Diab W. Abueidda

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All published works

Action	Title	Year	Authors
+	DeepOKAN: Deep operator network based on Kolmogorov Arnold networks for mechanics problems	2025	Diab W. Abueidda Panos Pantidis Mostafa E. Mobasher
+ PDF Chat	Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing	2024	Qibang Liu Pengfei Cai Diab W. Abueidda Sagar Vyas Seid Korić Rafael Gómez‐Bombarelli Philippe H. Geubelle
+ PDF Chat	Virtual Sensing for Real-Time Degradation Monitoring of Nuclear Systems: Leveraging DeepONet for Enhanced Sensing Coverage for Digital Twin-Enabling Technology	2024	Raisa Bentay Hossain Farid Ahmed Kazuma Kobayashi Seid Korić Diab W. Abueidda Syed Bahauddin Alam
+ PDF Chat	Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier	2024	Jaewan Park Shashank Kushwaha Junyan He Seid Korić Qibang Liu Iwona Jasiuk Diab W. Abueidda
+ PDF Chat	Physics-informed DeepONet with stiffness-based loss functions for structural response prediction	2024	Bilal Ahmed Yuqing Qiu Diab W. Abueidda Waleed El-Sekelly Borja Garcia de Soto Tarek Abdoun Mostafa E. Mobasher
+ PDF Chat	Damage identification for bridges using machine learning: Development and application to KW51 bridge	2024	Yuqing Qiu Bilal Ahmed Diab W. Abueidda Waleed El-Sekelly Borja Garcia de Soto Tarek Abdoun Hongli Ji Jinhao Qiu Mostafa E. Mobasher
+ PDF Chat	Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries	2024	Junyan He Seid Korić Diab W. Abueidda Ali Najafi Iwona Jasiuk
+	Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries	2024	Junyan He Seid Korić Diab W. Abueidda Ali Najafi Iwona Jasiuk
+ PDF Chat	DeepOKAN: Deep Operator Network Based on Kolmogorov Arnold Networks for Mechanics Problems	2024	Diab W. Abueidda Panos Pantidis Mostafa E. Mobasher
+	Advanced deep operator networks to predict multiphysics solution fields in materials processing and additive manufacturing	2024	Shashank Kushwaha Jaewan Park Seid Korić Junyan He Iwona Jasiuk Diab W. Abueidda
+ PDF Chat	I-FENN with Temporal Convolutional Networks: Expediting the load-history analysis of non-local gradient damage propagation	2024	Panos Pantidis Habiba Eldababy Diab W. Abueidda Mostafa E. Mobasher
+ PDF Chat	Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing	2024	Shashank Kushwaha Jaewan Park Seid Korić Junyan He Iwona Jasiuk Diab W. Abueidda
+ PDF Chat	I-FENN with Temporal Convolutional Networks: expediting the load-history analysis of non-local gradient damage propagation	2024	Panos Pantidis Habiba Eldababy Diab W. Abueidda Mostafa E. Mobasher
+	Material-Response-Informed DeepONet and its Application to Polycrystal Stress-strain Prediction in Crystal Plasticity	2024	Junyan He Deepankar Pal Ali Najafi Diab W. Abueidda Seid Korić Iwona Jasiuk
+ PDF Chat	I-Fenn with Temporal Convolutional Networks: Expediting the Load-History Analysis of Non-Local Gradient Damage Propagation	2024	Panos Pantidis Habiba Eldababy Diab W. Abueidda Mostafa E. Mobasher
+ PDF Chat	Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads	2023	Junyan He Shashank Kushwaha Jaewan Park Seid Korić Diab W. Abueidda Iwona Jasiuk
+	Designing impact-resistant bio-inspired low-porosity structures using neural networks	2023	Shashank Kushwaha Junyan He Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads	2023	Junyan He Seid Korić Shashank Kushwaha Jaewan Park Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	A deep learning energy-based method for classical elastoplasticity	2023	Junyan He Diab W. Abueidda Rashid K. Abu Al‐Rub Seid Korić Iwona Jasiuk
+	Gyroid-like metamaterials: Topology optimization and Deep Learning	2023	Asha Viswanath Diab W. Abueidda Mohamad Modrek Kamran A. Khan Seid Korić Rashid K. Abu Al‐Rub
+	I-FENN for thermoelasticity based on physics-informed temporal convolutional network (PI-TCN)	2023	Diab W. Abueidda Mostafa E. Mobasher
+	Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads	2023	Junyan He Seid Korić Shashank Kushwaha Jaewan Park Diab W. Abueidda Iwona Jasiuk
+	Sequential Deep Operator Networks (S-DeepONet) for Predicting Full-field Solutions Under Time-dependent Loads	2023	Junyan He Shashank Kushwaha Jaewan Park Seid Korić Diab W. Abueidda Iwona Jasiuk
+	Designing impact-resistant bio-inspired low-porosity structures using neural networks	2023	Shashank Kushwaha Junyan He Diab W. Abueidda Iwona Jasiuk
+	Multi-component Predictions of Transient Solution Fields with Sequential Deep Operator Network	2023	Junyan He Shashank Kushwaha Jaewan Park Seid Korić Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	Exploring the structure-property relations of thin-walled, 2D extruded lattices using neural networks	2022	Junyan He Shashank Kushwaha Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	Deep energy method in topology optimization applications	2022	Junyan He Charul Chadha Shashank Kushwaha Seid Korić Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	Enhanced physics‐informed neural networks for hyperelasticity	2022	Diab W. Abueidda Seid Korić Erman Guleryuz Nahil Sobh
+ PDF Chat	LatticeOPT: a heuristic topology optimization framework for thin-walled, 2D extruded lattices	2022	Junyan He Shashank Kushwaha Diab W. Abueidda Iwona Jasiuk
+ PDF Chat	On the use of graph neural networks and shape‐function‐based gradient computation in the deep energy method	2022	Junyan He Diab W. Abueidda Seid Korić Iwona Jasiuk
+ PDF Chat	Surrogate neural network model for sensitivity analysis and uncertainty quantification of the mechanical behavior in the optical lens-barrel assembly	2022	Shantanu Shahane Erman Guleryuz Diab W. Abueidda Allen S. Lee Joe Liu Xin Yu Raymond Chiu Seid Korić N. R. Aluru Placid M. Ferreira
+ PDF Chat	A deep learning energy method for hyperelasticity and viscoelasticity	2022	Diab W. Abueidda Seid Korić Rashid K. Abu Al‐Rub Corey M. Parrott Kai A. James Nahil Sobh
+	Exploring the structure-property relations of thin-walled, 2D extruded lattices using neural networks	2022	Junyan He Shashank Kushwaha Diab W. Abueidda Iwona Jasiuk
+	Enhanced physics-informed neural networks for hyperelasticity	2022	Diab W. Abueidda Seid Korić Erman Guleryuz Nahil Sobh
+	On the use of graph neural networks and shape-function-based gradient computation in the deep energy method	2022	Junyan He Diab W. Abueidda Seid Korić Iwona Jasiuk
+	A deep learning energy-based method for classical elastoplasticity	2022	Junyan He Diab W. Abueidda Rashid K. Abu Al‐Rub Seid Korić Iwona Jasiuk
+ PDF Chat	Meshless physics‐informed deep learning method for three‐dimensional solid mechanics	2021	Diab W. Abueidda Qiyue Lu Seid Korić
+	Deep learning collocation method for solid mechanics: Linear elasticity, hyperelasticity, and plasticity as examples.	2020	Diab W. Abueidda Qiyue Lu Seid Korić
+	Meshless physics-informed deep learning method for three-dimensional solid mechanics	2020	Diab W. Abueidda Qiyue Lu Seid Korić
+ PDF Chat	Topology optimization of 2D structures with nonlinearities using deep learning	2020	Diab W. Abueidda Seid Korić Nahil Sobh
+	Machine learning accelerated topology optimization of nonlinear structures.	2020	Diab W. Abueidda Seid Korić Nahil Sobh
+	Deep learning accelerated topology optimization of linear and nonlinear structures	2020	Diab W. Abueidda Seid Korić Nahil Sobh
+	Prediction and optimization of mechanical properties of composites using convolutional neural networks	2019	Diab W. Abueidda Mohammad Almasri Rami Ammourah Umberto Ravaioli Iwona Jasiuk Nahil Sobh

Common Coauthors

Coauthor	Papers Together
Seid Korić	29
Iwona Jasiuk	22
Junyan He	21
Shashank Kushwaha	14
Mostafa E. Mobasher	8
Nahil Sobh	7
Jaewan Park	6
Panos Pantidis	5
Rashid K. Abu Al‐Rub	4
Ali Najafi	3
Habiba Eldababy	3
Qiyue Lu	3
Erman Guleryuz	3
Waleed El-Sekelly	2
Tarek Abdoun	2
Yuqing Qiu	2
Bilal Ahmed	2
Borja Garcia de Soto	2
Jaewan Park	2
Qibang Liu	2
Asha Viswanath	1
Philippe H. Geubelle	1
Jinhao Qiu	1
Rami Ammourah	1
Xin Yu	1
Syed Bahauddin Alam	1
Sagar Vyas	1
Rafael Gómez‐Bombarelli	1
Placid M. Ferreira	1
Raymond Chiu	1
Hongli Ji	1
Kai A. James	1
Kamran A. Khan	1
Deepankar Pal	1
Mohammad Almasri	1
Farid Ahmed	1
Charul Chadha	1
Raisa Bentay Hossain	1
Corey M. Parrott	1
Allen S. Lee	1
N. R. Aluru	1
Joe Liu	1
Umberto Ravaioli	1
Mohamad Modrek	1
Kazuma Kobayashi	1
Shantanu Shahane	1
Pengfei Cai	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications	2020	Esteban Samaniego Cosmin Anitescu Somdatta Goswami Vien Minh Nguyen‐Thanh Hongwei Guo Khader M. Hamdia Xiaoying Zhuang Timon Rabczuk	12
+ PDF Chat	The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity	2021	Jan N. Fuhg Nikolaos Bouklas	10
+	Prediction and optimization of mechanical properties of composites using convolutional neural networks	2019	Diab W. Abueidda Mohammad Almasri Rami Ammourah Umberto Ravaioli Iwona Jasiuk Nahil Sobh	9
+ PDF Chat	Exploring the structure-property relations of thin-walled, 2D extruded lattices using neural networks	2022	Junyan He Shashank Kushwaha Diab W. Abueidda Iwona Jasiuk	8
+ PDF Chat	Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads	2023	Junyan He Seid Korić Shashank Kushwaha Jaewan Park Diab W. Abueidda Iwona Jasiuk	8
+ PDF Chat	Meshless physics‐informed deep learning method for three‐dimensional solid mechanics	2021	Diab W. Abueidda Qiyue Lu Seid Korić	8
+ PDF Chat	A deep learning energy-based method for classical elastoplasticity	2023	Junyan He Diab W. Abueidda Rashid K. Abu Al‐Rub Seid Korić Iwona Jasiuk	8
+ PDF Chat	On the use of graph neural networks and shape‐function‐based gradient computation in the deep energy method	2022	Junyan He Diab W. Abueidda Seid Korić Iwona Jasiuk	8
+ PDF Chat	DeepXDE: A Deep Learning Library for Solving Differential Equations	2021	Lu Lu Xuhui Meng Zhiping Mao George Em Karniadakis	7
+ PDF Chat	A deep learning energy method for hyperelasticity and viscoelasticity	2022	Diab W. Abueidda Seid Korić Rashid K. Abu Al‐Rub Corey M. Parrott Kai A. James Nahil Sobh	7
+ PDF Chat	Topology optimization of 2D structures with nonlinearities using deep learning	2020	Diab W. Abueidda Seid Korić Nahil Sobh	6
+ PDF Chat	Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads	2023	Junyan He Shashank Kushwaha Jaewan Park Seid Korić Diab W. Abueidda Iwona Jasiuk	6
+ PDF Chat	A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials	2022	Somdatta Goswami Minglang Yin Yue Yu George Em Karniadakis	6
+ PDF Chat	On the limited memory BFGS method for large scale optimization	1989	Cheng‐Di Dong Jorge Nocedal	6
+ PDF Chat	The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems	2018	E Weinan Bing Yu	6
+ PDF Chat	Nonsmooth optimization via quasi-Newton methods	2012	Adrian S. Lewis Michael L. Overton	5
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	5
+ PDF Chat	Deep energy method in topology optimization applications	2022	Junyan He Charul Chadha Shashank Kushwaha Seid Korić Diab W. Abueidda Iwona Jasiuk	5
+	Fourier Neural Operator for Parametric Partial Differential Equations	2020	Zongyi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu Kaushik Bhattacharya Andrew M. Stuart Anima Anandkumar	4
+ PDF Chat	Thermodynamics-based Artificial Neural Networks for constitutive modeling	2020	Filippo Masi Ioannis Stefanou Paolo Vannucci Victor Maffi-Berthier	4
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James T. Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	4
+ PDF Chat	Enhanced physics‐informed neural networks for hyperelasticity	2022	Diab W. Abueidda Seid Korić Erman Guleryuz Nahil Sobh	4
+	Geometric deep learning for computational mechanics Part I: anisotropic hyperelasticity	2020	Nikolaos N. Vlassis Ran Ma WaiChing Sun	4
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	4
+ PDF Chat	Going deeper with convolutions	2015	Christian Szegedy Wei Liu Yangqing Jia Pierre Sermanet Scott Reed Dragomir Anguelov Dumitru Erhan Vincent Vanhoucke Andrew Rabinovich	3
+	The method of moving asymptotes—a new method for structural optimization	1987	Krister Svanberg	3
+	Designing impact-resistant bio-inspired low-porosity structures using neural networks	2023	Shashank Kushwaha Junyan He Diab W. Abueidda Iwona Jasiuk	3
+ PDF Chat	Artificial neural networks for solving ordinary and partial differential equations	1998	I.E. Lagaris Aristidis Likas D.I. Fotiadis	3
+ PDF Chat	Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture	2021	Sina Amini Niaki Ehsan Haghighat Trevor Campbell Anoush Poursartip Reza Vaziri	3
+	Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks	2021	Shengze Cai Zhicheng Wang Frederik Fuest Young Jin Jeon Callum Gray George Em Karniadakis	3
+ PDF Chat	Physics-Informed Deep Learning for Computational Elastodynamics without Labeled Data	2021	Chengping Rao Hao Sun Yang Liu	3
+ PDF Chat	Alya: Multiphysics engineering simulation toward exascale	2016	Mariano Vázquez Guillaume Houzeaux Seid Korić Antoni Artigues Jazmín Aguado‐Sierra Ruth Arís Daniel Mira Hadrien Calmet Fernando Cucchietti Herbert Owen	3
+	On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks	2021	Sifan Wang Hanwen Wang Paris Perdikaris	3
+	Learning to fail: Predicting fracture evolution in brittle material models using recurrent graph convolutional neural networks	2019	Max Schwarzer Bryce Rogan Yadong Ruan Zhengming Song Diana Y. Lee Allon G. Percus Viet T. Chau Bryan A. Moore Esteban Rougier Hari Viswanathan	3
+	Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	3
+ PDF Chat	A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method	2022	Shahed Rezaei Ali Harandi Ahmad Moeineddin Bai‐Xiang Xu Stefanie Reese	3
+	NTopo: Mesh-free Topology Optimization using Implicit Neural Representations	2021	Jonas Zehnder Yue Li Stelian Coros Bernhard Thomaszewski	3
+ PDF Chat	Deep learning for determining a near-optimal topological design without any iteration	2018	Yonggyun Yu Taeil Hur Jaeho Jung In Gwun Jang	3
+	Fourier Neural Operator with Learned Deformations for PDEs on General Geometries	2022	Zongyi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar	3
+ PDF Chat	Interfacing finite elements with deep neural operators for fast multiscale modeling of mechanics problems	2022	Minglang Yin Enrui Zhang Yue Yu George Em Karniadakis	3
+	Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations	2018	Maziar Raissi	3
+ PDF Chat	Physics informed neural networks for continuum micromechanics	2022	Alexander Henkes Henning Wessels Rolf Mahnken	3
+ PDF Chat	Algorithm 778: L-BFGS-B	1997	Ciyou Zhu Richard H. Byrd Peihuang Lu Jorge Nocedal	3
+ PDF Chat	Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport	2020	Qizhi He David A. Barajas‐Solano G. Tartakovsky Alexandre M. Tartakovsky	3
+ PDF Chat	Learning the solution operator of parametric partial differential equations with physics-informed DeepONets	2021	Sifan Wang Hanwen Wang Paris Perdikaris	3
+ PDF Chat	Predicting the mechanical response of oligocrystals with deep learning	2019	Ari Frankel Reese E. Jones Coleman Alleman Jeremy Alan Templeton	3
+	Improved Architectures and Training Algorithms for Deep Operator Networks	2022	Sifan Wang Hanwen Wang Paris Perdikaris	3
+	Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators	2021	Lu Lu Pengzhan Jin Guofei Pang Zhongqiang Zhang George Em Karniadakis	2
+ PDF Chat	Stochastic sampling for deterministic structural topology optimization with many load cases: Density-based and ground structure approaches	2017	Xiaojia Shelly Zhang Eric de Sturler Gláucio H. Paulino	2
+	Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks	2016	Tim Salimans Diederik P. Kingma	2