Mingwei Li

447 citations
32 papers · 270 · h-index 8

Impact in

Papers in

Mingwei Li

27 papers receiving 262 citations

Peers

Mingwei Li
Comparison fields: 5 of 77
  • Computer Vision and Pattern Recognition 66
  • Artificial Intelligence 98
  • Computer Networks and Communications 44
  • Signal Processing 20
  • Management Science and Operations Research 17
Replace Nagat Drawel with:
Nagat Drawel Canada
Xiao-Zhi Gao Finland
M. Thenmozhi India
Jiashuai Shi China
Lijuan Zhou China
Ruilin Liu United States
Yogesh Kumar India
Yongjian Ren China
Diletta Chiaro Italy
Mingwei Li relative to Nagat Drawel Canada Nagat Drawel's profile →
Citations per field
00.5×10×15×19×
Nagat Drawel · 1×
Citations per year

Countries citing papers authored by Mingwei Li

Since Specialization
Citations

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

Fields of papers citing papers by Mingwei Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021103
2 201841
3 201828
4 202416
5 201213
6 20209
7 20208
8 20177
9 20127
10 20245
11 20234
12 20243
13
NNCubes: Learned Structures for Visual Data Exploration.
20183
14 20243
15 20213
16 20212
17 20132
18 20232
19 20202
20 20242

About Mingwei Li

Mingwei Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Electrical and Electronic Engineering, having authored 32 papers that have together received 270 indexed citations. Recurring topics across this work include Data Visualization and Analytics (7 papers), Anomaly Detection Techniques and Applications (4 papers), Data Stream Mining Techniques (4 papers), Energy Efficient Wireless Sensor Networks (3 papers), Online and Blended Learning (2 papers), Quantum Computing Algorithms and Architecture (2 papers), Cloud Computing and Resource Management (2 papers) and Music and Audio Processing (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (66 citations), Artificial Intelligence (98 citations), Computer Networks and Communications (44 citations), Signal Processing (20 citations) and Management Science and Operations Research (17 citations). Mingwei Li has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Wei‐Chiang Hong, Carlos Scheidegger, Michael Correll, Gordon Kindlmann, Yuanwei Jing, L. Zhou, Yongjian Ren, Jian Wan, Jue Wang and Jilin Zhang. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Access, Computer Graphics Forum, Nonlinear Dynamics and INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service 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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