Faming Lu

29 papers receiving 399 citations

Peers

Faming Lu
Comparison fields: 5 of 64
  • Management Information Systems 239
  • Information Systems 205
  • Computational Theory and Mathematics 82
  • Industrial and Manufacturing Engineering 49
  • Statistics, Probability and Uncertainty 25
Replace Filip Caron with:
Filip Caron Belgium
Nick van Beest Australia
Wangyang Yu China
Marek Grzegorowski Poland
Wen Jun Tan Singapore
Dnyanesh Rajpathak United States
Elisa Marengo Italy
Lee W. Wagenhals United States
Alexander Wise United States
Yagil Engel Israel
Faming Lu relative to Filip Caron Belgium Filip Caron's profile →
Citations per field
00.5×6.8×
Filip Caron · 1×
Citations per year

Countries citing papers authored by Faming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Faming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Faming 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 Faming Lu Line = papers co-authored together Faming Lu 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 201691
2 201473
3 201461
4 201724
5 202219
6 201417
7 201114
8 201514
9 201612
10 201612
11 20229
12 20199
13 20196
14 20196
15 20225
16 20195
17 20235
18 20124
19 20214
20 20202

About Faming Lu

Faming Lu is a scholar working on Management Information Systems, Information Systems, Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications, having authored 32 papers that have together received 404 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (16 papers), Petri Nets in System Modeling (9 papers), Service-Oriented Architecture and Web Services (9 papers), Software System Performance and Reliability (4 papers), Semantic Web and Ontologies (3 papers), Flexible and Reconfigurable Manufacturing Systems (2 papers), Data Management and Algorithms (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Management Information Systems (239 citations), Information Systems (205 citations), Computational Theory and Mathematics (82 citations), Industrial and Manufacturing Engineering (49 citations) and Statistics, Probability and Uncertainty (25 citations). Faming Lu has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Qingtian Zeng, Hua Duan, Cong Liu, MengChu Zhou, Jiujun Cheng, Fuxin Zhang, An Liu, Mengfan Tang, Libao Zhang and Zhaoyang Cai. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Access, Expert Systems with Applications, Information Sciences and Applied Intelligence.

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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