Ming Ling

660 citations
60 papers · 413 indexed · h-index 10
Topics
Parallel Computing and Optimization Techniques (30 papers)Advanced Data Storage Technologies (16 papers)Low-power high-performance VLSI design (13 papers)
Partner nations
ChinaCanadaBelgium

In The Last Decade

Ming Ling

49 papers receiving 402 citations

Peers

Ming Ling
Comparison fields: 5 of 98
  • Electrical and Electronic Engineering 124
  • Hardware and Architecture 103
  • Computer Networks and Communications 97
  • Molecular Biology 81
  • Computational Theory and Mathematics 74
Replace Hiroyoshi Morita with:
Hiroyoshi Morita Japan
Rahul Tripathi United States
Noriyuki Fujimoto Japan
Aixia Liu China
Reza Rahimi United States
Jintao Meng China
Lixia Zhang China
Yeh Yeh Taiwan
Ming Ling relative to Hiroyoshi Morita Japan Hiroyoshi Morita's profile →
Citations per field
00.5×6.4×
Hiroyoshi Morita · 1×
Citations per year

Countries citing papers authored by Ming Ling

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Ling

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Ling. A scholar is included among the top collaborators of Ming Ling 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 Ming Ling. Ming Ling 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
1 0
2 0
3 1
4 7
5 2
6 2
7 18
8 0
9 2
10 57
11 3
12 2
13 3
14 4
15 11
16 4
17 9
18 2
19
Coverage Directed Vector Generation for Functional Verification Using Genetic Algorithm
1
20 4

About Ming Ling

Ming Ling is a scholar working on Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 60 papers that have together received 413 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (30 papers), Advanced Data Storage Technologies (16 papers) and Low-power high-performance VLSI design (13 papers). The work is most often cited by research in Hardware and Architecture (103 citations), Computational Theory and Mathematics (74 citations) and Computer Networks and Communications (97 citations). Ming Ling has collaborated with scholars based in China, Canada and Belgium. Frequent co-authors include Longxing Shi, Jiansheng Wu, Shidi Tang, Haifeng Hu, Ruiqi Chen, Jianping Pan, Liang He, Kaiyang Liu, Zhiwu Huang and Jun Peng. Their work appears in journals such as IEEE Access, Molecules and IEEE Transactions on Vehicular Technology.

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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