Fan Lam
- Computational Mathematics top 2%
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- Advanced MRI Techniques and Applications 43
- Medical Imaging Techniques and Applications 15
- Advanced Neuroimaging Techniques and Applications 13
- Computational Mechanics top 2%
- Sparse and Compressive Sensing Techniques 18
- Biophysics top 5%
- Spectroscopy Techniques in Biomedical and Chemical Research 6
- Spectroscopy top 5%
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- Image and Signal Denoising Methods 8
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- Atomic and Subatomic Physics Research 8
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- Photoacoustic and Ultrasonic Imaging 8
- Co-authors
- Zhi‐Pei LiangChao MaBo ZhaoBryan CliffordYingkun HouZhong ChenXiaobo QuDi Guo
- Journals
- Magnetic Resonance in Medicine (15 papers)IEEE Transactions on Biomedical Engineering (6 papers)IEEE Transactions on Medical Imaging (4 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Fan Lam
60 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 95
- Computational Mathematics 54
- Radiology, Nuclear Medicine and Imaging 1.3k
- Computational Mechanics 402
- Biophysics 101
- Spectroscopy 262
Countries citing papers authored by Fan Lam
This map shows the geographic impact of Fan Lam'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 Fan Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fan Lam more than expected).
Fields of papers citing papers by Fan Lam
This network shows the impact of papers produced by Fan Lam. 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 Fan Lam. The network helps show where Fan Lam may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fan Lam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 2 | |
| 7 | 2022 | 6 | |
| 8 | 2022 | 21 | |
| 9 | 2022 | 19 | |
| 10 | 2021 | 13 | |
| 11 | 2019 | 39 | |
| 12 | 2014 | 104 | |
| 13 | 2014 | 3 | |
| 14 | 2013 | 29 | |
| 15 | 2013 | 60 | |
| 16 | 2012 | 23 | |
| 17 | 2012 | 4 | |
| 18 | 2009 | 23 | |
| 19 | 2002 | 10 | |
| 20 | 1995 | 4 |
About Fan Lam
Fan Lam is a scholar working on Computational Mathematics, Radiology, Nuclear Medicine and Imaging, Biophysics, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 64 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (43 papers), Sparse and Compressive Sensing Techniques (18 papers), Medical Imaging Techniques and Applications (15 papers), Advanced Neuroimaging Techniques and Applications (13 papers), Image and Signal Denoising Methods (8 papers), Atomic and Subatomic Physics Research (8 papers), Photoacoustic and Ultrasonic Imaging (8 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (6 papers). The work is most often cited by research in Computational Mathematics (54 citations), Radiology, Nuclear Medicine and Imaging (1.3k citations), Computational Mechanics (402 citations), Biophysics (101 citations) and Spectroscopy (262 citations). Fan Lam has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Zhi‐Pei Liang, Chao Ma, Bo Zhao, Bryan Clifford, Yingkun Hou, Zhong Chen, Xiaobo Qu, Di Guo, Jianhui Zhong and Curtis L. Johnson. Their work appears in journals such as Magnetic Resonance in Medicine, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Medical Imaging, Analytical Chemistry and Obesity Reviews.
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.