Guoming Lu

615 citations
42 papers · 380 · h-index 11

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Graph Neural Networks
    • Anomaly Detection Techniques and Applications
    • Advanced Text Analysis Techniques
    • Privacy-Preserving Technologies in Data

Papers in

Guoming Lu

39 papers receiving 366 citations

Peers

Guoming Lu
Comparison fields: 5 of 75
  • Artificial Intelligence 202
  • Computer Science Applications 24
  • Computer Networks and Communications 81
  • Information Systems 64
  • Computer Vision and Pattern Recognition 50
Replace Bin Fu with:
Bin Fu United States
Manisha Verma United States
Depeng Dang China
Kevin Zhao United States
Zongda Wu China
Muhammad Arif Shah Pakistan
Yiqun Diao Singapore
Dariusz Król Poland
Libing Wu China
Guoming Lu relative to Bin Fu United States Bin Fu's profile →
Citations per field
00.5×2.8×
Bin Fu · 1×
Citations per year

Countries citing papers authored by Guoming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Guoming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202250
2 202239
3 201438
4 202031
5 202129
6 202026
7 201025
8 202023
9 201912
10 202112
11 202410
12 20218
13 20078
14 20227
15 20077
16 20216
17 20226
18 20255
19 20085
20 20215

About Guoming Lu

Guoming Lu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Sociology and Political Science and Information Systems, having authored 42 papers that have together received 380 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Privacy-Preserving Technologies in Data (5 papers), Natural Language Processing Techniques (5 papers), Adversarial Robustness in Machine Learning (4 papers), Advanced Graph Neural Networks (4 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Privacy, Security, and Data Protection (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (202 citations), Computer Science Applications (24 citations), Computer Networks and Communications (81 citations), Information Systems (64 citations) and Computer Vision and Pattern Recognition (50 citations). Guoming Lu has collaborated with scholars based in China, United States and Austria. Frequent co-authors include Ke Qin, Hailin Wang, Aiguo Chen, Guangchun Luo, Xu Zheng, Yang Fu, Rufai Yusuf Zakari, Zhipeng Cai, Wenhong Tian and Kaiyang Li. Their work appears in journals such as Knowledge-Based Systems, Computers & Electrical Engineering, Neurocomputing, Tsinghua Science & Technology and IEEE Transactions on Mobile Computing.

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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