Cheng Cheng

623 total citations
48 papers, 365 citations indexed

About

Cheng Cheng is a scholar working on Computational Mechanics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Cheng Cheng has authored 48 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computational Mechanics, 15 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Cheng Cheng's work include Advanced Graph Neural Networks (11 papers), Sparse and Compressive Sensing Techniques (9 papers) and Complex Network Analysis Techniques (7 papers). Cheng Cheng is often cited by papers focused on Advanced Graph Neural Networks (11 papers), Sparse and Compressive Sensing Techniques (9 papers) and Complex Network Analysis Techniques (7 papers). Cheng Cheng collaborates with scholars based in China, United States and Canada. Cheng Cheng's co-authors include Qiyu Sun, Emanuel Parzen, Junzheng Jiang, Xiaosheng Cheng, Ning Dai, Cong Xu, Ramana Rao Kompella, Qingjin Peng, James Caverlee and Yun He and has published in prestigious journals such as Kidney International, IEEE Transactions on Signal Processing and Neurocomputing.

In The Last Decade

Cheng Cheng

44 papers receiving 358 citations

Peers

Cheng Cheng
Comparison fields: 5 of 92
  • Artificial Intelligence 96
  • Computer Vision and Pattern Recognition 79
  • Computational Mechanics 57
  • Radiation 49
  • Computer Networks and Communications 43
Replace Cristina García–Cardona with:
Cristina García–Cardona United States
Elias S. Helou Brazil
Max Simchowitz United States
S. Bellini Italy
Gyemin Lee South Korea
Ali Ahmed Pakistan
Huishuai Zhang United States
Ramakrishnan Kannan United States
Cristina García–Cardona United States View profile →
Citations per field, relative to Cheng Cheng
Cheng Cheng · 1×
Citations per year, relative to Cheng Cheng
Cheng Cheng · 1×

Countries citing papers authored by Cheng Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Cheng. A scholar is included among the top collaborators of Cheng Cheng 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 Cheng Cheng. Cheng Cheng 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 0
2 0
3 1
4 25
5 1
6 2
7 5
8 3
9 7
10 1
11 6
12 2
13 26
14 22
15
The Buss Reduction for the k-Weighted Vertex Cover Problem.
1
16
Study on Big Data and Intelligence in the Campaign of Crime Crackdown
1
17 29
18 20
19 2
20
On local fairing algorithm for cubic B-spline with discrete curvature
1

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

Rankless by CCL
2026