Beibei Li
Impact in
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- Network Security and Intrusion Detection
- Distributed Control Multi-Agent Systems
- Plant Science top 2%
- Wheat and Barley Genetics and Pathology
- Plant Stress Responses and Tolerance
- Powdery Mildew Fungal Diseases
Papers in
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- Recommender Systems and Techniques 16
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- Privacy-Preserving Technologies in Data 15
- Cryptography and Data Security 8
- Co-authors
- Rongxing Lu (23 shared papers)Tao Li (17 shared papers)Gaoxi Xiao (10 shared papers)Daqiang Yuan (6 shared papers)Yuhao Wu (4 shared papers)Jiarui Song (3 shared papers)Liang Zhao (2 shared papers)Feng Zhang (1 shared paper)
In The Last Decade
Beibei Li
199 papers receiving 4.6k citations
Beibei Li's Hit Papers
Peers
Comparison fields: 5 of 146
- Computer Networks and Communications 709
- Plant Science 1.2k
- Control and Systems Engineering 551
- Inorganic Chemistry 250
- Artificial Intelligence 559
Countries citing papers authored by Beibei Li
This map shows the geographic impact of Beibei Li'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 Beibei Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beibei Li more than expected).
Fields of papers citing papers by Beibei Li
This network shows the impact of papers produced by Beibei Li. 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 Beibei Li. The network helps show where Beibei Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Beibei Li, 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 231 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems Hit paper breakdown → | 2020 | 481 |
| 2 | 2004 | 388 | |
| 3 | 2020 | 189 | |
| 4 | 2019 | 155 | |
| 5 | 2018 | 136 | |
| 6 | 2020 | 135 | |
| 7 | 2020 | 125 | |
| 8 | 2020 | 124 | |
| 9 | 2018 | 120 | |
| 10 | 2019 | 117 | |
| 11 | 2016 | 113 | |
| 12 | 2022 | 107 | |
| 13 | 2021 | 85 | |
| 14 | 2019 | 79 | |
| 15 | 2018 | 77 | |
| 16 | 2016 | 74 | |
| 17 | 2015 | 66 | |
| 18 | 2016 | 58 | |
| 19 | 2022 | 57 | |
| 20 | 2022 | 56 |
About Beibei Li
Beibei Li is a scholar working on Information Systems, Artificial Intelligence, Control and Systems Engineering, Computer Networks and Communications and Plant Science, having authored 231 papers that have together received 4.7k indexed citations. Recurring topics across this work include Smart Grid Security and Resilience (22 papers), Recommender Systems and Techniques (16 papers), Wheat and Barley Genetics and Pathology (16 papers), Privacy-Preserving Technologies in Data (15 papers), Network Security and Intrusion Detection (11 papers), Powdery Mildew Fungal Diseases (9 papers), Cryptography and Data Security (8 papers) and Metal-Organic Frameworks: Synthesis and Applications (6 papers). The work is most often cited by research in Computer Networks and Communications (709 citations), Plant Science (1.2k citations), Control and Systems Engineering (551 citations), Inorganic Chemistry (250 citations) and Artificial Intelligence (559 citations). Beibei Li has collaborated with scholars based in China, Singapore and Canada. Frequent co-authors include Rongxing Lu, Tao Li, Gaoxi Xiao, Daqiang Yuan, Yuhao Wu, Jiarui Song, Liang Zhao, Feng Zhang, Liqun Zhao and Jinkui Guo. Their work appears in journals such as IEEE Internet of Things Journal, Future Generation Computer Systems, IEEE Transactions on Industrial Informatics, Applied Soft Computing and Nature Communications.
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.