Hongjin He

891 citations
59 papers · 589 indexed · h-index 15
Topics
Sparse and Compressive Sensing Techniques (31 papers)Advanced Optimization Algorithms Research (31 papers)Tensor decomposition and applications (19 papers)
Partner nations
ChinaHong KongSingapore

In The Last Decade

Hongjin He

52 papers receiving 563 citations

Peers

Hongjin He
Comparison fields: 5 of 46
  • Computational Theory and Mathematics 328
  • Numerical Analysis 240
  • Computational Mechanics 227
  • Computational Mathematics 208
  • Electrical and Electronic Engineering 57
Replace Guang-Xin Huang with:
Guang-Xin Huang China
Zheng‐Jian Bai China
Quoc Tran Dinh Belgium
Luba Tetruashvili Israel
Alberto Seeger France
Roland Hildebrand France
Margherita Porcelli Italy
Samir Adly France
Jürgen Garloff Germany
Phillip A. Regalia United States
Hongjin He relative to Guang-Xin Huang China Guang-Xin Huang's profile →
Citations per field
00.5×4.8×
Guang-Xin Huang · 1×
Citations per year

Countries citing papers authored by Hongjin He

Since Specialization
Citations

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

Fields of papers citing papers by Hongjin He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongjin He

This figure shows the co-authorship network connecting the top 25 collaborators of Hongjin He. A scholar is included among the top collaborators of Hongjin He 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 Hongjin He. Hongjin He 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
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12 44
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An efficient nonnegativity preserving algorithm for multilinear systems with nonsingular M-tensors
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About Hongjin He

Hongjin He is a scholar working on Computational Mathematics, Numerical Analysis and Computational Theory and Mathematics, having authored 59 papers that have together received 589 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (31 papers), Advanced Optimization Algorithms Research (31 papers) and Tensor decomposition and applications (19 papers). The work is most often cited by research in Computational Mathematics (208 citations), Numerical Analysis (240 citations) and Computational Theory and Mathematics (328 citations). Hongjin He has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Chen Ling, Liqun Qi, Hong‐Kun Xu, Qinghua Feng, Deren Han, Guanglu Zhou, Kai Wang, Deren Han, Jitamitra Desai and Ling Chen. Their work appears in journals such as Chemical Engineering Journal, Applied Mathematics and Computation and Applied Mathematical Modelling.

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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