A deep learning framework for solution and discovery in solid mechanics: linear elasticity. - Ehsan Haghighat; Maziar Raissi; Adrian Moure; Héctor Gómez; Ruben Juanes (CoRR, 2020)

SciANN: A Keras wrapper for scientific computations and physics-informed deep learning using artificial neural networks. - Ehsan Haghighat; Ruben Juanes (CoRR, 2020)

A nonlocal physics-informed deep learning framework using the peridynamic differential operator. - Ehsan Haghighat; Ali Can Bekar; Erdogan Madenci; Ruben Juanes (CoRR, 2020)

An energy-based error bound of physics-informed neural network solutions in elasticity. - Mengwu Guo; Ehsan Haghighat (CoRR, 2020)

Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture. - Sina Amini Niaki; Ehsan Haghighat; Xinglong Li; Trevor Campbell; Reza Vaziri (CoRR, 2020)

Deep learning for solution and inversion of structural mechanics and vibrations. - Ehsan Haghighat; Ali Can Bekar; Erdogan Madenci; Ruben Juanes (CoRR, 2021)

A Physics Informed Neural Network Approach to Solution and Identification of Biharmonic Equations of Elasticity. - Mohammad Vahab; Ehsan Haghighat; Maryam Khaleghi; Nasser Khalili (CoRR, 2021)

Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training. - Ehsan Haghighat; Danial Amini; Ruben Juanes (CoRR, 2021)

PINNeik: Eikonal solution using physics-informed neural networks. - Umair bin Waheed; Ehsan Haghighat; Tariq Alkhalifah; Chao Song 003; Qi Hao (Comput. Geosci., 2021)

Physics-informed neural network solution of thermo-hydro-mechanical (THM) processes in porous media. - Danial Amini; Ehsan Haghighat; Ruben Juanes (CoRR, 2022)

An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator. - A. Mavi; Ali Can Bekar; Ehsan Haghighat; Erdogan Madenci (CoRR, 2022)

Application of Physics-Informed Neural Networks for Forward and Inverse Analysis of Pile-Soil Interaction. - Mohammad Vahab; B. Shahbodagh; Ehsan Haghighat; Nasser Khalili (CoRR, 2022)

An efficient phase-field model of shear fractures using deviatoric stress split. - Ehsan Haghighat; David Santillán (CoRR, 2023)

A novel deeponet model for learning moving-solution operators with applications to earthquake hypocenter localization. - Ehsan Haghighat; Umair bin Waheed; George Em Karniadakis (CoRR, 2023)

Machine Learning-Enabled Precision Position Control and Thermal Regulation in Advanced Thermal Actuators. - Seyed M. Mirvakili; Ehsan Haghighat; Douglas Sim (CoRR, 2023)

Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks. - Danial Amini; Ehsan Haghighat; Ruben Juanes (J. Comput. Phys., 2023)

Constitutive model characterization and discovery using physics-informed deep learning. - Ehsan Haghighat; Sahar Abouali; Reza Vaziri (Eng. Appl. Artif. Intell., 2023)

STONet: A novel neural operator for modeling solute transport in micro-cracked reservoirs. - Ehsan Haghighat; Mohammad Hesan Adeli; S. Mohammad Mousavi; Ruben Juanes (CoRR, 2024)

Multiphysics discovery with moving boundaries using Ensemble SINDy and peridynamic differential operator. - Ali Can Bekar; Ehsan Haghighat; Erdogan Madenci (Eng. Comput., 2025)

LatticeGraphNet: a two-scale graph neural operator for simulating lattice structures. - Ayush Jain; Ehsan Haghighat; Sai Nelaturi (Eng. Comput., 2025)