Ming Li

5.7k citations
227 papers · 4.0k indexed · 1 hit paper · h-index 34

Impact in

Papers in

Ming Li

195 papers receiving 3.8k citations

Hit Papers

Tri-training: exploiting unlabeled data using three classifiers 2005 · 801 citations
8012005202620122019250500750

Peers

Ming Li
Comparison fields: 5 of 159
  • Industrial and Manufacturing Engineering 925
  • Computer Networks and Communications 908
  • Building and Construction 474
  • Management Information Systems 241
  • Artificial Intelligence 859
Replace Qi Hao with:
Qi Hao China
Wei‐Chang Yeh Taiwan
Wolfgang Kästner Austria
Daqiang Zhang China
Nader Mohamed United States
Gang Xiong China
Jameela Al‐Jaroodi United States
Abdullah Konak United States
Runwei Cheng Japan
Lei Ren China
Ming Li relative to Qi Hao China Qi Hao's profile →
Citations per field
00.5×4.3×
Qi Hao · 1×
Citations per year

Countries citing papers authored by Ming Li

Since Specialization
Citations

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

Fields of papers citing papers by Ming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20256
2 20250
3 20251
4 20248
5 20245
6 20243
7 202420
8 20241
9 20240
10 202337
11 202353
12 202339
13 20235
14 20238
15 20231
16 202316
17 202310
18 201913
19 20172
20 19993

About Ming Li

Ming Li is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications, Information Systems, Building and Construction and Computer Vision and Pattern Recognition, having authored 227 papers that have together received 4.0k indexed citations. Recurring topics across this work include Advanced Manufacturing and Logistics Optimization (26 papers), Digital Transformation in Industry (25 papers), Blockchain Technology Applications and Security (20 papers), Manufacturing Process and Optimization (17 papers), Flexible and Reconfigurable Manufacturing Systems (11 papers), Scheduling and Optimization Algorithms (11 papers), Metaheuristic Optimization Algorithms Research (11 papers) and Mobile Ad Hoc Networks (10 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (925 citations), Computer Networks and Communications (908 citations), Building and Construction (474 citations), Management Information Systems (241 citations) and Artificial Intelligence (859 citations). Ming Li has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhi‐Hua Zhou, George Q. Huang, Gangyan Xu, Qing-An Zeng, Wen-Ben Jone, Ray Y. Zhong, Yishuo Jiang, Saijun Shao, Chun‐Hsien Chen and Balakrishnan Prabhakaran. Their work appears in journals such as Advanced Engineering Informatics, Computers & Industrial Engineering, Transportation Research Part E Logistics and Transportation Review, Journal of Manufacturing Systems and Automation in Construction.

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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