Jun‐e Feng

1.5k citations
84 papers · 1.1k indexed · h-index 18
Topics
Gene Regulatory Network Analysis (44 papers)Receptor Mechanisms and Signaling (16 papers)Formal Methods in Verification (14 papers)
Journals
SHILAP Revista de lepidopterologíaAutomaticaInformation Sciences
Partner nations
ChinaSingaporeHong Kong

In The Last Decade

Jun‐e Feng

75 papers receiving 1.1k citations

Peers

Jun‐e Feng
Comparison fields: 5 of 60
  • Molecular Biology 679
  • Computational Theory and Mathematics 350
  • Control and Systems Engineering 291
  • Computer Networks and Communications 255
  • Biomedical Engineering 118
Replace Kuize Zhang with:
Kuize Zhang China
Guodong Zhao China
Shiyong Zhu China
Ching-Tai Lin United States
Chi Huang China
Sean Summers Switzerland
Ankur Agrawal United States
Alain Bretto France
Chung-Shou Liao Taiwan
Gina M. B. Oliveira Brazil
Jun‐e Feng relative to Kuize Zhang China Kuize Zhang's profile →
Citations per field
00.5×1.5×1.9×
Kuize Zhang · 1×
Citations per year

Countries citing papers authored by Jun‐e Feng

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐e Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐e Feng. 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 Jun‐e Feng. The network helps show where Jun‐e Feng may publish in the future.

Co-authorship network of co-authors of Jun‐e Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Jun‐e Feng. A scholar is included among the top collaborators of Jun‐e Feng 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 Jun‐e Feng. Jun‐e Feng 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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Optimal distributed fusion of two-channel observation systems with correlated noises
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20 8

About Jun‐e Feng

Jun‐e Feng is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Control and Systems Engineering, having authored 84 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (44 papers), Receptor Mechanisms and Signaling (16 papers) and Formal Methods in Verification (14 papers). The work is most often cited by research in Computational Mathematics (19 citations), Computational Theory and Mathematics (350 citations) and Control and Systems Engineering (291 citations). Jun‐e Feng has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Min Meng, Biao Wang, Yongyuan Yu, Daizhan Cheng, Haitao Li, Jianli Zhao, Guodong Zhao, James Lam, Peihe Wang and Hongli Lv. Their work appears in journals such as SHILAP Revista de lepidopterología, Automatica and Information Sciences.

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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