Submitted - Under review

[+] Corrochano, A., Freitas, R.S.M., Parente, A., Le Clainche, S., A predictive physics-aware hybrid reduced order model for reacting flows, arXiv:2301.09860, 2023.

[+] Foggi Rota, G., Amor, C., Le Clainche, S., Rosti, M.,Elastic turbulence in planar channel flows - Turbulence with no drag and enhanced mixing, arXiv:2310.05340, 2023.

[+] Hetherington, A., Le Clainche, S., Low-cost singular value decomposition with optimal sensor placement, arXiv:2311.09791, 2023.

[+] Bell-Navas, A., Groun, N., Villalba-Orero, M., Lara-Pezzi, E., Garicano-Mena, J., Le Clainche, S., Automatic Cardiac Pathology Recognition in Echocardiography Images Using Higher Order Dynamic Mode Decomposition and a Vision Transformer for Small Datasets, arxiv, 2024.

[+] Groun, N., Villalba-Orero, M., Casado-Martín, L., Lara-Pezzi, E., Valero, E., Garicano-Mena, J., Le Clainche, S., Data-Driven Modal Decomposition techniques: Effective Tool For Image Classification Improvement, arxiv, 2024.

[+] Nagargoje, M., Lazpita, E., Garicano-Mena, J., Le Clainche, S., Review on vortex dynamics in the left ventricle as an early diagnosis marker for heart diseases and its treatment outcomes, arxiv, 2024.

[+] Abadía-Heredia, R., Corrochano, A., López-Martín, M., Le Clainche, S., Exploring the efficacy of a hybrid approach with modal decomposition over fully deep learning models for flow dynamics forecasting, arXiv:2404.17884 , 2024.

[+] Tagilaferro, S., Corrochano, A., Marchetti, P., Marcon, A., Le Clainche, S., A new method based on physical patterns to impute aerobiological datasets, 2024.

[+] Giral, F., Gómez, I., Le Clainche, S., Intercepting Unauthorized Aerial Robots in Controlled Airspace Using Reinforcement Learning, arXiv:2407.06909, 2024.

2024

99) Hetherington, A., Corrochano, A., Abadía-Heredia, R., Lazpita, E., Muñoz, E., Díaz, E., Maiora, E., López-Martín, M., Le Clainche, S., ModelFLOWs-app: data-driven post-processing and reduced order modelling tools, Comp. Phys. Commu., 301, 109217, 2024.

98) Hetherington, A., Serfaty, D., Corrochano, A., Soria, J., Le Clainche, S., Data repairing and resolution enhancement using data-driven modal decomposition and deep learning, Exp. Therm. Fluid  Sci., 157, 111241, 2024.

97) Amor, C., Corrochano, A., Foggi Rota, G., Rosti, M., Le Clainche, S., Coherent structures in elastic turbulent planar jets, J. Phys. Conf. ser., 2753, 012020, 2024.

96) Giral, F., Gómez, I., Le Clainche, S., Control and Motion Planning of Fixed-Wing UAV through Reinforcement Learning , Res. in Eng., 102379, 2024.

95) Corrochano, A., D'Alessio, G., Parente, A., Le Clainche, S., Hierarchical Higher-Order Dynamic Mode Decomposition for Clustering and Feature Selection, Comp. Math. with Appl.,158, 36-45, 2024. 

94) Lazpita, E., Garicano-Mena, J., Paniagua, G., Le Clainche, S., Valero, E., Hierarchical Higher-Order Dynamic Mode Decomposition for Clustering and Feature Selection, Comp. Math. with Appl.,158, 36-45, 2024. 

93) Martin, J.A., Rosti, M., Le Clainche, S., Navarro, R., Vinuesa, R., Direct Numerical Simulations of a novel device to fight virus airborne transmission , Phys. Fluids, 36 (2), 023352, 2024.

92) Díaz, P., Corrochano, A., López-Martín, M., Le Clainche, S., Deep Learning combined with singular value decomposition to reconstruct databases in fluid dynamics, Exp. Syst. Appl., 238, B, 121924, 2024.

91) Braun, J.,  Rahbari, I., Paniagua, G.,Addo, P.A., Garicano-Mena, J., Valero, E., Le Clainche, S., Experimental Characterization of Shock-Separation Interaction Over Wavy-Shaped Geometries Through Feature Analysis, Exp. Therm. Fluid Sc., 111021, 2024.

2023

90) Corrochano, A., Sierra, J., Martín, J.A., Fabre, F., Le Clainche, S., Mode selection in concentric jets. The steady-steady 1: 2 resonant mode interaction with O (2) symmetry, J. Fluid Mech., 971, A30, 2023.

89) Muñoz, E., Dave, H., D’Alessio, G., Parente, A., Le Clainche, S., Extraction and analysis of flow features in planar synthetic jets using different machine learning techniques, Phys. Fluids, 094107, 2023. 

88) Martínez-Sánchez, A., López, E., Le Clainche, S., Lozano-Durán, A., Srivastava, A. & Vinuesa, R., Causality analysis of large-scale structures in the flow around a wall-mounted square cylinder, J. Fluid Mech., 967, A1, 2023.

87) Mata, L., Abadía-Heredia, R., López-Martín, M., Pérez, J.M., Le Clainche, S., Forecasting through deep learning and modal decomposition in multi-phase concentric jets, Exp. Syst. Appl., 120817, 2023.

86) Groun, N., Begiashvili, B., Valero, E., Garicano-Mena, J., Le Clainche, S., Higher order dynamic mode decomposition beyond aerospace engineering, Res. in Eng., 20, 101471, 2023. 

85) Atzori, M., Torres, P., Vidal, A., Le Clainche, S., Hoyas, S., Vinuesa, R., High-resolution large-eddy simulations of simplified urban flows, Phys. Rev. Fluids, 8, 063801, 2023.

84) Zormpa, M., Le Clainche, S., Ferrer, E., Vogel, C.R., Willden, R.H.J., Dynamic mode decomposition of merging wind turbine wakes, J. Phys.: Conf. Ser., 2505, 012020, 2023. 

83) Begiashvili, B., Groun, N., Garicano-Mena, J., Le Clainche, S., Valero, E., Data-driven modal  decomposition methods as feature detection techniques for flow problems: a critical assessment, Phys. of Fluids, 35, 041301, 2023. 

82) Le Clainche, S., Ferrer, E., Gibson, S., Cross, L., Parente, A., Vinuesa, R., Improving aircraft performance using machine learning: a review , Aerosp. Sci. Tech.,108354, 2023.

81) Corrochano, A., D’Alessio, G., Parente, A., Le Clainche, S., Higher order dynamic mode decomposition to model reactive flows, Int. J. Mech. Sci., 249, 108219, 2023.

80) Amor, C., Schlatter, P., Vinuesa, R.,Le Clainche, S., Higher order dynamic mode decomposition on-the-fly: a low-order algorithm for complex fluid flows, J. Comp. Phys.,475, 111849, 2023. 

79) Martínez-Sánchez, A., Lazpita, E., Corrochano, A., Le Clainche, S., Hoyas, S., Vinuesa, R., Datadriven assessment of arch vortices in simplified urban flows, Int. J. Heat Fluid Flow,100, 109101, 2023. 

78) Pujante-Martínez, L., Le Clainche, S., Pérez, J.M., Ferrer, E., Learning fluid dynamics and the principles of flight: from primary school to STEM degrees , Europ. J. Phys., 44(4), 045002, 2023. 

2022

77) Corrochano, A., Le Clainche, S., Structural sensitivity in non-linear flows using direct solutions, Comp. Math. with Appl.,128, 69-78, 2022. 

76) Groun, N.,Villalba-Orero, M., Lara-Pezzi, E., Valero, E., Garicano-Mena, J., Le Clainche, S., A novel data-driven method for the analysis and reconstruction of cardiac cine MRI, Comp. Biolog. Medic.,151, 106317, 2022. 

75) Le Clainche, S., Rosti, M., Brandt, L., O., ‘A data-driven model based on modal decomposition: application to the turbulent channel flow over an anisotropic porous wall’, J. Fluid Mech., 939, 2022. 

74) Evazi, H., Le Clainche, S., Hoyas, S., Vinuesa, R., ‘Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows’, Exp. Syst. Appl., 202, 117038, 2022. 

73) Muñoz, E., Le Clainche, S., ‘On the topology patterns and symmetry breaking in two planar synthetic jets’, Phys. Fluids 34, 024103, 2022. 

72) Beltrán, V., Le Clainche, S., Vega, J.M., ‘An adaptive data-driven reduced order model based on higher order dynamic mode decomposition’, J. Sci. Comp., 92 (12), 2022. 

71) Abadía-Heredia, R., Lopez-Martin, M., Carro, B., Arribas, J.I., Pérez, J.M., Le Clainche, S., A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures, Exp. Syst. Appl., 187, 115910, 2022. 

70) Groun, N.,Villalba-Orero, M., Lara-Pezzi, E., Valero, E., Garicano-Mena, J., Le Clainche, S., Higher order dynamic mode decomposition: From fluid dynamics to heart disease analysis, Comp. Biolog. Medic.,144, 105384, 2022. 

69) Lazpita, E., Martínez-Sánchez, A., Corrochano, A., Hoyas, S., Le Clainche, S., Vinuesa, R., On the generation and destruction mechanisms of arch vortices in urban fluid flows, Phys. Fluids, 34(5), 051702, 2022. 

68) Kou, J., Le Clainche, S., Ferrer, E., ‘Data-driven eigensolution analysis based on a spatio-temporal Koopman decomposition, with applications to high order methods’, J. Comp. Phys., 449, 110798, 2022. 

67) Kou, J., Hurtado-de-Mendoza, A., Joshi, S., Le Clainche, S., Ferrer, E., ‘Eigensolution analysis of immersed boundary method based on volume penalization: applications to high-order schemes’, J. Comp. Phys., 449, 110917, 2022. 

66) Corrochano, A., Neves, A.F., Khanal, B., Le Clainche, S., Lawson, N.J., ‘DES of a Slingsby Firefly Aircraft: Unsteady Flow Feature Extraction using POD and HODMD’, J. Aerosp. Eng. 35 (5), 2022. 

65) Pérez, J.M., Sastre, F., Le Clainche, S., Vega, J.M., Velázquez, A., ‘Reconstruction of threedimensional field from two-dimensional PIV data out of sync’, Exp. Therm. Fluid Sci., 133, 110523, 2022. 

64) Mamchur, D., Peksa, J., Le Clainche, S., Vinuesa, R., ‘Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection’, Sensors, 22(6), 2121, 2022. 

63) Amor, C., Pérez, J.M., Schlatter, P., Vinuesa, R., Le Clainche, S., ‘Modeling the Turbulent Wake behind a Wall-Mounted Square Cylinder’, Logic Journal of the IGPL, 30(2), 263-373,2022 

62) Mamchur, D., Peksa, J., Le Clainche, S., Vinuesa, R., Analysis of the state of the art on nonintrusive object-screening techniques, Przeglad Elektrotechniczny, 98 (2), 168-173, 2022. 

2021

61) López-Martín, Le Clainche, S., Carro, B., ‘Model-free short-term fluid dynamics estimator with a deep 3D-convolutional neural network’, Exp. Syst. Applic., 177, 114924, 2021. 

60) Méndez, C., Le Clainche, S., Moreno, R., Vega, J.M., ‘A new method to predict flutter’, Aerosp. Sci. Tech., 114, 106749, 2021. 

59) Abadía-Heredia, R., Pariente, A., Pérez, J.M., Le Clainche, S., ‘Tortuosity in tumours: the need of combining multiphase flows with machine learning tools’, Res. in Eng., 11, 100234, 2021. 

58) Corrochano,A., Xavier,D., Schlatter, P., Vinuesa, R., Le Clainche, S., Flow Structures on a Planar Food and Drug Administration (FDA) Nozzle at Low and Intermediate Reynolds Number, Fluids, 6(1), 4, 2021. 

57) Torres, P., Le Clainche, S., Vinuesa, R. ‘On the experimental, numerical and data-driven methods to study urban flow’, Energies, 14(5), 1310, 2021. 

56) Muñoz-Salamanca, E., Le Clainche, S., 'Flow Patterns in Double Planar Synthetic Jets', International Symposium on Unmanned Systems and The Defense Industry 2021 (ISUDEF’21), International Sustainable Aviation and Energy Research Society, Springer, ISBN: 978-605-80140-9-1 chapter 27 

55) Corrochano, A., D' Alessio, G., Parente, A., Le Clainche, S., 'Higher-Order Dynamic Mode Decomposition to Model Reacting Flows', International Symposium on Unmanned Systems and The Defense Industry 2021 (ISUDEF’21), International Sustainable Aviation and Energy Research Society, Springer, ISBN: 978-605-80140-9-1 chapter 37

2020

54) Le Clainche, S., Pérez, J.M., Vega, J.M., Soria, J., ‘Near and far field flow structures in a zero-netmass flux jet’, Aerosp. Sci. Tech., 105, 105921, 2020. 

53) Le Clainche, S., Rosti, M., Brandt, L., ‘Flow structures and deep learning in an anisotropic porous wall’, J. of Physics: Conf. Ser., 1522:012016, 2020. 

52) Le Clainche, S., Izbassarov, D., Rosti, M., Brandt, L., Tammisola, O., ‘Coherent structures in the turbulent channel flow of an elastoviscoplastic fluid’, J. Fluid Mech., 888, 2020. 

51) Pérez, J.M., Le Clainche, S., Vega, J.M., ‘Reconstruction of three-dimensional fields from twodimensional data’, J. Comp. Phys., 407:109239, 2020 

50) Martín, J.A., Corrochano, A., Sierra, J. Fabre, D., Le Clainche, S., ‘Modelling double concentric jets using linear and non-linear approaches’, 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), Advances in Intelligent Systems and Computing, vol. 1268, 2021, Springer,doi: 10.1007/978-3-030-57802-2_43. ISBN: 978-3-030-57802-2 

49) Pérez, J.M., Le Clainche, S., Vega, J.M., ‘HODMD analysis in a forced flow over a backward-facing step by harmonic perturbations’, 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), Advances in Intelligent Systems and Computing, Springer, vol. 1268, 2021,Springer, doi: 10.1007/978-3-030-57802-2_45, ISBN: 978-3- 030-57802-2 

2019

48) Beltrán, V., Méndez, C., Le Clainche, S., Vega, J.M., ‘Wake interactions in multibody configurations with different shape’, Aerospace Science and Technology, Vol. 95, 105428, 2019. 

47) Le Clainche, S., ‘Prediction of the Optimal Vortex in Synthetic Jets’, Energies, Vol. 12 (9), 2019. 

46) Le Clainche, S., Mao, X., Vega, J.M., ‘Traveling waves describing the wake of a wind turbine’, Wind Energy, Vol. 22 (7), 922-931, 2019. 

45) Le Clainche, S., Han, Z.H., Ferrer, E. ‘An alternative method to study cross-flow instabilities based on high order dynamic mode decomposition’, Phys. Fluids, Vol. 31 (9), 094101, 2019. 

44) Palomo, I., Pérez, J.M., Le Clainche, S., ‘Topological variations in the optimal vortex due to the interaction of two concentric synthetic jets’, Results in Engineering, DOI. 10.1016/j.rineng.2019.100023, 2019. 

43) Wu, M., Han, Z., Nie, H., Song, W., Le Clainche, S., Ferrer, E., ‘A transition prediction method for flow over airfoils based on high-order dynamic mode decomposition’, Chinese Journal of Aeronautics, DOI. 10.1016/j.cja.2019.03.020, 2019. 

42) Méndez, C., Le Clainche, S., Vega, J.M., Moreno-Ramos, R., Taylor, P., Aeroelastic flutter flight test data analysis using a high order dynamic mode decomposition approach, Proceedings of AIAA Scitech 2019, San Diego, California, USA, AIAA paper 2019-1531, 2019. DOI: 10.2514/6.2019-1531 

41) Bell, E., Méndez, C., Le Clainche, S., Vega, J.M., A reduced order model to create two-dimensional flow fields from uni-dimensional data, Proceedings of AIAA Scitech 2019, San Diego, California, USA, AIAA paper 2019-2361, 2019. https://doi.org/10.2514/6.2019-2361 

40) Le Clainche, S., Vega, J.M., ‘A review on Reduced Order Modeling Using DMD-based Method’, IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22– 25, 2018. IUTAM Bookseries, Springer. Vol. 36, 55-66, 2019. Springer, https://doi.org/10.1007/978- 3-030-21013-7_4 

39) Le Clainche, S., ‘An Introduction to Some Methods for Soft Computing in Fluid Dynamics’, 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), Advances in Intelligent Systems and Computing, Springer, Vol. 950, 557-566, 2019. Springer, DOI: 10.1007/978-3-030-20055-8_53 

38) Amor, C., Pérez, J.M., Schlatter, P., Vinuesa, R., Le Clainche, S., ‘Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder’, 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), Advances in Intelligent Systems and Computing, Springer, Vol. 950, 577-586, 2019. DOI: 10.1007/978-3-030- 20055-8_55 

37) Pérez, J.M., Le Clainche, S., Vega, J.M., ‘Generating Three-Dimensional Fields from TwoDimensional Soft Computing Strategies.’, 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), Advances in Intelligent Systems and Computing, Springer, Vol. 950, 587-595, 2019. https://doi.org/10.1007/978-3-030-20055-8_56 

36) Beltrán, V., Le Clainche, S., Vega, J.M., ‘A data-driven ROM based on HODMD’, 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), Advances in Intelligent Systems and Computing, Springer, Vol. 950, 567-576, 2019. https://doi.org/10.1007/978-3-030-20055-8_54 

35) Ferrer, E., Le Clainche, S., ‘Simple models for cross flow turbines’, Recent advances in CFD for Wind and Tidal Offshore Turbines, Springer, 83-93, 2019. DOI: 10.1007/978-3-030-11887-7_1 

34) Le Clainche, S., Vega, J.M., Mao, X., Ferrer, E., ‘A review on two methods to detect spatio-temporal patterns in wind turbines’, Recent advances in CFD for Wind and Tidal Offshore Turbines, Springer, 83- 93, 2019. DOI:10.1007/978-3-030-11887-7_8 

2018

33) Le Clainche, S., Vega, J.M., ‘Analyzing Nonlinear Dynamics via Data-Driven Dynamic Mode Decomposition-Like Methods’, Complexity, Vol. 6920783(1):21, 2018. 

32) Le Clainche, S., Moreno, R., Taylor, P., Vega, J.M., ‘A new robust method to study flight flutter testing’, J. of Aircraft, Vol. 56 (1), 1-8, 2018. 

31) Le Clainche, S., Vega, J.M., ‘Spatio-Temporal Koopman Decomposition’, J. of Nonlin. Sci. Vol. 28 (3), 1-50, 2018 

30) Le Clainche, S., Ferrer, E., ‘A reduced order model for temporal forecasting of flows around vertical axis wind turbines’, Energies, Vol. 11(3), 566, 2018. 

29) Le Clainche, S., Lorente, L., Vega, J.M., ‘Wind predictions upstream wind turbines from a LiDAR database’, Energies, Vol. 11(3), 543, 2018 

28) Le Clainche, S., Pérez, J.M., Vega, J.M., ‘Spatio-temporal flow structures in the three-dimensional wake of a circular cylinder’, Fluid Dynamic Research, Vol. 50 (5), 051406, 2018 

27) Kou, J., Le Clainche, S., Zhang, W., ‘A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion’, Physics of Fluids, Vol. 30, 016103, 2018. 

26) Le Clainche, S., Wu, M., Han, Z., Ferrer, E. ‘An alternative method to calculate cross-flow instabilities’, Proceedings of 2018 Fluid Dynamics Conference, Atlanta, GA, USA, AIAA paper 2018- 3700, 2018. https://doi.org/10.2514/6.2018-3700 

25) Beltrán, V., Le Clainche, S., Vega, J.M., ‘Temporal extrapolation of quasi-periodic solutions via DMD-like methods’, Proceedings of 2018 Fluid Dynamics Conference, Atlanta, GA, USA, AIAA paper 2018-3092, 2018. https://doi.org/10.2514/6.2018-3092 

24) Beltrán, V., Le Clainche, S., Vega, J.M., ‘Characterization of the wake past a two-dimensional multibody cylinder arrangement’, Proceedings of 2018 AIAA Aerospace Sciences Meeting, Kissimmee, Florida, USA, AIAA paper 2018-0825, 2018. https://doi.org/10.2514/6.2018-0825 

23) Viturro, M., Le Clainche, S., Vega, J.M., Soria, J., ‘The influence of the cavity in the flow structures of a zero-net-mass-flux jet’, Proceedings of the 2018 Fluid Dynamics Conference, Atlanta, Georgia, USA, AIAA paper 2018-4037, 2018. DOI: https://doi.org/10.2514/6.2018-4037 

22) Ramos, G., Beltrán, V., Le Clainche, S., Ferrer, E., Vega, J.M., ‘Flow structures in the turbulent wake of a cross-flow wind turbine’, Proceedings of the 2018 Wind Energy Symposium, Kissimmee, Florida, USA, AIAA paper 2018-0253, 2018. DOI: 10.2514/6.2018-0253 

21) S. Le Clainche, J.M. Pérez, E. Ferrer, “A short guide linking the first course of mathematics for engineering and computational fluid dynamics”, 10th International Conference on Education and New Learning Technologies, 2-4 July, 2018, Palma, Spain. EDULEARN-2018, pp. 648-653. ISBN: 978-84-09-02709-5.  DOI: 10.21125/edulearn.2018.0251,

20) J.M. Pérez, S. Le Clainche, R. Corral, ‘Physical approach of computational fluid dynamics for undergraduate engineering students’, 10th International Conference on Education and New Learning Technologies, 2-4 July, 2018, Palma, Spain. EDULEARN-2018, pp. 638-647, ISBN: 978-84-09-02709-5, DOI: 10.21125/edulearn.2018.0250.

2017

19) Le Clainche, S., Vega, J.M., ‘Higher order dynamic mode decomposition to identify and extrapolate flow patterns’, Physics of Fluids, Vol. 29 (8), 084102, 2017. 

18) Le Clainche, S., Vega, J.M., Soria, J., ‘Higher order dynamic mode decomposition of noisy experimental data: The flow structure of a zero-net-mass-flux jet’, Exp. Thermal and Fluid Sci.,Vol. 88, 336-353, 2017. 

17) Le Clainche, S., Vega, J.M., ‘Higher order dynamic mode decomposition’, SIAM J. of Applied Dynamical Systems, Vol. 16(2), 882-925, 2017. 

16) Le Clainche, S., Varas, F., Vega, J.M., ‘Accelerating oil reservoir simulations using POD on the fly’, Int. J. Num. Meth. Eng., Vol.: 110 (1), 79-100, 2017. 

15) S. Le Clainche, J.M. Pérez, E. Ferrer, “Mathematics applied to engineering processes: a practical guide to increase students' motivation”, 9th International Conference on Education and New Learning Technologies, 3-5 July, 2017, Spain. EDULEARN-2017, pp. 1841-1850. ISBN: 978-84-697-3777-4. DOI: 10.21125/edulearn.2017.1389.

14) Le Clainche, S., Sastre, F., Vega, J.M., Velázquez, A., ‘Higher order dynamic mode decomposition applied to study flow structures in noisy experimental data’, Proceedings of 47th AIAA Fluid Dynamics conference, Denver, CO, USA, AIAA paper 2017-3304, 2017. https://doi.org/10.2514/6.2017-3304 

13) Pérez, J.M., Le Clainche, S., Vega, J.M., ‘Alternative three-dimensional instability analysis of the wake of a circular cylinder’, Proceedings of 8th AIAA Theoretical Fluid Mechanics Conference, Denver, CO, USA, AIAA paper 2017-4021, 2017. https://doi.org/10.2514/6.2017-4021 

2016-2012

12) Le Clainche, S., Rodriguez, D., Theofilis, V., Soria, J., ‘On the formation of the three-dimensional structures in the hemisphere-cylinder’, AIAA Journal, Vol. 54 (12), 3884-3894, 2016. 

11) Le Clainche, S., Rodriguez, D., Theofilis, V., Soria, J.,’ Flow around a hemisphere-cylinder at high angle of attack and low Reynolds number. Part II: POD and DMD applied to reduced domains’, Aerospace Sciences and Technology, Vol. 44, 88-100, 2015. 

10) Le Clainche, S., Li, J. I., Theofilis, V., Soria, J., ‘ Flow around a hemisphere-cylinder at high angle of attack and low Reynolds number. Part I: experimental and numerical investigation’, Aerospace Sciences and Technology, Vol.: 44, 77-87, 2015. 

9) Ferrer, E., Le Clainche, S., ‘Flow scales in Cross-Flow Turbines’, CFD for Wind and Tidal Offshore Turbines. Springer. Vol. 239: 1-11, 2015. https://doi.org/10.1007/978-3-319-16202-7_1 

8) S. Le Clainche, M. Schlapkohl, V. Theorilis, H. Wei, J.A. Tendero-Ventana, Q. Liu, J.M. Pérez, ‘Wind tunnel experiments to teach physics’.  6th International Conference on Education and New Learning Technologies, 7-9 July, 2014, Barcelona, Spain. EDULEARN-2014, pp- 3441-3449. ISBN: 978-84-617-0557-3.

7) Le Clainche, S., Parente, A., Benocci, C., ‘Principal Component Analysis on a LES of a squared ribbed channel’, International Joint Conference SOCO’13-CISIS’13-ICEUTE’13, Advances in Intelligent and Soft Computing, Springer, Vol.239: 259-268, 2013. https://doi.org/10.1007/978-3-319-01854- 6_27 

6) Paredes P., Hermanns, M., Le Clainche, S., Theofilis, V., ‘Order 10^4 speed up in global linear instability analysis using matrix formation’, Computer Methods in Applied Mechanics and Engineering, Vol. 253, 287-304, 2013. 

5) Le Clainche, S., Gómez, F., Li, I., Soria, J., Theofilis, V., ‘Structural analysis on a hemisphere-cylinder at moderate Reynolds number at high angle of attack’, Proceedings of 51 st AIAA Aerospace Sciences Meeting, Grapevine, TX, USA, AIAA paper 2013-0387, 2013. https://doi.org/10.2514/6.2013-387 

4) Gómez, F., Le Clainche, S., Paredes, P., Hermanns, M., Theofilis, V., ‘Four Decades of Studying Global Linear Instability: Progress and Challenges’, AIAA Journal, Vol. 50, 2731 – 2743, Year: 2012. 

3) Le Clainche, S., Li, J., Theofilis, V., Soria, J., ‘Time-resolved Particle Image Velocimetry and structural analysis on a hemisphere-cylinder at low Reynolds numbers and large angle of incidence’, Proceedings of 42nd AIAA Fluid Dynamics Conference and Exhibit, New Orleans, LA, USA, AIAA paper 2012-3275, 2012. https://doi.org/10.2514/6.2012-3275 

2) Theofilis, V., Le Clainche, S., ‘Global Linear Instability at the Dawn of its 4th Decade: A List of Challenges (A Practical Guide on how to Contain the Euphoria and Avoid the Oversell)’, Proceedings of 6th AIAA Theoretical Fluid Mechanics Conference, Honolulu, HI, USA, AIAA paper 2011-3291, 2011. https://doi.org/10.2514/6.2011-3291 

1) Foures, D., Le Clainche, S., Semeraro, O., ‘Optimal wind farm design using derivative-free optimization methods’, 89th ERCOFTAC Bulletin, Vol. 89: 11-14, 2011. 

2024 Hybrid reduced order models grounded in physics. Advancing fluid and soft-matter dynamics with machine learning and data science: a conference at UW-Madison. 3rd-5th June, Madison, USA. 

2024 Modal decomposition and machine learning to develop robust models. LMFL Fluid Mechanics Webinars. ENSAM, France.

2024 Reduced order models in complex flows. Von Karman Institute/ULB Lecture Series Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures. 29th January - 2nd February, Brussels, Belgium. 

2023 Modal decompositions and other machine learning tools in fluid dynamics, 18th European Turbulence Conference. Plenary speaker. 4-6 September, Universitat Politecnica de Valencia, Spain.

See my talk in the following link:

https://www.youtube.com/watch?v=ZKeShcM8nuI&t=490s 

2023 Machine learning and reduced order models in the aerospace industry, International symposium on unmanned systems: AI, Design and Efficiency. Plenary speaker. 7-9 June, KTH Royal Institute of Technology, Sweden.

2023 Modal decompositions and other data-driven tools in fluid mechanics, Université Libre de Bruxelles, Belgium. Master course.

2022 Reduced order models combining modal decompositions and machine learning tools, 14th SIG33 ERCOFTAC Workshop:  Progress in flow instability, transition and control. Plenary speaker. 15-17 June, Cádiz, España.

2022 Simulation of air pollution dispersion in urban Environments, Workshop: Health research on air pollution effects and climate change: challenges and opportunities, University of Verone, Italia.

2022 Learning fluid dynamics and machine learning, Divulga Ciencia, Colegio Miguel de Cervantes, Invitada, São Paulo, Brasil.

2022 Predictive models based on physical principles for applications in aerospace engineering, Plenaria. International Symposium on Sustainable Aviation, 3-5 agosto, Melbourne, Australia.

2022 Machine learning and modal decompositions in complex flows, Université Libre de Bruxelles, Belgium.

2022 Extensions of modal decompositions for machine learning applications, University of Grenoble, France.

2022 Models for fluid dynamics using machine learning tools, Universidad de Zaragoza, Spain.

2022 Reduced order models in fluid dynamics: from modal decompositions to machine learning, KTH Royal Institute of Technology, Sweden.

2022 Machine learning and Reduced Order Models using modal decompositions and neural networks, Université Libre de Bruxelles, Belgium. Master course.

2022 Reduced order models based on physical principles using modal decompositions and machine learning, Universidad Politécnica de Valencia, Spain. Degree course.

2020 DMD methods to identify flow patterns, Australian Fluid Mechanics Seminars, Webminar, Monash University (Australia). Presentación en YouTube: https://www.youtube.com/watch?v=DjTk73Q_Gsg&t=2553s

2020 Data driven methods based on DMD and SVD and Deep learning in fluid dynamics, Universidad Autónoma de Madrid, Spain.

2019 Coherent structures in complex flows using DMD- and SVD- based methods, Instituto de Mecánica de Fluidos de Toulouse, Toulouse, Francie.

2018 Spatio-temporal flow structures using Koopman operators, KTH Royal Institute of Technology, Sweden.

2018 A new method to predict flutter in flight test, Gulfstream CO, Savannah, GE, EEUU.

2017 Applications of higher order dynamic mode decomposition, Universidad de Málaga, Spain.

2017 Flow structures and higher order dynamic mode decomposition, Northwestern Polytechnical University, Xi’an, China.

2017 A method to analyse flow structures, The University of Nottingham, Nottingham, UK.

2017 Higher order dynamic mode decomposition, Universidad Carlos III, Madrid, Spain.

2016 Applications of singular value decomposition Monash University, Melbourne, Australia.

2012 Time-resolved Particle Image Velocimetry and structural analysis on a hemisphere- cylinder at low Reynolds numbers and large angle of incidence, Universidade de São Paulo, São Paulo, Brasil.