| Hierarchical deep learning neural network (HiDeNN): an artificial intelligence (AI) framework for computational science and engineering S Saha, Z Gan, L Cheng, J Gao, OL Kafka, X Xie, H Li, M Tajdari, HA Kim, ... Computer Methods in Applied Mechanics and Engineering 373, 113452, 2021 | 127 | 2021 |
| Clustering discretization methods for generation of material performance databases in machine learning and design optimization H Li, OL Kafka, J Gao, C Yu, Y Nie, L Zhang, M Tajdari, S Tang, X Guo, ... Computational Mechanics 64, 281-305, 2019 | 99 | 2019 |
| Hierarchical deep-learning neural networks: finite elements and beyond L Zhang, L Cheng, H Li, J Gao, C Yu, R Domel, Y Yang, S Tang, WK Liu Computational Mechanics 67, 207-230, 2021 | 72 | 2021 |
| Nanopore creation in graphene by ion beam irradiation: geometry, quality, and efficiency Z Bai, L Zhang, H Li, L Liu ACS applied materials & interfaces 8 (37), 24803-24809, 2016 | 71 | 2016 |
| Image-based modelling for adolescent idiopathic scoliosis: mechanistic machine learning analysis and prediction M Tajdari, A Pawar, H Li, F Tajdari, A Maqsood, E Cleary, S Saha, ... Computer methods in applied mechanics and engineering 374, 113590, 2021 | 63 | 2021 |
| Data-driven microstructure and microhardness design in additive manufacturing using a self-organizing map Z Gan, H Li, SJ Wolff, JL Bennett, G Hyatt, GJ Wagner, J Cao, WK Liu Engineering 5 (4), 730-735, 2019 | 62 | 2019 |
| FEM-Cluster based reduction method for efficient numerical prediction of effective properties of heterogeneous material in nonlinear range G Cheng, X Li, Y Nie, H Li Computer Methods in Applied Mechanics and Engineering 348, 157-184, 2019 | 57 | 2019 |
| A data-driven self-consistent clustering analysis for the progressive damage behavior of 3D braided composites C He, J Gao, H Li, J Ge, Y Chen, J Liu, D Fang Composite Structures 249, 112471, 2020 | 37 | 2020 |
| On predicting the effective elastic properties of polymer nanocomposites by novel numerical implementation of asymptotic homogenization method J Zhao, H Li, G Cheng, Y Cai Composite Structures 135, 297-305, 2016 | 36 | 2016 |
| Concurrent n-scale modeling for non-orthogonal woven composite J Gao, S Mojumder, W Zhang, H Li, D Suarez, C He, J Cao, WK Liu Computational Mechanics 70 (4), 853-866, 2022 | 16 | 2022 |
| Convolution hierarchical deep-learning neural network tensor decomposition (C-HiDeNN-TD) for high-resolution topology optimization H Li, S Knapik, Y Li, C Park, J Guo, S Mojumder, Y Lu, W Chen, DW Apley, ... Computational Mechanics 72 (2), 363-382, 2023 | 15 | 2023 |
| Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond Y Lu, H Li, L Zhang, C Park, S Mojumder, S Knapik, Z Sang, S Tang, ... Computational Mechanics 72 (2), 333-362, 2023 | 12 | 2023 |
| Reduced order machine learning finite element methods: concept, implementation, and future applications Y Lu, H Li, S Saha, S Mojumder, A Al Amin, D Suarez, Y Liu, D Qian, ... Computer Modeling in Engineering & Sciences 129 (1), 2021 | 9 | 2021 |
| Mathematical modeling for the mechanical properties of poly (vinylchloride) ternary composites J Zhao, HY Li, Y Wang, N Feng, MJ Qu, LH Wu Polymer Engineering & Science 56 (10), 1109-1117, 2016 | 3 | 2016 |
| Isogeometric Convolution Hierarchical Deep-learning Neural Network: Isogeometric analysis with versatile adaptivity L Zhang, C Park, Y Lu, H Li, S Mojumder, S Saha, J Guo, Y Li, T Abbott, ... Computer Methods in Applied Mechanics and Engineering 417, 116356, 2023 | 2 | 2023 |
| Self-consistent Clustering Analysis-Based Moving Morphable Component (SMMC) Method for Multiscale Topology Optimization Y Li, J Guo, H Li, H Chen Acta Mechanica Solida Sinica 36 (6), 884-898, 2023 | | 2023 |
