David Fan
Impact in
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- Multiferroics and related materials
- Magnetic and transport properties of perovskites and related materials
Papers in
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- Human Pose and Action Recognition 3
- Multimodal Machine Learning Applications 2
- Video Analysis and Summarization 2
- Advanced Vision and Imaging 2
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- Memory and Neural Mechanisms 2
- Co-authors
- Henry H. Yin (3 shared papers)Gia-Wei Chern (1 shared paper)Sang‐Wook Cheong (1 shared paper)Shi‐Zeng Lin (1 shared paper)Yue Liu (1 shared paper)Cristian D. Batista (1 shared paper)Yoshitomo Kamiya (1 shared paper)Xueyun Wang (1 shared paper)
- Journals
- PLoS ONE (2 papers)Nature Physics (1 paper)Aging (1 paper)European Journal of Neuroscience (1 paper)Cureus (1 paper)
- Partner nations
- United StatesGrenadaChina
In The Last Decade
David Fan
12 papers receiving 260 citations
Peers
Comparison fields: 5 of 59
- Aging 10
- Electronic, Optical and Magnetic Materials 83
- Condensed Matter Physics 47
- Computer Vision and Pattern Recognition 62
- Cellular and Molecular Neuroscience 41
Countries citing papers authored by David Fan
This map shows the geographic impact of David Fan'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 David Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Fan more than expected).
Fields of papers citing papers by David Fan
This network shows the impact of papers produced by David Fan. 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 David Fan. The network helps show where David Fan may publish in the future.
Co-authors
The 25 scholars most cited alongside David Fan, 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 | 2014 | 136 | |
| 2 | 2013 | 33 | |
| 3 | 2021 | 33 | |
| 4 | 2020 | 23 | |
| 5 | 2011 | 15 | |
| 6 | 2015 | 12 | |
| 7 | 2022 | 5 | |
| 8 | 2024 | 5 | |
| 9 | 2023 | 4 | |
| 10 | 2024 | 1 | |
| 11 | 2014 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2021 | 0 | |
| 14 | 2025 | 0 |
About David Fan
David Fan is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Artificial Intelligence and Molecular Biology, having authored 14 papers that have together received 269 indexed citations. Recurring topics across this work include Neurotransmitter Receptor Influence on Behavior (3 papers), Human Pose and Action Recognition (3 papers), Multimodal Machine Learning Applications (2 papers), Memory and Neural Mechanisms (2 papers), Video Analysis and Summarization (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Advanced Vision and Imaging (2 papers) and Physics of Superconductivity and Magnetism (1 paper). The work is most often cited by research in Aging (10 citations), Electronic, Optical and Magnetic Materials (83 citations), Condensed Matter Physics (47 citations), Computer Vision and Pattern Recognition (62 citations) and Cellular and Molecular Neuroscience (41 citations). David Fan has collaborated with scholars based in United States, Grenada and China. Frequent co-authors include Henry H. Yin, Gia-Wei Chern, Sang‐Wook Cheong, Shi‐Zeng Lin, Yue Liu, Cristian D. Batista, Yoshitomo Kamiya, Xueyun Wang, V. Kiryukhin and Wojciech H. Zurek. Their work appears in journals such as PLoS ONE, Nature Physics, Aging, European Journal of Neuroscience and Cureus.
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.