Kaibin Shi

3.2k total citations · 1 hit paper
38 papers, 2.3k citations indexed

About

Kaibin Shi is a scholar working on Neurology, Neurology and Epidemiology. According to data from OpenAlex, Kaibin Shi has authored 38 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Neurology, 18 papers in Neurology and 10 papers in Epidemiology. Recurrent topics in Kaibin Shi's work include Neuroinflammation and Neurodegeneration Mechanisms (17 papers), Intracerebral and Subarachnoid Hemorrhage Research (11 papers) and Acute Ischemic Stroke Management (10 papers). Kaibin Shi is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (17 papers), Intracerebral and Subarachnoid Hemorrhage Research (11 papers) and Acute Ischemic Stroke Management (10 papers). Kaibin Shi collaborates with scholars based in China, United States and Germany. Kaibin Shi's co-authors include Fu‐Dong Shi, Andrew F. Ducruet, Qiang Liu, Michael T. Lawton, De‐Cai Tian, Zhiguo Li, Kevin N. Sheth, Samuel Shi, Jing‐fei Dong and Kristofer Wood and has published in prestigious journals such as Cell, Nature Neuroscience and Immunity.

In The Last Decade

Kaibin Shi

38 papers receiving 2.3k citations

Hit Papers

Global brain inflammation in stroke 2019 2026 2021 2023 2019 200 400 600

Peers

Kaibin Shi
Comparison fields: 5 of 106
  • Neurology 1.1k
  • Neurology 697
  • Molecular Biology 688
  • Epidemiology 514
  • Immunology 478
Replace Honglei Ren with:
Honglei Ren China
Xiaoyan Jiang United States
Wei Cai China
Xiao‐Yi Xiong China
Hongjian Pu United States
Li Sun China
Masato Kanazawa Japan
Michael K. Schuhmann Germany
Lidia García‐Bonilla United States
Peter Kraft Germany
Honglei Ren China View profile →
Citations per field, relative to Kaibin Shi
Kaibin Shi · 1×
Citations per year, relative to Kaibin Shi
Kaibin Shi · 1×

Countries citing papers authored by Kaibin Shi

Since Specialization
Citations

This map shows the geographic impact of Kaibin Shi'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 Kaibin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaibin Shi more than expected).

Fields of papers citing papers by Kaibin Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kaibin Shi. 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 Kaibin Shi. The network helps show where Kaibin Shi may publish in the future.

Co-authorship network of co-authors of Kaibin Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Kaibin Shi. A scholar is included among the top collaborators of Kaibin Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kaibin Shi. Kaibin Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 4
2 2
3 1
4 3
5 4
6 13
7 10
8 37
9 4
10 92
11 15
12 7
13 56
14 55
15
Global brain inflammation in stroke breakdown →
656
16 26
17 148
18 47
19 96
20 22

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.

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