Xiaolin Hong
Impact in
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Human-Computer Interaction top 10%
- Gaze Tracking and Assistive Technology
Papers in
-
- Data Stream Mining Techniques 3
- Neural Networks and Applications 2
- Anomaly Detection Techniques and Applications 2
-
- Neural Networks Stability and Synchronization 3
- Distributed Control Multi-Agent Systems 2
- Co-authors
- Zhongke Gao (8 shared papers)Kai Ma (2 shared papers)Weidong Dang (7 shared papers)Linhua Hou (4 shared papers)Xinmin Wang (2 shared papers)Matjaž Perc (1 shared paper)Luyan Liu (1 shared paper)Qingqing Zheng (1 shared paper)
In The Last Decade
Xiaolin Hong
10 papers receiving 327 citations
Peers
Comparison fields: 5 of 63
- Cognitive Neuroscience 197
- Human-Computer Interaction 36
- Signal Processing 39
- Experimental and Cognitive Psychology 28
- Neurology 13
Countries citing papers authored by Xiaolin Hong
This map shows the geographic impact of Xiaolin Hong'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 Xiaolin Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolin Hong more than expected).
Fields of papers citing papers by Xiaolin Hong
This network shows the impact of papers produced by Xiaolin Hong. 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 Xiaolin Hong. The network helps show where Xiaolin Hong may publish in the future.
Co-authors
The 16 scholars most cited alongside Xiaolin Hong, 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 | 2020 | 157 | |
| 2 | 2021 | 94 | |
| 3 | 2020 | 31 | |
| 4 | 2018 | 13 | |
| 5 | 2020 | 12 | |
| 6 | 2019 | 11 | |
| 7 | 2020 | 11 | |
| 8 | 2023 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2019 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 0 |
About Xiaolin Hong
Xiaolin Hong is a scholar working on Artificial Intelligence, Computer Networks and Communications, Economics and Econometrics, Signal Processing and Cognitive Neuroscience, having authored 12 papers that have together received 334 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (4 papers), Neural Networks Stability and Synchronization (3 papers), Data Stream Mining Techniques (3 papers), Time Series Analysis and Forecasting (3 papers), Neural Networks and Applications (2 papers), Distributed Control Multi-Agent Systems (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Fractional Differential Equations Solutions (2 papers). The work is most often cited by research in Cognitive Neuroscience (197 citations), Human-Computer Interaction (36 citations), Signal Processing (39 citations), Experimental and Cognitive Psychology (28 citations) and Neurology (13 citations). Xiaolin Hong has collaborated with scholars based in China, Hong Kong and Slovenia. Frequent co-authors include Zhongke Gao, Kai Ma, Weidong Dang, Linhua Hou, Xinmin Wang, Matjaž Perc, Luyan Liu, Qingqing Zheng, Yefeng Zheng and Guanrong Chen. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, International Journal of Bifurcation and Chaos, IEEE Transactions on Industrial Informatics, IEEE Transactions on Neural Systems and Rehabilitation Engineering and New Journal of Physics.
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.