Min Zhu

1.4k citations
101 papers · 771 · h-index 15

Impact in

Papers in

Min Zhu

90 papers receiving 738 citations

Peers

Min Zhu
Comparison fields: 5 of 140
  • Computer Vision and Pattern Recognition 149
  • Modeling and Simulation 32
  • Statistical and Nonlinear Physics 63
  • Analytical Chemistry 41
  • Control and Systems Engineering 95
Replace Kejia Chen with:
Kejia Chen China
William Guo Australia
Marco Turchi Italy
Manjusha Pandey India
Faten Khalid Karim Saudi Arabia
Pramod Kumar Singh India
Răzvan Andonie United States
Mohammad Ehsan Basiri Iran
Aswani Kumar Cherukuri India
Mahendra Kumar Gourisaria India
Min Zhu relative to Kejia Chen China Kejia Chen's profile →
Citations per field
00.5×1.5×2.5×
Kejia Chen · 1×
Citations per year

Countries citing papers authored by Min Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Min Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 101 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202044
2 201541
3 201838
4 201438
5 199936
6 201232
7 201830
8 202228
9 201323
10 201922
11 202321
12 201521
13 202020
14 201914
15 201514
16 202314
17 202013
18 201912
19 202012
20 201811

About Min Zhu

Min Zhu is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering and Aerospace Engineering, having authored 101 papers that have together received 771 indexed citations. Recurring topics across this work include Data Visualization and Analytics (13 papers), Genomics and Chromatin Dynamics (7 papers), RNA and protein synthesis mechanisms (6 papers), Complex Network Analysis Techniques (6 papers), RNA modifications and cancer (5 papers), Video Analysis and Summarization (5 papers), Machine Learning in Bioinformatics (5 papers) and Team Dynamics and Performance (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (149 citations), Modeling and Simulation (32 citations), Statistical and Nonlinear Physics (63 citations), Analytical Chemistry (41 citations) and Control and Systems Engineering (95 citations). Min Zhu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Junqiang Song, Huaqing Wang, Haibo Du, Di Wu, Yongqing Zhang, Tian Tian, Fukang Yin, Yingying Cheng, Dwight S. Walker and Xiaoyu Zhu. Their work appears in journals such as Advances in Difference Equations, IEEE Transactions on Circuits & Systems II Express Briefs, Journal of Visual Languages & Computing, Plant Biotechnology Journal and Chemometrics and Intelligent Laboratory Systems.

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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