. Blanchet, R. Desmarchelier, A. Morana, A. Boukenter, Y. Ouerdane, E. Marin, G. Laffont, S. Girard, Radiation and High Tempera- ture Effects on Regenerated Fiber Bragg Grating, Journal of Lightwave Tech- nology, vol. 37(18), pp. 4763-4769 (2019) - IF: 4.162 (Q1)
  5. M. Royon, E. Marin, S. Girard, A. Boukenter, Y. Ouerdane, R. Stoian, X-ray preconditioning for enhancing refractive index contrast in femtosecond laser photoinscription of embedded waveguides in pure silica, Optical Materials Express, vol. 9(1), pp. 65 (2019) - IF: 3.064 (Q1)
  6. C. Sabatier, S. Girard, L. Mescia, A. Ladaci, T. Robin, B. Cadier, A. Boukenter, Y. Ouerdane, E. Marin, Combined Experimental and Simulation Study of the Fiber Composition Effects on its Brillouin Scat- tering Signature, Journal of Lightwave Technology, (2019) - IF: 4.162 (Q1)
More about the MOPERE team's work


Images and videos as signals carrying information in the (near) visible domain are useful to humans in order to communicate, see beyond eye-scale, learn and make decision. Digital means promote the development of ever more efficient systems. The Image Science and Computer Vision team forms a chain of skills in image processing and analysis, gathering the physical and semantic approaches. The team investigates main links of the image chain: (i) image attributes and reproduction (modeling and metrology of optical surfaces), (ii) imaging systems (image formation, restoration and reconstruction), (iii) image interpretation \ understanding (multidimensional analysis and machine learning).

  1. C. Rambour, L. Denis, F. Tupin, H. Oriot, Introducing spatial regularization in SAR tomography reconstruction, IEEE Transactions on Geoscience and Remote Sensing, (2020) - IF : 5.855 (Q1)
  2. O. Flasseur, L. Denis, É. Thiébaut, M. Langlois, PACO ASDI: an algorithm for exoplanet detection and characterization in direct imaging with integral field spectrographs, Astronomy and Astrophysics - A&A, vol. 637(), pp. A9 (2020) - IF : 5.636 (Q1)
  3. F. GERENTON, J. Eymard, S. Harrison, R. Clerc, D. Munoz, Analysis of edge losses on silicon heterojunction half solar cells, Solar Energy Materials and Solar Cells, vol. 204(), pp. 110213 (2020) - IF : 6.984 (Q1)
  4. HAMMOUMI, M. Moreaud, C. Ducottet, S. Desroziers, Adding geodesic information and stochastic patch-wise image pre- diction for small dataset learning, Neurocomputing, (2020) - IF : 4.438 (Q1)
  5. Reynaud, R. Clerc, P. Lechêne, M. Hebert, A. Cazier, A. Arias, Evaluation of indoor photovoltaic power production under direc- tional and dffuse lighting conditions, Solar Energy Materials and Solar Cells, vol. 200(), pp. 110010 (2019) - IF : 6.019 (Q1)
  6. R. Sahli, G. Pallares, A. Papangelo, M. Ciavarella, C. Ducottet, N. Ponthus, J. Scheibert, Shear-Induced Anisotropy in Rough Elastomer Con- tact, Physical Review Letters, vol. 122(21), pp. 214301 (2019) - IF : 8.385 (Q1)
More about the Image Science and Computer Vision team's work


Data intelligence is about interacting with data in rich, semantically meaningful ways, going beyond search to create the path from data to knowledge. The Data Intelligence team explores two main aspects of Data Intelligence: Statistical Machine Learning (metric Learning, representation learning, transfer learning and domain adaptation, optimal transport, PAC-bayesian theory), and Complex Data Analysis (structured data mining on graphs, texts and social networks, data mining for image and video analysis, heterogeneous document modeling). Through solid partnerships, the team has developed a strong expertise in fraud and anomaly detection requiring the design of advanced machine learning models to deal with highly imbalanced datasets.

  1. P. Germain, A. Habrard, F. Laviolette, E. Morvant, PAC-Bayes and Domain Adaptation, Neurocomputing, vol. 379(), pp. 379- 397 (2020) - IF : 4.438 (Q1)
  2. S. Dhouib, I. Redko, C. Lartizien, Margin-aware Ad- versarial Domain Adaptation with Optimal Transport, Thirty-seventh International Conference on Machine Learning, Vienne, Austria (2020) - CORE Ranking : A*
  3. T. Kerdoncuff, R. Emonet, M. Sebban, Metric Learn- ing in Optimal Transport for Domain Adaptation, International Joint Conference on Artificial Intelligence, Kyoto, Japan (2020) - CORE Ranking : A*
  4. Dulac, E. Gaussier, C. Largeron, Mixed-Membership Stochastic Block Models for Weighted Networks, Conference on Uncertainty in Artificial Intelligence (UAI), Toronto, Canada (2020) - CORE Ranking : A*
  5. V Titouan, I Redko, R Flamary, N Courty, CO-Optimal Transport, Advances in Neural Information Processing Systems 33 (NeurIPS) (2020) - CORE Ranking : A*
  6. J. Tissier, C. Gravier, A. Habrard, Near-lossless Binariza- tion of Word Embeddings, 33rd AAAI Conference on Artifcial Intelligence (AAAI-19), Honolulu, HI, United States (2019) - CORE Ranking : A*
More about the Data Intelligence team's work


The SESAM team aims at studying hardware security which concerns different fields: data security (confidentiality, integrity, authentication and non-repudiation), system security (user authentication, guaranteed quality of services, the war against malicious hardware) and the protection of intellectual property (IP protection, the war against counterfeiting, illegal copying and theft).
The SESAM team explores four main aspects of hardware security: (i) the random number generation and physical unclonable function implementation in logic devices, (ii) the design of hardware architectures resistant to passive and active cryptographic attacks, (iii) the secure implementations of post-quantum schemes, (iv) the security of systems on chip (SoC).
  1. L. Bossuet, C. Mancillas-Lopez, B. Ovilla-Martinez, Pipelined Hardware Implementation of COPA, ELmD, and COLM, IEEE Transactions on Computers, vol. 69(10), pp. 1533- 1543 (2020) - IF : 2.711
  2. E. Benhani, L. Bossuet, A. Aubert, The Security of ARM TrustZone in a FPGA-based SoC, IEEE Transactions on Computers, pp. 1-1 (2019) - IF : 3.131 (Q1)
  3. D. Bellizia, O. Bronchain, G. Cassiers, V. Grosso, C. Guo, C. Momin, O. Pereira, T. Peters, F. X. Standaert, Mode-Level vs. Implementation-Level Physical Security in Symmetric Cryptography A Practical Guide Through the Leakage-Resistance Jungle, Advances in Cryptology (CRYPTO) conference, Santa Barbabra, United States (2020) CORE Ranking : A*
  4. B. Colombier, N. Bochard, F. Bernard, L. Bossuet, Backtracking Search for Optimal Parameters of a PLL-based True Random Number Generator, 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 1-6, Grenoble, France (2020) - GDR SoC2 Ranking : A*
  5. T. Simon, L. Batina, J. Daemen, V. Grosso, P. Massolino, K. Papagiannopoulos, F. Regazzoni, N. Samwel, Friet: an Authenticated Encryption Scheme with Built-in Fault Detection, Advances in Cryptology – EUROCRYPT 202039th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Zagreb, Croatia, May 10–14, 2020, Proceedings (pp. 581-611). (2020) - CORE Ranking : A*
More about the SESAM team's work