| Tsunami propagation modelling–a sensitivity study MH Dao, P Tkalich Natural Hazards and Earth System Sciences 7 (6), 741-754, 2007 | 159 | 2007 |
| CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method PH Chiu, JC Wong, C Ooi, MH Dao, YS Ong Computer Methods in Applied Mechanics and Engineering 395, 114909, 2022 | 158 | 2022 |
| Tsunami propagation scenarios in the South China Sea MH Dao, P Tkalich, ES Chan, K Megawati Journal of Asian Earth Sciences 36 (1), 67-73, 2009 | 60 | 2009 |
| Artificial neural network for tsunami forecasting M Romano, SY Liong, MT Vu, P Zemskyy, CD Doan, MH Dao, P Tkalich Journal of Asian Earth Sciences 36 (1), 29-37, 2009 | 53 | 2009 |
| Simulations of laser assisted additive manufacturing by smoothed particle hydrodynamics MH Dao, J Lou Computer Methods in Applied Mechanics and Engineering 373, 113491, 2021 | 51 | 2021 |
| Real-time optimization using proper orthogonal decomposition: Free surface shape prediction due to underwater bubble dynamics D My-Ha, KM Lim, BC Khoo, K Willcox Computers & fluids 36 (3), 499-512, 2007 | 45 | 2007 |
| Modelling of tsunami-like wave run-up, breaking and impact on a vertical wall by SPH method MH Dao, H Xu, ES Chan, P Tkalich Natural Hazards and Earth System Sciences 13 (12), 3457-3467, 2013 | 33 | 2013 |
| Numerical modelling of extreme waves by Smoothed Particle Hydrodynamics MH Dao, H Xu, ES Chan, P Tkalich Natural Hazards and Earth System Sciences 11 (2), 419-429, 2011 | 27 | 2011 |
| Modelling physical wave tank with flap paddle and porous beach in OpenFOAM MH Dao, LW Chew, Y Zhang Ocean Engineering 154, 204-215, 2018 | 25 | 2018 |
| Modeling transient fluid simulations with proper orthogonal decomposition and machine learning C Ooi, QT Le, MH Dao, VB Nguyen, HH Nguyen, T Ba International Journal for Numerical Methods in Fluids 93 (2), 396-410, 2021 | 23 | 2021 |
| Tsunami forecasting using proper orthogonal decomposition method D My Ha, P Tkalich, ES Chan Journal of Geophysical Research: Oceans 113 (C6), 2008 | 22 | 2008 |
| A part-scale, feature-based surrogate model for residual stresses in the laser powder bed fusion process G Dong, JC Wong, L Lestandi, J Mikula, G Vastola, MH Jhon, MH Dao, ... Journal of Materials Processing Technology 304, 117541, 2022 | 21 | 2022 |
| Reassessment of the cell surface area limitation to nutrient uptake in phytoplankton MH Dao Marine Ecology Progress Series 489, 87-92, 2013 | 20 | 2013 |
| Digital twining of an offshore wind turbine on a monopile using reduced-order modelling approach X Zhao, MH Dao, QT Le Renewable Energy 206, 531-551, 2023 | 16 | 2023 |
| Fusing sensor data with CFD results using gappy POD X Xing, MH Dao, B Zhang, J Lou, WS Tan, Y Cui, BC Khoo Ocean Engineering 246, 110549, 2022 | 16 | 2022 |
| Improved surrogate modeling of fluid dynamics with physics-informed neural networks JC Wong, C Ooi, PH Chiu, MH Dao arXiv preprint arXiv:2105.01838, 2021 | 13 | 2021 |
| Tsunami propagation modeling and forecasting for early warning system P Tkalich, MYHA DAO, ENGS CHAN Journal of Earthquake and Tsunami 1 (01), 87-98, 2007 | 13 | 2007 |
| Case study of phytoplankton blooms in Serangoon Harbor of Singapore BH Ooi, H Zheng, KP Yue, H Kurniawati, P Sundarambal, MH Dao, ... OCEANS'10 IEEE SYDNEY, 1-6, 2010 | 11 | 2010 |
| Multi-vehicle oceanographic feature exploration BH Ooi, H Zheng, H Kurniawati, W Cho, NM Patrikalakis, MH Dao, ... ISOPE International Ocean and Polar Engineering Conference, ISOPE-I-09-501, 2009 | 11 | 2009 |
| Graph neural network based surrogate model of physics simulations for geometry design JC Wong, CC Ooi, J Chattoraj, L Lestandi, G Dong, U Kizhakkinan, ... 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1469-1475, 2022 | 8 | 2022 |
