Xing-Xing Lu

25 papers receiving 627 citations

Peers

Xing-Xing Lu
Comparison fields: 5 of 103
  • Cancer Research 94
  • Geriatrics and Gerontology 20
  • Molecular Biology 317
  • Immunology 78
  • Cell Biology 60
Replace Hua‐Jun He with:
Hua‐Jun He United States
Bei Liu United States
Ana Latorre Spain
Yung-Hao Wong Taiwan
Sun‐Joo Lee South Korea
Oscar Teijido United States
Jonathan A. Stefely United States
Cuiwen He United States
Yajie Xu China
Feng Jin China
Xing-Xing Lu relative to Hua‐Jun He United States Hua‐Jun He's profile →
Citations per field
00.5×2.7×
Hua‐Jun He · 1×
Citations per year

Countries citing papers authored by Xing-Xing Lu

Since Specialization
Citations

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

Fields of papers citing papers by Xing-Xing Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xing-Xing Lu. 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 Xing-Xing Lu. The network helps show where Xing-Xing Lu may publish in the future.

Co-authors

The 25 scholars most cited alongside Xing-Xing Lu, 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 Xing-Xing Lu Line = papers co-authored together Xing-Xing Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019105
2 201880
3 201579
4 201959
5 201648
6 201834
7 202032
8 201529
9 201226
10 201623
11 202123
12 202216
13 201816
14 202216
15 202114
16 202210
17 20205
18 20185
19 20194
20 20234

About Xing-Xing Lu

Xing-Xing Lu is a scholar working on Electrical and Electronic Engineering, Molecular Biology, Astronomy and Astrophysics, Biomedical Engineering and Computer Networks and Communications, having authored 26 papers that have together received 637 indexed citations. Recurring topics across this work include Terahertz technology and applications (12 papers), Superconducting and THz Device Technology (4 papers), Advanced Chemical Sensor Technologies (3 papers), Internet Traffic Analysis and Secure E-voting (3 papers), Photonic and Optical Devices (3 papers), Network Security and Intrusion Detection (3 papers), Network Packet Processing and Optimization (3 papers) and Allergic Rhinitis and Sensitization (2 papers). The work is most often cited by research in Cancer Research (94 citations), Geriatrics and Gerontology (20 citations), Molecular Biology (317 citations), Immunology (78 citations) and Cell Biology (60 citations). Xing-Xing Lu has collaborated with scholars based in China, United States and Pakistan. Frequent co-authors include Peng-Da Guo, Jianming Li, Wen-Juan Gan, Hua Wu, Jingru Wang, Hong‐Liang Cui, Xiu‐Ming Li, Xiao‐Shun He, Xiuming Li and Tianying Chang. Their work appears in journals such as Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Journal of Inflammation, Cancer Research, Autophagy and Journal of Network and Computer Applications.

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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