Physics-Aware Recurrent Convolutional (PARC) Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials. - Phong C. H. Nguyen; Joseph B. Choi; Yen Thi Nguyen; Pradeep K. Seshadri; H. S. Udaykumar; Stephen Baek (CoRR, 2022)

A physics-aware deep learning model for energy localization in multiscale shock-to-detonation simulations of heterogeneous energetic materials. - Phong C. H. Nguyen; Yen Thi Nguyen; Pradeep K. Seshadri; Joseph B. Choi; H. S. Udaykumar; Stephen Baek (CoRR, 2022)

Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions. - Joseph B. Choi; Phong C. H. Nguyen; Oishik Sen; H. S. Udaykumar; Stephen Baek (CoRR, 2022)

Characterization and design of two-dimensional multi-morphology cellular structures for desired deformation. - Youngdoo Kim; Phong C. H. Nguyen; Hoon Kim; Hae-Jin Choi; Young Choi (J. Comput. Des. Eng., 2023)

Challenges and Opportunities for Machine Learning in Multiscale Computational Modeling. - Phong C. H. Nguyen; Joseph B. Choi; H. S. Udaykumar; Stephen Baek (J. Comput. Inf. Sci. Eng., 2023)

PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling. - Phong C. H. Nguyen; Xinlun Cheng; Shahab Azarfar; Pradeep K. Seshadri; Yen Thi Nguyen; Munho Kim; Sanghun Choi; H. S. Udaykumar; Stephen Baek (ICML, 2024)

FLRNet: A Deep Learning Method for Regressive Reconstruction of Flow Field From Limited Sensor Measurements. - Phong C. H. Nguyen; Joseph B. Choi; Quang-Trung Luu (CoRR, 2024)

FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements. - Hiep Vo Dang; Joseph B. Choi; Phong C. H. Nguyen (CoRR, 2024)

Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic Material. - Shahab Azarfar; Joseph B. Choi; Phong C. H. Nguyen; Yen Thi Nguyen; Pradeep K. Seshadri; H. S. Udaykumar; Stephen Baek (CoRR, 2025)