Gengming Zhang

664 total citations · 1 hit paper
33 papers, 481 citations indexed

About

Gengming Zhang is a scholar working on Electrical and Electronic Engineering, Surgery and Mechanical Engineering. According to data from OpenAlex, Gengming Zhang has authored 33 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 7 papers in Surgery and 6 papers in Mechanical Engineering. Recurrent topics in Gengming Zhang's work include Advanced Memory and Neural Computing (7 papers), Thin-Film Transistor Technologies (5 papers) and High Entropy Alloys Studies (4 papers). Gengming Zhang is often cited by papers focused on Advanced Memory and Neural Computing (7 papers), Thin-Film Transistor Technologies (5 papers) and High Entropy Alloys Studies (4 papers). Gengming Zhang collaborates with scholars based in China, United States and Hong Kong. Gengming Zhang's co-authors include Jia Sun, Junliang Yang, Chenxing Jin, Yunchao Xu, Xueping Gan, Kechao Zhou, Chao Chen, Wanrong Liu, Pei He and Yulong Huang and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Gengming Zhang

29 papers receiving 464 citations

Hit Papers

Geometry‐Aware 3D Point Cloud Learning for Precise Cuttin... 2025 2026 2025 5 10 15

Peers

Gengming Zhang
Comparison fields: 5 of 72
  • Electrical and Electronic Engineering 255
  • Mechanical Engineering 135
  • Cellular and Molecular Neuroscience 106
  • Materials Chemistry 98
  • Polymers and Plastics 68
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Citations per field, relative to Gengming Zhang
Gengming Zhang · 1×
Citations per year, relative to Gengming Zhang
Gengming Zhang · 1×

Countries citing papers authored by Gengming Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Gengming Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gengming Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Gengming Zhang. A scholar is included among the top collaborators of Gengming Zhang 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 Gengming Zhang. Gengming Zhang 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
Geometry‐Aware 3D Point Cloud Learning for Precise Cutting‐Point Detection in Unstructured Field Environments breakdown →
19
2 1
3 0
4 0
5 1
6 1
7 0
8 3
9 5
10 3
11 0
12 10
13 5
14 8
15 21
16 3
17 6
18 34
19 2
20 6

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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