My Ha Dao
- Statistical and Nonlinear Physics top 5%
- Computational Mechanics top 5%
- Geophysics top 10%
- Mechanical Engineering
- Aerospace Engineering
- Co-authors
- Pavel TkalichChin Chun OoiJian Cheng WongPao‐Hsiung ChiuYew-Soon OngJing LouEng Soon ChanXiang Zhao
- Topics
- Model Reduction and Neural Networks (8 papers)Fluid Dynamics and Vibration Analysis (6 papers)Coastal and Marine Dynamics (4 papers)
- Journals
- Computer Methods in Applied Mechanics and EngineeringRenewable EnergyJournal of Materials Processing Technology
- Partner nations
- SingaporeUnited StatesUnited Kingdom
In The Last Decade
My Ha Dao
33 papers receiving 569 citations
Hit Papers
Peers
Comparison fields: 5 of 66
- Statistical and Nonlinear Physics 181
- Computational Mechanics 174
- Geophysics 115
- Mechanical Engineering 101
- Aerospace Engineering 87
Countries citing papers authored by My Ha Dao
This map shows the geographic impact of My Ha Dao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by My Ha Dao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites My Ha Dao more than expected).
Fields of papers citing papers by My Ha Dao
This network shows the impact of papers produced by My Ha Dao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by My Ha Dao. The network helps show where My Ha Dao may publish in the future.
Co-authorship network of co-authors of My Ha Dao
This figure shows the co-authorship network connecting the top 25 collaborators of My Ha Dao. A scholar is included among the top collaborators of My Ha Dao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with My Ha Dao. My Ha Dao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 27 | |
| 7 | 5 | |
| 8 | CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation methodbreakdown → | 189 |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 26 | |
| 12 | 2 | |
| 13 | 6 | |
| 14 | 1 | |
| 15 | 51 | |
| 16 | 1 | |
| 17 | Wave Absorption Study of Artificial Beach with CFD | 2 |
| 18 | 17 | |
| 19 | 12 | |
| 20 | 29 |
About My Ha Dao
My Ha Dao is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Earth-Surface Processes, having authored 33 papers that have together received 599 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (8 papers), Fluid Dynamics and Vibration Analysis (6 papers) and Coastal and Marine Dynamics (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (181 citations), Geophysics (115 citations) and Earth-Surface Processes (58 citations). My Ha Dao has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include Pavel Tkalich, Chin Chun Ooi, Jian Cheng Wong, Pao‐Hsiung Chiu, Yew-Soon Ong, Jing Lou, Eng Soon Chan, Xiang Zhao, Kusnowidjaja Megawati and Lup Wai Chew. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Renewable Energy and Journal of Materials Processing Technology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.