Chunfeng Cui

29 papers receiving 381 citations

Peers

Chunfeng Cui
Comparison fields: 5 of 66
  • Computational Mathematics 158
  • Computational Theory and Mathematics 143
  • Statistics, Probability and Uncertainty 63
  • Numerical Analysis 33
  • Statistical and Nonlinear Physics 53
Replace Kim Batselier with:
Kim Batselier Hong Kong
Elias Tsigaridas France
G. Lotti Italy
Guang-Xin Huang China
Carmeliza Navasca United States
Michael Brazell United States
Zhengfeng Yang China
Roland Hildebrand France
Zhening Li United Kingdom
Chunfeng Cui relative to Kim Batselier Hong Kong Kim Batselier's profile →
Citations per field
00.5×3.9×
Kim Batselier · 1×
Citations per year

Countries citing papers authored by Chunfeng Cui

Since Specialization
Citations

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

Fields of papers citing papers by Chunfeng Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201495
2 201838
3 201634
4 201629
5 201926
6 202418
7 201817
8 202014
9 201913
10 201812
11
A FEASIBLE TRUST-REGION METHOD FOR CALCULATING EXTREME Z-EIGENVALUES OF SYMMETRIC TENSORS
201512
12 202411
13 20249
14 20238
15 20177
16 20167
17 20246
18 20226
19 20206
20 20234

About Chunfeng Cui

Chunfeng Cui is a scholar working on Computational Theory and Mathematics, Computational Mathematics, Electrical and Electronic Engineering, Computational Mechanics and Artificial Intelligence, having authored 39 papers that have together received 394 indexed citations. Recurring topics across this work include Tensor decomposition and applications (11 papers), Probabilistic and Robust Engineering Design (7 papers), Sparse and Compressive Sensing Techniques (7 papers), Matrix Theory and Algorithms (6 papers), Advanced Optimization Algorithms Research (4 papers), Model Reduction and Neural Networks (4 papers), Parallel Computing and Optimization Techniques (3 papers) and Blind Source Separation Techniques (3 papers). The work is most often cited by research in Computational Mathematics (158 citations), Computational Theory and Mathematics (143 citations), Statistics, Probability and Uncertainty (63 citations), Numerical Analysis (33 citations) and Statistical and Nonlinear Physics (53 citations). Chunfeng Cui has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zheng Zhang, Yu‐Hong Dai, Jiawang Nie, Liqun Qi, Qinyu Chen, Jingjing Zhang, Hong Yan, Xiongjun Zhang, Minru Bai and Guyan Ni. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, SIAM Journal on Imaging Sciences, Journal of Scientific Computing, Journal of Optimization Theory and Applications and SIAM Journal on Matrix Analysis and 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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