Siyuan Gao
- Cognitive Neuroscience top 2%
- Functional Brain Connectivity Studies 17
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- Mental Health Research Topics 5
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- Advanced MRI Techniques and Applications 5
- Psychiatry and Mental health top 10%
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- Microbial bioremediation and biosurfactants 6
- Pesticide and Herbicide Environmental Studies 4
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- Animal Behavior and Welfare Studies 4
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- Nanoplatforms for cancer theranostics 3
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- Microbial Community Ecology and Physiology 3
Siyuan Gao
57 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Cognitive Neuroscience 1.1k
- Experimental and Cognitive Psychology 343
- Radiology, Nuclear Medicine and Imaging 341
- Psychiatry and Mental health 149
- Health, Toxicology and Mutagenesis 116
Countries citing papers authored by Siyuan Gao
This map shows the geographic impact of Siyuan Gao'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 Siyuan Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siyuan Gao more than expected).
Fields of papers citing papers by Siyuan Gao
This network shows the impact of papers produced by Siyuan Gao. 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 Siyuan Gao. The network helps show where Siyuan Gao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Siyuan Gao, 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 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 18 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 0 | |
| 11 | 2022 | 29 | |
| 12 | 2022 | 12 | |
| 13 | BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysisbreakdown → | 2021 | 351 |
| 14 | 2021 | 14 | |
| 15 | 2020 | 38 | |
| 16 | Ten simple rules for predictive modeling of individual differences in neuroimagingbreakdown → | 2019 | 250 |
| 17 | 2019 | 88 | |
| 18 | Task-induced brain state manipulation improves prediction of individual traitsbreakdown → | 2018 | 306 |
| 19 | 2017 | 27 | |
| 20 | Beijing University of Posts and Telecommunications(BUPT) at TREC 2016: A Rating Model Based on Tags for ABSTRACT Contextual Suggestion. | 2016 | 1 |
About Siyuan Gao
Siyuan Gao is a scholar working on Cognitive Neuroscience, Medical Laboratory Technology and Pollution, having authored 62 papers that have together received 1.7k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (17 papers), Microbial bioremediation and biosurfactants (6 papers), Mental Health Research Topics (5 papers), Advanced MRI Techniques and Applications (5 papers), Animal Behavior and Welfare Studies (4 papers), Pesticide and Herbicide Environmental Studies (4 papers), Nanoplatforms for cancer theranostics (3 papers) and Microbial Community Ecology and Physiology (3 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Experimental and Cognitive Psychology (343 citations) and Radiology, Nuclear Medicine and Imaging (341 citations). Siyuan Gao has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Dustin Scheinost, Abigail S. Greene, R. Todd Constable, Stephanie Noble, Nicha C. Dvornek, Yuan Zhou, James S. Duncan, Xiaoxiao Li, Lawrence H. Staib and Muhan Zhang. Their work appears in journals such as NeuroImage, Applied and Environmental Microbiology, Animals, Biological Psychiatry and IEEE Transactions on Intelligent Transportation 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.