Publications

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Latest Articles

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NUS MathEXLab Gianmarco Mengaldo SitesGo Singapore
Publish Date
2024

Similarities and differences between natural and simulated slow earthquakes

Gualandi, A., Dal Zilio, L., Faranda, D. and Mengaldo, G.
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NUS MathEXLab Gianmarco Mengaldo SitesGo Singapore
Publish Date
2023

FinXABSA: Explainable finance through aspect-based sentiment analysis

Ong, K., van der Heever, W., Satapathy, R., Cambria, E. and Mengaldo, G.
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NUS MathEXLab Gianmarco Mengaldo SitesGo Singapore
Publish Date
2023

Fully-discrete spatial eigenanalysis of discontinuous spectral element methods

Tonicello, N., Moura, R.C., Lodato, G. and Mengaldo, G.
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Journal Articles

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2024

Tonicello, N., Lario, A., Rozza, G. and Mengaldo, G., 2024. Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics. Computers & Fluids, p.106307. Read

Rogowski, M., Yeung, B.C., Schmidt, O.T., Maulik, R., Dalcin, L., Parsani, M. and Mengaldo, G., 2024. Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. Computer Physics Communications, p.109246. Read

Gualandi, A., Dal Zilio, L., Faranda, D. and Mengaldo, G., 2024. Similarities and differences between natural and simulated slow earthquakes (No. EGU24-20926). Copernicus Meetings. Read

Mao, R., Lin, Q., Liu, Q., Mengaldo, G. and Cambria, E., 2024. Understanding public perception towards weather disasters through the lens of metaphor. In Proceedings of the thirty-third international joint conference on artificial intelligence. Read

2023

Ong, K., van der Heever, W., Satapathy, R., Cambria, E. and Mengaldo, G., 2023, December. FinXABSA: Explainable finance through aspect-based sentiment analysis. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 773-782). IEEE.  Read

Tonicello, N., Moura, R.C., Lodato, G. and Mengaldo, G., 2023. Fully-discrete spatial eigenanalysis of discontinuous spectral element methods: insights into well-resolved and under-resolved vortical flows. Computers & Fluids, 266, p.106060.  Read

Tan, Y.J., Mengaldo, G. and Laschi, C., 2023. Artificial Muscles for Underwater Soft Robots: Materials and Their Interactions. Annual Review of Condensed Matter Physics, 15.  Read

Lin, S., Mengaldo, G. and Maulik, R., 2023. Online data-driven changepoint detection for high-dimensional dynamical systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(10).  Read

Rogowski, M., Yeung, B.C., Schmidt, O.T., Maulik, R., Dalcin, L., Parsani, M. and Mengaldo, G., 2023. Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. arXiv preprint arXiv:2309.11808.  Read

Yeo, W.J., van der Heever, W., Mao, R., Cambria, E., Satapathy, R. and Mengaldo, G., 2023. A comprehensive review on financial explainable AI. arXiv preprint arXiv:2309.11960.  Read

Duong, C., Raghuram, V.C., Lee, A., Mao, R., Mengaldo, G. and Cambria, E., 2023. Neurosymbolic AI for mining public opinions about wildfires. Cognitive Computation, pp.1-23.  Read

Turbé, H., Bjelogrlic, M., Lovis, C. and Mengaldo, G., 2023. Evaluation of post-hoc interpretability methods in time-series classification. Nature Machine Intelligence, 5(3), pp.250-260.  Read

Gualandi, A., Faranda, D., Marone, C., Cocco, M. and Mengaldo, G., 2023. Deterministic and stochastic chaos characterize laboratory earthquakes. Earth and Planetary Science Letters, 604, p.117995.  Read

2022

Lario, A., Maulik, R., Schmidt, O.T., Rozza, G. and Mengaldo, G., 2022. Neural-network learning of SPOD latent dynamics. Journal of Computational Physics, 468, p.111475.  Read


Maulik, R., Rao, V., Wang, J., Mengaldo, G., Constantinescu, E., Lusch, B., Balaprakash, P., Foster, I. and Kotamarthi, R., 2022. AIEADA 1.0: Efficient high-dimensional variational data assimilation with machine-learned reduced-order models. Geoscientific Model Development Discussions, 2022, pp.1-20.  Read


Hess, M.W., Lario, A., Mengaldo, G. and Rozza, G., 2022, November. Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives. In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2020+ 1: Selected Papers from the ICOSAHOM Conference, Vienna, Austria, July 12-16, 2021 (pp. 361-374). Cham: Springer International Publishing.  Read


Mengaldo, G., Renda, F., Brunton, S.L., Bächer, M., Calisti, M., Duriez, C., Chirikjian, G.S. and Laschi, C., 2022. A concise guide to modelling the physics of embodied intelligence in soft robotics. Nature Reviews Physics, 4(9), pp.595-610.  Read


Tonicello, N., Lario, A., Rozza, G. and Mengaldo, G., 2022. Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics. arXiv preprint arXiv:2212.10198Read


Moura, R.C., Fernandes, L.D., Silva, A.F.C., Mengaldo, G. and Sherwin, S.J., 2022. Spectral/hp element methods' linear mechanism of (apparent) energy transfer in Fourier space: Insights into dispersion analysis for implicit LES. Journal of Computational Physics, 471, p.111613.  Read

2021

Mengaldo, G. and Maulik, R., 2021. Pyspod: A python package for spectral proper orthogonal decomposition (spod). Journal of Open Source Software, 6(60), p.2862.  Read


Maulik, R. and Mengaldo, G., 2021, November. PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. In 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7) (pp. 19-25). IEEE.  Read


Mengaldo, G., Moxey, D., Turner, M., Moura, R.C., Jassim, A., Taylor, M., Peiro, J. and Sherwin, S., 2021. Industry-relevant implicit large-eddy simulation of a high-performance road car via spectral/hp element methods. SIAM Review, 63(4), pp.723-755.  Read

2020

Moxey, D., Cantwell, C.D., Bao, Y., Cassinelli, A., Castiglioni, G., Chun, S., Juda, E., Kazemi, E., Lackhove, K., Marcon, J. and Mengaldo, G., 2020. Nektar++: Enhancing the capability and application of high-fidelity spectral/hp element methods. Computer Physics Communications, 249, p.107110.  Read


Dorschner, B., Yu, K., Mengaldo, G. and Colonius, T., 2020. A fast multi-resolution lattice Green's function method for elliptic difference equations. Journal of Computational Physics, 407, p.109270.  Read


Moura, R.C., Fernandez, P., Mengaldo, G. and Sherwin, S.J., 2020. Viscous diffusion effects in the eigenanalysis of (hybridisable) DG methods. In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018: Selected Papers from the ICOSAHOM Conference, London, UK, July 9-13, 2018 (pp. 371-382). Springer International Publishing.  Read

2019

Fernandez, P., Moura, R.C., Mengaldo, G. and Peraire, J., 2019. Non-modal analysis of spectral element methods: Towards accurate and robust large-eddy simulations. Computer Methods in Applied Mechanics and Engineering, 346, pp.43-62.  Read


Schmidt, O.T., Mengaldo, G., Balsamo, G. and Wedi, N.P., 2019. Spectral empirical orthogonal function analysis of weather and climate data. Monthly Weather Review, 147(8), pp.2979-2995.  Read


Mengaldo, G., 2019. Batch 1: definition of several weather & climate dwarfs. arXiv preprint arXiv:1908.06089.  Read


Müller, A., Deconinck, W., Kühnlein, C., Mengaldo, G., Lange, M., Wedi, N., Bauer, P., Smolarkiewicz, P.K., Diamantakis, M., Lock, S.J. and Hamrud, M., 2019. The ESCAPE project: energy-efficient scalable algorithms for weather prediction at exascale. Geoscientific Model Development, 12(10), pp.4425-4441.  Read

2018

Mengaldo, G., Moura, R.C., Giralda, B., Peiró, J. and Sherwin, S.J., 2018. Spatial eigensolution analysis of discontinuous Galerkin schemes with practical insights for under-resolved computations and implicit LES. Computers & Fluids, 169, pp.349-364.  Read


Winters, A.R., Moura, R.C., Mengaldo, G., Gassner, G.J., Walch, S., Peiro, J. and Sherwin, S.J., 2018. A comparative study on polynomial dealiasing and split form discontinuous Galerkin schemes for under-resolved turbulence computations. Journal of Computational Physics, 372, pp.1-21.  Read


Mengaldo, G., Wyszogrodzki, A., Diamantakis, M., Lock, S.J., Giraldo, F.X. and Wedi, N.P., 2019. Current and emerging time-integration strategies in global numerical weather and climate prediction. Archives of Computational Methods in Engineering, 26, pp.663-684.  Read


Mengaldo, G., De Grazia, D., Moura, R.C. and Sherwin, S.J., 2018. Spatial eigensolution analysis of energy-stable flux reconstruction schemes and influence of the numerical flux on accuracy and robustness. J. Comput. Phys., 358(1), pp.1-20.  Read

2017

Moura, R.C., Mengaldo, G., Peiró, J. and Sherwin, S.J., 2017. On the eddy-resolving capability of high-order discontinuous Galerkin approaches to implicit LES/under-resolved DNS of Euler turbulence. Journal of Computational Physics, 330, pp.615-623.  Read


Moura, R.C., Mengaldo, G., Peiró, J. and Sherwin, S.J., 2017. An LES setting for DG-based implicit LES with insights on dissipation and robustness. In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016: Selected Papers from the ICOSAHOM conference, June 27-July 1, 2016, Rio de Janeiro, Brazil (pp. 161-173). Springer International Publishing.  Read


Mengaldo, G., Liska, S., Yu, K., Colonius, T. and Jardin, T., 2017. Immersed boundary lattice Green function methods for external aerodynamics. In 23rd AIAA computational fluid dynamics conference (p. 3621).  Read


Deconinck, W., Bauer, P., Diamantakis, M., Hamrud, M., Kühnlein, C., Maciel, P., Mengaldo, G., Quintino, T., Raoult, B., Smolarkiewicz, P.K. and Wedi, N.P., 2017. Atlas: A library for numerical weather prediction and climate modelling. Computer Physics Communications, 220, pp.188-204.  Read


Moxey, D., Cantwell, C.D., Mengaldo, G., Serson, D., Ekelschot, D., Peiró, J., Sherwin, S.J. and Kirby, R.M., 2017. Towards p-adaptive spectral/hp element methods for modelling industrial flows. In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016: Selected Papers from the ICOSAHOM conference, June 27-July 1, 2016, Rio de Janeiro, Brazil (pp. 63-79). Springer International Publishing.  Read


Moura, R., Fernandez, P. and Mengaldo, G., 2017, November. Diffusion and dispersion characteristics of hybridized discontinuous Galerkin methods for under-resolved turbulence simulations. In APS Division of Fluid Dynamics Meeting Abstracts (pp. F31-007).  Read

2016

Mengaldo, G., De Grazia, D., Vincent, P.E. and Sherwin, S.J., 2016. On the connections between discontinuous Galerkin and flux reconstruction schemes: extension to curvilinear meshes. Journal of Scientific Computing, 67, pp.1272-1292.  Read

2015

Cantwell, C.D., Moxey, D., Comerford, A., Bolis, A., Rocco, G., Mengaldo, G., De Grazia, D., Yakovlev, S., Lombard, J.E., Ekelschot, D. and Jordi, B., 2015. Nektar++: An open-source spectral/hp element framework. Computer physics communications, 192, pp.205-219.  Read


Mengaldo, G., Kravtsova, M., Ruban, A.I. and Sherwin, S.J., 2015. Triple-deck and direct numerical simulation analyses of high-speed subsonic flows past a roughness element. Journal of Fluid Mechanics, 774, pp.311-323.  Read


Mengaldo, G., De Grazia, D., Moxey, D., Vincent, P.E. and Sherwin, S.J., 2015. Dealiasing techniques for high-order spectral element methods on regular and irregular grids. Journal of Computational Physics, 299, pp.56-81.  Read

2014

De Grazia, D., Mengaldo, G., Moxey, D., Vincent, P.E. and Sherwin, S., 2014. Connections between the discontinuous Galerkin method and high‐order flux reconstruction schemes. International journal for numerical methods in fluids, 75(12), pp.860-877.  Read


Mengaldo, G., De Grazia, D., Witherden, F., Farrington, A., Vincent, P., Sherwin, S. and Peiro, J., 2014. A guide to the implementation of boundary conditions in compact high-order methods for compressible aerodynamics. In 7th AIAA Theoretical Fluid Mechanics Conference (p. 2923).  Read

PhD Thesis

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2015

Mengaldo, G., 2015. Discontinuous spectral/hp element methods: development, analysis and applications to compressible flows (Doctoral dissertation, Imperial College London). Read

M. Klein, K. Blecharz, B.W.H. Cheng, A. Bruno, C. Soci
Adv. Electron. Mat., accepted (2023); arXiv:2304.11606
H.N.S. Krishnamoorthy, A.M. Dubrovkin, G. Adamo, C. Soci
Chem. Rev. 123, 4416 (2023); arXiv:2209.05810
Y. Wang, J. Tian, M. Klein, G. Adamo, S.T. Ha, C. Soci
Nano Lett. 23, 4431 (2023); arXiv:2209.05810
J. Tian, Q.Y. Tan, Y. Wang, Y. Yang, G. Yuan, G. Adamo, C. Soci
Nat. Comms. 14, 1433 (2023); arXiv:2205.14932
M. d'Amato, Q.Y. Tan, Q. Glorieux, A. Bramati, C. Soci
ACS Photonics 10, 197 (2023); arXiv:2207.03201
M. Nuber, Q.Y. Tan, D. Sandner, J. Yin, R. Kienberger, C. Soci, H. Iglev
J. Mater. Chem. C 11, 3581 (2023)
C. Soci, G. Adamo, D. Cortecchia, K. Wang, S. Xiao, Q. Song, A.L. Schall-Giesecke, P.J. Cegielski, M.C. Lemme, D. Gerace, D. Sanvitto, J. Tian, P.A. Tonkaev, S.V. Makarov, Y.S. Kivshar, O.A. Jimenez Gordillo, A. Melloni, A.P. Pushkarev, M. D'Amato, E. Lhuillier, A. Bramati
Optical Materials X 17, 100214 (2023)
A.N. Vetlugin, F. Martinelli, S. Dong, C. Soci
Nanophotonics 12, 505 (2023); arXiv:2210.16653
J. Tian, G. Adamo, H. Liu, M. Wu, M. Klein, J. Deng, N.S.S. Ang, R. Paniagua-Domínguez, H. Liu, A.I. Kuznetsov, C. Soci
Adv. Mater. 35, 2207430 (2023); arXiv:2107.05239
M. Klein, Y. Wang, J. Tian, S.T. Ha, R. Paniagua-Domínguez, A.I. Kuznetsov, G. Adamo, C. Soci
Adv. Mater. 35, 2207317 (2023); arXiv:2206.12050
A.N. Vetlugin, R. Guo, C. Soci, N.I. Zheludev
New J. of Physics 24, 122001 (2022); arXiv:2105.05444
A. Maity, S. Perotto, M. Moschetta, H. Hua, S. Sardar, G. Paternò, J. Tian, M. Klein, G. Adamo, G. Lanzani, C. Soci
ACS Omega 7, 42674 (2022)
A.N. Vetlugin, C. Soci, N.I. Zheludev
Appl. Phys. Lett. 121, 104001 (2022); arXiv:2111.15183
J. Tian, D. Cortecchia, Y. Wang, H. Liu, E. Feltri, H. Liu, G. Adamo, C. Soci
Nanophotonics 11, 3961 (2022)
A.N. Vetlugin, R. Guo, C. Soci, N.I. Zheludev
Phys. Rev. A 106, 012402  (2022)
G. Long, G. Adamo, J. Tian, M. Klein, H.S.N. Krishnamoorthy, E. Feltri, H. Wang, C. Soci
Nat. Comms. 13, 1551 (2022)

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