Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks. - Mohammad Amin Nabian; Hadi Meidani (CoRR, 2017)

A Recursive Data-driven Model for Traffic Flow Predictions for Locations with Faulty Sensors. - Negin Alemazkoor; Shiyu Wang; Hadi Meidani (ITSC, 2018)

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks. - Mohammad Amin Nabian; Hadi Meidani (Comput. Aided Civ. Infrastructure Eng., 2018)

A Deep Neural Network Surrogate for High-Dimensional Random Partial Differential Equations. - Mohammad Amin Nabian; Hadi Meidani (CoRR, 2018)

Physics-Informed Regularization of Deep Neural Networks. - Mohammad Amin Nabian; Hadi Meidani (CoRR, 2018)

A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions. - Negin Alemazkoor; Hadi Meidani (J. Comput. Phys., 2018)

Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data. - Xu Wu; Tomasz Kozlowski; Hadi Meidani (Reliab. Eng. Syst. Saf., 2018)

Fast Probabilistic Voltage Control for Distribution Networks With Distributed Generation Using Polynomial Surrogates. - Negin Alemazkoor; Hadi Meidani (IEEE Access, 2020)

Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo. - Mohammad Amin Nabian; Hadi Meidani (CoRR, 2020)

IGANI: Iterative Generative Adversarial Networks for Imputation Applied to Prediction of Traffic Data. - Amir Kazemi; Hadi Meidani (CoRR, 2020)

Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis. - Mohammad Amin Nabian; Hadi Meidani (J. Comput. Inf. Sci. Eng., 2020)

Efficient Collection of Connected Vehicles Data With Precision Guarantees. - Negin Alemazkoor; Hadi Meidani (IEEE Trans. Intell. Transp. Syst., 2020)

A Data-Driven Multi-Fidelity Approach for Traffic State Estimation Using Data From Multiple Sources. - Negin Alemazkoor; Hadi Meidani (IEEE Access, 2021)

IGANI: Iterative Generative Adversarial Networks for Imputation With Application to Traffic Data. - Amir Kazemi; Hadi Meidani (IEEE Access, 2021)

Efficient training of physics-informed neural networks via importance sampling. - Mohammad Amin Nabian; Rini Jasmine Gladstone; Hadi Meidani (Comput. Aided Civ. Infrastructure Eng., 2021)

Robust Topology Optimization Using Variational Autoencoders. - Rini Jasmine Gladstone; Mohammad Amin Nabian; Vahid Keshavarzzadeh; Hadi Meidani (CoRR, 2021)

PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations. - Weiheng Zhong; Hadi Meidani (CoRR, 2022)

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting. - Weiheng Zhong; Tanwi Mallick; Hadi Meidani; Jane MacFarlane; Prasanna Balaprakash (CoRR, 2022)

Graph Neural Network Surrogate for seismic reliability analysis of highway bridge system. - Tong Liu 029; Hadi Meidani (CoRR, 2022)

FO-PINNs: A First-Order formulation for Physics Informed Neural Networks. - Rini Jasmine Gladstone; Mohammad Amin Nabian; Hadi Meidani (CoRR, 2022)

Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram. - Amir Kazemi; Hadi Meidani (CoRR, 2022)

Optimizing Seismic Retrofit of Bridges: Integrating Efficient Graph Neural Network Surrogates and Transportation Equity. - Tong Liu 029; Hadi Meidani (CPS-IoT Week Workshops, 2023)

Graph Pyramid Autoformer for Long- Term Traffic Forecasting. - Weiheng Zhong; Tanwi Mallick; Jane MacFarlane; Hadi Meidani; Prasanna Balaprakash (ICMLA, 2023)

GNN-based physics solver for time-independent PDEs. - Rini Jasmine Gladstone; Helia Rahmani; Vishvas Suryakumar; Hadi Meidani; Marta D'Elia; Ahmad Zareei (CoRR, 2023)

Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction. - Weiheng Zhong; Hadi Meidani; Jane MacFarlane (CoRR, 2023)

Heterogeneous Graph Neural Networks for Data-driven Traffic Assignment. - Tong Liu 029; Hadi Meidani (CoRR, 2023)

Supply Chain Network Extraction and Entity Classification Leveraging Large Language Models. - Tong Liu 029; Hadi Meidani (IEEE Big Data, 2024)

Physics-informed Mesh-independent Deep Compositional Operator Network. - Weiheng Zhong; Hadi Meidani (CoRR, 2024)

Physics-Informed Geometry-Aware Neural Operator. - Weiheng Zhong; Hadi Meidani (CoRR, 2024)

Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment. - Tong Liu 029; Hadi Meidani (CoRR, 2024)

A Multi-Fidelity Graph U-Net Model for Accelerated Physics Simulations. - Rini Jasmine Gladstone; Hadi Meidani (CoRR, 2024)

Multi-class traffic assignment using multi-view heterogeneous graph attention networks. - Tong Liu 029; Hadi Meidani (Expert Syst. Appl., 2025)

PINN-FEM: A Hybrid Approach for Enforcing Dirichlet Boundary Conditions in Physics-Informed Neural Networks. - Nahil Sobh; Rini Jasmine Gladstone; Hadi Meidani (CoRR, 2025)

Graph Neural Networks for Travel Distance Estimation and Route Recommendation Under Probabilistic Hazards. - Tong Liu 029; Hadi Meidani (CoRR, 2025)

Geometry-Informed Neural Operator Transformer. - Qibang Liu; Vincient Zhong; Hadi Meidani; Diab W. Abueidda; Seid Koric; Philippe H. Geubelle (CoRR, 2025)

A comprehensive comparison of neural operators for 3D industry-scale engineering designs. - Weiheng Zhong; Qibang Liu; Diab W. Abueidda; Seid Koric; Hadi Meidani (CoRR, 2025)