Ehsan Haghighat

According to our database, Ehsan Haghighat authored at least 20 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

LatticeGraphNet: A two-scale graph neural operator for simulating lattice structures.

Ayush Jain, Ehsan Haghighat, Sai Nelaturi

CoRR, 2024

2023

Constitutive model characterization and discovery using physics-informed deep learning.

Ehsan Haghighat, Sahar Abouali, Reza Vaziri

Eng. Appl. Artif. Intell., April, 2023

Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks.

Danial Amini, Ehsan Haghighat, Ruben Juanes

J. Comput. Phys., 2023

Machine Learning-Enabled Precision Position Control and Thermal Regulation in Advanced Thermal Actuators.

Seyed M. Mirvakili, Ehsan Haghighat, Douglas Sim

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

Multiphysics discovery with moving boundaries using Ensemble SINDy and Peridynamic Differential Operator.

Ali Can Bekar, Ehsan Haghighat, Erdogan Madenci

CoRR, 2023

An efficient phase-field model of shear fractures using deviatoric stress split.

Ehsan Haghighat, David Santillán

CoRR, 2023

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 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

Physics-informed neural network solution of thermo-hydro-mechanical (THM) processes in porous media.

Danial Amini, Ehsan Haghighat, Ruben Juanes

CoRR, 2022

2021

PINNeik: Eikonal solution using physics-informed neural networks.

Umair bin Waheed, Ehsan Haghighat, Tariq Alkhalifah, Chao Song, Qi Hao

Comput. Geosci., 2021

Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training.

Ehsan Haghighat, Danial Amini, 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

Deep learning for solution and inversion of structural mechanics and vibrations.

Ehsan Haghighat, Ali Can Bekar, Erdogan Madenci, Ruben Juanes

CoRR, 2021

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

An energy-based error bound of physics-informed neural network solutions in elasticity.

Mengwu Guo, Ehsan Haghighat

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

SciANN: A Keras wrapper for scientific computations and physics-informed deep learning using artificial neural networks.

Ehsan Haghighat, Ruben Juanes

CoRR, 2020

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