Qingkai Kong

2.0k citations
49 papers · 1.4k indexed · 1 hit paper · h-index 15
Topics
Seismology and Earthquake Studies (28 papers)Seismic Waves and Analysis (22 papers)Earthquake Detection and Analysis (14 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsGeophysical Research Letters

In The Last Decade

Qingkai Kong

48 papers receiving 1.3k citations

Hit Papers

Machine Learning in Seismology: Turning Data into Insights20182026202020232018100200300

Peers

Qingkai Kong
Comparison fields: 5 of 92
  • Geophysics 861
  • Artificial Intelligence 851
  • Civil and Structural Engineering 160
  • Applied Mathematics 130
  • Ocean Engineering 112
Replace Omar M. Saad with:
Omar M. Saad Egypt
Wenyuan Liao Canada
Wei‐Chau Xie Canada
P. J. Maechling United States
Zhenhua He China
Marco Iglesias United Kingdom
Waltraud Huyer Austria
Tiangang Cui Australia
Anna Maria Lombardi Italy
Weidong Zhao China
Qingkai Kong relative to Omar M. Saad Egypt Omar M. Saad's profile →
Citations per field
00.5×10×16.3×
Omar M. Saad · 1×
Citations per year

Countries citing papers authored by Qingkai Kong

Since Specialization
Citations

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

Fields of papers citing papers by Qingkai Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingkai Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Qingkai Kong. A scholar is included among the top collaborators of Qingkai Kong 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 Qingkai Kong. Qingkai Kong 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
#WorkIndexed citations
1 0
2 4
3 14
4 1
5 9
6 4
7 5
8 52
9 36
10 7
11 1
12
MyShake: Lessons from the first year of public earthquake early warning delivery in California
4
13 14
14 56
15 21
16
Using Smartphones to Detect Earthquakes
3
17 10
18
Positive solutions of boundary value problems with p-Laplacian
2
19 2
20 115

About Qingkai Kong

Qingkai Kong is a scholar working on Geophysics, Numerical Analysis and Artificial Intelligence, having authored 49 papers that have together received 1.4k indexed citations. Recurring topics across this work include Seismology and Earthquake Studies (28 papers), Seismic Waves and Analysis (22 papers) and Earthquake Detection and Analysis (14 papers). The work is most often cited by research in Geophysics (861 citations), Artificial Intelligence (851 citations) and Numerical Analysis (108 citations). Qingkai Kong has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include R. M. Allen, Peter Gerstoft, Daniel T. Trugman, Brendan J. Meade, Michael J. Bianco, Youngwoo Kwon, Zachary E. Ross, Shiyong Zhou, Han Yue and Yijian Zhou. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Geophysical Research Letters.

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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2026