Fan Mo
Impact in
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- Neuroscience and Neural Engineering
Papers in
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- Neuroscience and Neural Engineering 14
- Neuroscience and Neuropharmacology Research 10
- Photoreceptor and optogenetics research 4
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- Neural dynamics and brain function 12
- Memory and Neural Mechanisms 4
- EEG and Brain-Computer Interfaces 4
- Co-authors
- Hamed Haddadi (2 shared papers)Diego Perino (1 shared paper)Eduard Marin (1 shared paper)Kleomenis Katevas (2 shared papers)Nicolas Kourtellis (1 shared paper)Yilin Song (14 shared papers)Penghui Fan (13 shared papers)Baoyang Hu (6 shared papers)
- Journals
- ACS Sensors (4 papers)Advanced Science (2 papers)Biosensors (2 papers)Fundamental Research (2 papers)Cell Proliferation (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Fan Mo
28 papers receiving 435 citations
Peers
Comparison fields: 5 of 81
- Cellular and Molecular Neuroscience 115
- Developmental Neuroscience 17
- Artificial Intelligence 129
- Cognitive Neuroscience 72
- Polymers and Plastics 33
Countries citing papers authored by Fan Mo
This map shows the geographic impact of Fan Mo'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 Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fan Mo more than expected).
Fields of papers citing papers by Fan Mo
This network shows the impact of papers produced by Fan Mo. 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 Mo. The network helps show where Fan Mo may publish in the future.
Co-authors
The 25 scholars most cited alongside Fan Mo, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 138 | |
| 2 | 2018 | 43 | |
| 3 | 2021 | 40 | |
| 4 | 2019 | 37 | |
| 5 | 2023 | 35 | |
| 6 | 2022 | 17 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 13 | |
| 9 | 2022 | 13 | |
| 10 | 2022 | 11 | |
| 11 | 2025 | 11 | |
| 12 | 2013 | 10 | |
| 13 | 2022 | 9 | |
| 14 | 2021 | 8 | |
| 15 | 2023 | 7 | |
| 16 | 2023 | 7 | |
| 17 | 2024 | 7 | |
| 18 | 2023 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2023 | 3 |
About Fan Mo
Fan Mo is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Molecular Biology, Artificial Intelligence and Sensory Systems, having authored 30 papers that have together received 445 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (14 papers), Neural dynamics and brain function (12 papers), Neuroscience and Neuropharmacology Research (10 papers), Memory and Neural Mechanisms (4 papers), EEG and Brain-Computer Interfaces (4 papers), Pluripotent Stem Cells Research (4 papers), Photoreceptor and optogenetics research (4 papers) and Olfactory and Sensory Function Studies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (115 citations), Developmental Neuroscience (17 citations), Artificial Intelligence (129 citations), Cognitive Neuroscience (72 citations) and Polymers and Plastics (33 citations). Fan Mo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Hamed Haddadi, Diego Perino, Eduard Marin, Kleomenis Katevas, Nicolas Kourtellis, Yilin Song, Penghui Fan, Baoyang Hu, Boya Zhang and Xinxia Cai. Their work appears in journals such as ACS Sensors, Advanced Science, Biosensors, Fundamental Research and Cell Proliferation.
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.