Xinghui Chen

2.7k citations
18 papers · 825 · h-index 11

Impact in

    • COVID-19 epidemiological studies
    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 detection and testing
    • Viral Infections and Outbreaks Research

Papers in

    • SARS-CoV-2 and COVID-19 Research 10
    • COVID-19 Clinical Research Studies 6
    • SARS-CoV-2 detection and testing 2
    • Vaccine Coverage and Hesitancy 5

Xinghui Chen

17 papers receiving 815 citations

Peers

Xinghui Chen
Comparison fields: 5 of 94
  • Modeling and Simulation 373
  • Infectious Diseases 582
  • Health 243
  • Neurology 47
  • Obstetrics and Gynecology 24
Replace Molly Steele with:
Molly Steele United States
Yeheskel Levy Israel
Cécile Tran Kiem France
Bingyi Yang Hong Kong
Ruijia Sun China
Talía M. Quandelacy United States
Gregory Barnsley United Kingdom
Noémie Courtejoie France
Pragati Prasad United States
Kalaiarasu M. Peariasamy Malaysia
Xinghui Chen relative to Molly Steele United States Molly Steele's profile →
Citations per field
00.5×1.5×2.2×
Molly Steele · 1×
Citations per year

Countries citing papers authored by Xinghui Chen

Since Specialization
Citations

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

Fields of papers citing papers by Xinghui Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xinghui Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xinghui Chen Line = papers co-authored together Xinghui Chen links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2020243
2 2021148
3 2020128
4 2021126
5 202167
6 202227
7 202023
8 202214
9 202212
10 202310
11 202110
12 20228
13 20224
14 20232
15 20251
16 20231
17 20241
18 20250

About Xinghui Chen

Xinghui Chen is a scholar working on Infectious Diseases, Health, Modeling and Simulation, Animal Science and Zoology and Epidemiology, having authored 18 papers that have together received 825 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (10 papers), COVID-19 Clinical Research Studies (6 papers), COVID-19 epidemiological studies (5 papers), Vaccine Coverage and Hesitancy (5 papers), Animal Virus Infections Studies (3 papers), SARS-CoV-2 detection and testing (2 papers), Meningioma and schwannoma management (1 paper) and Pituitary Gland Disorders and Treatments (1 paper). The work is most often cited by research in Modeling and Simulation (373 citations), Infectious Diseases (582 citations), Health (243 citations), Neurology (47 citations) and Obstetrics and Gynecology (24 citations). Xinghui Chen has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Hongjie Yu, Qianhui Wu, Marco Ajelli, Cécile Viboud, Juan Yang, Xufang Bai, Kaige Dong, Tingyu Zhuang, Matthew Z. Dudley and Daniel A. Salmon. Their work appears in journals such as BMC Medicine, Clinical Infectious Diseases, Child s Nervous System, Science and Biomedicine & Pharmacotherapy.

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.

Explore authors with similar magnitude of impact