Lingchen Kong

52 papers receiving 533 citations

Peers

Lingchen Kong
Comparison fields: 5 of 75
  • Numerical Analysis 169
  • Computational Mathematics 7
  • Statistics and Probability 90
  • Computational Theory and Mathematics 151
  • Computational Mechanics 154
Replace Stephen Montgomery-Smith with:
Stephen Montgomery-Smith United States
Peter J. Grabner Austria
Mohammed Yusuf Waziri Nigeria
George M. Phillips United Kingdom
Alvaro R. De Pierro Brazil
Horst Martini Germany
Qi He China
Stefania Bellavia Italy
Max Simchowitz United States
Dirk Nuyens Belgium
Lingchen Kong relative to Stephen Montgomery-Smith United States Stephen Montgomery-Smith's profile →
Citations per field
00.5×7.7×
Stephen Montgomery-Smith · 1×
Citations per year

Countries citing papers authored by Lingchen Kong

Since Specialization
Citations

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

Fields of papers citing papers by Lingchen Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201786
2 202377
3 200865
4 201747
5 200929
6 201318
7 200917
8 202516
9 201414
10 202311
11 202110
12 201010
13 20139
14 20138
15 20208
16 20228
17 20168
18
The Fischer-Burmeister Complementarity Function on Euclidean Jordan Algebras∗
20088
19 20077
20 20187

About Lingchen Kong

Lingchen Kong is a scholar working on Computational Mechanics, Computational Theory and Mathematics, Numerical Analysis, Biomedical Engineering and Statistics and Probability, having authored 55 papers that have together received 564 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (29 papers), Advanced Optimization Algorithms Research (10 papers), Optimization and Variational Analysis (9 papers), Statistical Methods and Inference (8 papers), Microwave Imaging and Scattering Analysis (8 papers), Matrix Theory and Algorithms (7 papers), Advanced Statistical Methods and Models (5 papers) and Direction-of-Arrival Estimation Techniques (4 papers). The work is most often cited by research in Numerical Analysis (169 citations), Computational Mathematics (7 citations), Statistics and Probability (90 citations), Computational Theory and Mathematics (151 citations) and Computational Mechanics (154 citations). Lingchen Kong has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Naihua Xiu, Jie Sun, Levent Tunçel, Yu Li, Jun Fan, Wei Feng, Hui Zou, Shiqian Ma, Shixue Zhang and Cong Peng. Their work appears in journals such as Journal of Optimization Theory and Applications, Computational Optimization and Applications, Journal of Computational and Applied Mathematics, Applied Mathematics and Computation and Linear Algebra and its 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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