Nam Pham
Impact in
- Geophysics top 2%
- Seismic Imaging and Inversion Techniques
- Seismic Waves and Analysis
- Ocean Engineering top 1%
- Drilling and Well Engineering
- Reservoir Engineering and Simulation Methods
- Geophysical Methods and Applications
Papers in
- Geophysics 33
- Seismic Imaging and Inversion Techniques 32
- Seismic Waves and Analysis 16
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- Drilling and Well Engineering 14
- Reservoir Engineering and Simulation Methods 8
- Co-authors
- Sergey Fomel (28 shared papers)Harpreet Kaur (15 shared papers)Xinming Wu (4 shared papers)Dallas Dunlap (3 shared papers)Zhicheng Geng (6 shared papers)Ehsan Zabihi Naeini (2 shared papers)Yunzhi Shi (2 shared papers)Guillaume Caumon (1 shared paper)
- Journals
- Geophysics (8 papers)Geophysical Prospecting (4 papers)Applied Geochemistry (2 papers)Journal of Geophysical Research Solid Earth (2 papers)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Nam Pham
42 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 50
- Geophysics 901
- Ocean Engineering 543
- Geochemistry and Petrology 49
- Artificial Intelligence 255
- Mechanical Engineering 269
Countries citing papers authored by Nam Pham
This map shows the geographic impact of Nam Pham'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 Nam Pham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nam Pham more than expected).
Fields of papers citing papers by Nam Pham
This network shows the impact of papers produced by Nam Pham. 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 Nam Pham. The network helps show where Nam Pham may publish in the future.
Co-authors
The 25 scholars most cited alongside Nam Pham, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 180 | |
| 2 | 2019 | 93 | |
| 3 | 2020 | 83 | |
| 4 | 2020 | 78 | |
| 5 | 2019 | 74 | |
| 6 | 2003 | 69 | |
| 7 | 2020 | 64 | |
| 8 | 2020 | 63 | |
| 9 | 2021 | 61 | |
| 10 | 2022 | 41 | |
| 11 | 2021 | 30 | |
| 12 | 2018 | 25 | |
| 13 | 2013 | 22 | |
| 14 | 2015 | 20 | |
| 15 | 2021 | 16 | |
| 16 | 2021 | 14 | |
| 17 | 2019 | 12 | |
| 18 | 2022 | 12 | |
| 19 | 2019 | 12 | |
| 20 | 2019 | 12 |
About Nam Pham
Nam Pham is a scholar working on Geophysics, Ocean Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Seismic Imaging and Inversion Techniques (32 papers), Seismic Waves and Analysis (16 papers), Drilling and Well Engineering (14 papers), Seismology and Earthquake Studies (8 papers), Reservoir Engineering and Simulation Methods (8 papers), Hydraulic Fracturing and Reservoir Analysis (7 papers), Image and Signal Denoising Methods (6 papers) and Hydrocarbon exploration and reservoir analysis (5 papers). The work is most often cited by research in Geophysics (901 citations), Ocean Engineering (543 citations), Geochemistry and Petrology (49 citations), Artificial Intelligence (255 citations) and Mechanical Engineering (269 citations). Nam Pham has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Sergey Fomel, Harpreet Kaur, Xinming Wu, Dallas Dunlap, Zhicheng Geng, Ehsan Zabihi Naeini, Yunzhi Shi, Guillaume Caumon, Hans B. Helle and José M. Carcione. Their work appears in journals such as Geophysics, Geophysical Prospecting, Applied Geochemistry, Journal of Geophysical Research Solid Earth and IEEE Transactions on Neural Networks and Learning Systems.
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.