Nektar++: An open-source spectral/hp element framework. - Chris D. Cantwell; David Moxey; Andrew Comerford; Alessandro Bolis; Gabriele Rocco; Gianmarco Mengaldo; Daniele De Grazia; Sergey Yakovlev; Jean-Eloise Lombard; Dirk Ekelschot; Bastien Jordi; Hui Xu 005; et al. (Comput. Phys. Commun., 2015)

Dealiasing techniques for high-order spectral element methods on regular and irregular grids. - Gianmarco Mengaldo; Daniele De Grazia; David Moxey; Peter E. Vincent; Spencer J. Sherwin (J. Comput. Phys., 2015)

On the Connections Between Discontinuous Galerkin and Flux Reconstruction Schemes: Extension to Curvilinear Meshes. - Gianmarco Mengaldo; Daniele De Grazia; Peter E. Vincent; Spencer J. Sherwin (J. Sci. Comput., 2016)

Atlas : A library for numerical weather prediction and climate modelling. - Willem Deconinck; Peter Bauer; Michail Diamantakis; Mats Hamrud; Christian Kühnlein; Pedro Maciel; Gianmarco Mengaldo; Tiago Quintino; Baudouin Raoult; Piotr K. Smolarkiewicz; Nils P. Wedi (Comput. Phys. Commun., 2017)

On the eddy-resolving capability of high-order discontinuous Galerkin approaches to implicit LES / under-resolved DNS of Euler turbulence. - Rodrigo Costa Moura; Gianmarco Mengaldo; Joaquim Peiró; Spencer J. Sherwin (J. Comput. Phys., 2017)

Spatial eigensolution analysis of energy-stable flux reconstruction schemes and influence of the numerical flux on accuracy and robustness. - Gianmarco Mengaldo; Daniele De Grazia; Rodrigo Costa Moura; Spencer J. Sherwin (J. Comput. Phys., 2018)

A comparative study on polynomial dealiasing and split form discontinuous Galerkin schemes for under-resolved turbulence computations. - Andrew R. Winters; Rodrigo Costa Moura; Gianmarco Mengaldo; Gregor J. Gassner; Stefanie Walch; Joaquim Peiró; Spencer J. Sherwin (J. Comput. Phys., 2018)

Nektar++: enhancing the capability and application of high-fidelity spectral/hp element methods. - David Moxey; Chris D. Cantwell; Yan Bao; Andrea Cassinelli; Giacomo Castiglioni; Sehun Chun; Emilia Juda; Ehsan Kazemi 002; Kilian Lackhove; Julian Marcon; Gianmarco Mengaldo; Douglas Serson; et al. (CoRR, 2019)

Batch 1: Definition of several Weather & Climate Dwarfs. - Gianmarco Mengaldo (CoRR, 2019)

Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods. - Gianmarco Mengaldo; David Moxey; Michael Turner; Rodrigo Costa Moura; Ayad Jassim; Mark Taylor; Joaquim Peiró; Spencer J. Sherwin (CoRR, 2020)

Nektar++: Enhancing the capability and application of high-fidelity spectral/hp element methods. - David Moxey; Chris D. Cantwell; Yan Bao; Andrea Cassinelli; Giacomo Castiglioni; Sehun Chun; Emilia Juda; Ehsan Kazemi 002; Kilian Lackhove; Julian Marcon; Gianmarco Mengaldo; Douglas Serson; et al. (Comput. Phys. Commun., 2020)

A fast multi-resolution lattice Green's function method for elliptic difference equations. - Benedikt Dorschner; Ke Yu; Gianmarco Mengaldo; Tim Colonius (J. Comput. Phys., 2020)

PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. - Romit Maulik; Gianmarco Mengaldo (DRBSD@SC, 2021)

Neural-network learning of SPOD latent dynamics. - Andrea Lario; Romit Maulik; Gianluigi Rozza; Gianmarco Mengaldo (CoRR, 2021)

Fully-discrete spatial eigenanalysis of discontinuous spectral element methods: insights into well-resolved and under-resolved vortical flows. - Niccolò Tonicello; Rodrigo Costa Moura; Guido Lodato; Gianmarco Mengaldo (CoRR, 2021)

PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD). - Gianmarco Mengaldo; Romit Maulik (J. Open Source Softw., 2021)

Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods. - Gianmarco Mengaldo; David Moxey; Michael Turner; Rodrigo Costa Moura; Ayad Jassim; Mark Taylor; Joaquim Peiró; Spencer J. Sherwin (SIAM Rev., 2021)

Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives. - Martin W. Hess; Andrea Lario; Gianmarco Mengaldo; Gianluigi Rozza (CoRR, 2022)

InterpretTime: a new approach for the systematic evaluation of neural-network interpretability in time series classification. - Hugues Turbé; Mina Bjelogrlic; Christian Lovis; Gianmarco Mengaldo (CoRR, 2022)

Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics. - Niccolò Tonicello; Andrea Lario; Gianluigi Rozza; Gianmarco Mengaldo (CoRR, 2022)

Neural-network learning of SPOD latent dynamics. - Andrea Lario; Romit Maulik; Oliver T. Schmidt; Gianluigi Rozza; Gianmarco Mengaldo (J. Comput. Phys., 2022)

Spectral/hp element methods' linear mechanism of (apparent) energy transfer in Fourier space: Insights into dispersion analysis for implicit LES. - Rodrigo Costa Moura; Lucas Dantas Fernandes; A. F. C. Silva; Gianmarco Mengaldo; Spencer J. Sherwin (J. Comput. Phys., 2022)

FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis. - Keane Ong; Wihan van der Heever; Ranjan Satapathy; Erik Cambria; Gianmarco Mengaldo (ICDM (Workshops), 2023)

Evaluation of post-hoc interpretability methods in time-series classification. - Hugues Turbé; Mina Bjelogrlic; Christian Lovis; Gianmarco Mengaldo (Nat. Mac. Intell., 2023)

Sentiment Analysis on Climate Change for Sustainable Investment. - Keane Ong; Rui Mao 010; Deeksha Varshney; Ranjan Satapathy; Erik Cambria; Gianmarco Mengaldo (ICDM (Workshops), 2024)

Understanding Public Perception Towards Weather Disasters Through the Lens of Metaphor. - Rui Mao 010; Qika Lin; Qiawen Liu; Gianmarco Mengaldo; Erik Cambria (IJCAI, 2024)

ProtoS-ViT: Visual foundation models for sparse self-explainable classifications. - Hugues Turbé; Mina Bjelogrlic; Gianmarco Mengaldo; Christian Lovis (CoRR, 2024)

Explain the Black Box for the Sake of Science: Revisiting the Scientific Method in the Era of Generative Artificial Intelligence. - Gianmarco Mengaldo (CoRR, 2024)

Revisiting the robustness of post-hoc interpretability methods. - Jiawen Wei 002; Hugues Turbé; Gianmarco Mengaldo (CoRR, 2024)

Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. - Marcin Rogowski; Brandon C. Y. Yeung; Oliver T. Schmidt; Romit Maulik; Lisandro Dalcín; Matteo Parsani; Gianmarco Mengaldo (Comput. Phys. Commun., 2024)

Neurosymbolic AI for Mining Public Opinions about Wildfires. - Cuc Duong; Vethavikashini Chithrra Raghuram; Amos Lee; Rui Mao 010; Gianmarco Mengaldo; Erik Cambria (Cogn. Comput., 2024)

Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization. - Keane Ong; Rui Mao 010; Deeksha Varshney; Erik Cambria; Gianmarco Mengaldo (ACL (1), 2025)

Explainable natural language processing for corporate sustainability analysis. - Keane Ong; Rui Mao 010; Ranjan Satapathy; Ricardo Shirota Filho; Erik Cambria; Johan Sulaeman; Gianmarco Mengaldo (Inf. Fusion, 2025)

ESGSenticNet: A Neurosymbolic Knowledge Base for Corporate Sustainability Analysis. - Keane Ong; Rui Mao 010; Frank Xing; Ranjan Satapathy; Johan Sulaeman; Erik Cambria; Gianmarco Mengaldo (CoRR, 2025)

CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints. - Xin Wang; Juntao Yang; Jeff Adie; Simon See; Kalli Furtado; Chen Chen; Troy Arcomano; Romit Maulik; Gianmarco Mengaldo (CoRR, 2025)

Tell me why: Visual foundation models as self-explainable classifiers. - Hugues Turbé; Mina Bjelogrlic; Gianmarco Mengaldo; Christian Lovis (CoRR, 2025)

XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change. - Jiawen Wei 002; Aniruddha Bora; Vivek Oommen; Chenyu Dong; Juntao Yang; Jeff Adie; Chen Chen; Simon See; George E. Karniadakis; Gianmarco Mengaldo (CoRR, 2025)

Leveraging LLMS for Top-Down Sector Allocation In Automated Trading. - Ryan Quek Wei Heng; Edoardo Vittori; Keane Ong; Rui Mao 010; Erik Cambria; Gianmarco Mengaldo (CoRR, 2025)

Dynamical errors in machine learning forecasts. - Zhou Fang; Gianmarco Mengaldo (CoRR, 2025)

ClimaEmpact: Domain-Aligned Small Language Models and Datasets for Extreme Weather Analytics. - Deeksha Varshney; Keane Ong; Rui Mao 010; Erik Cambria; Gianmarco Mengaldo (CoRR, 2025)

Deriving Strategic Market Insights with Large Language Models: A Benchmark for Forward Counterfactual Generation. - Keane Ong; Rui Mao 010; Deeksha Varshney; Paul Pu Liang; Erik Cambria; Gianmarco Mengaldo (CoRR, 2025)

A comprehensive review on financial explainable AI. - Wei Jie Yeo; Wihan van der Heever; Rui Mao 010; Erik Cambria; Ranjan Satapathy; Gianmarco Mengaldo (Artif. Intell. Rev., 2025)