Manling Li

1.3k citations
52 papers · 488 · h-index 11

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Advanced Graph Neural Networks
    • Domain Adaptation and Few-Shot Learning
    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques

Papers in

Manling Li

45 papers receiving 472 citations

Peers

Manling Li
Comparison fields: 5 of 95
  • Artificial Intelligence 327
  • Computer Vision and Pattern Recognition 120
  • Management Science and Operations Research 45
  • Information Systems 48
  • General Social Sciences 5
Replace Hongyu Ren with:
Hongyu Ren United States
Cícero Nogueira dos Santos United States
Biao Zhao China
Ledell Wu China
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Xuanjing Huang China
Diego Marcheggiani Italy
Jungo Kasai United States
Qinmin Hu Canada
Xilun Chen United States
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Citations per field
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Hongyu Ren · 1×
Citations per year

Countries citing papers authored by Manling Li

Since Specialization
Citations

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

Fields of papers citing papers by Manling Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201968
2 202258
3 202044
4 202044
5 201920
6 202019
7 202317
8 202417
9 202116
10 201815
11 202113
12 202110
13 201910
14 202210
15 20219
16 20149
17 20199
18 20238
19 20228
20 20238

About Manling Li

Manling Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Management Science and Operations Research and Aerospace Engineering, having authored 52 papers that have together received 488 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (14 papers), Multimodal Machine Learning Applications (11 papers), Advanced Graph Neural Networks (7 papers), Data Quality and Management (5 papers), Advanced Text Analysis Techniques (4 papers), Fluid Dynamics and Turbulent Flows (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Artificial Intelligence (327 citations), Computer Vision and Pattern Recognition (120 citations), Management Science and Operations Research (45 citations), Information Systems (48 citations) and General Social Sciences (5 citations). Manling Li has collaborated with scholars based in United States, China and Jamaica. Frequent co-authors include Heng Ji, Heng Ji, Richard J. Radke, Lingyu Zhang, Clare R. Voss, Xudong Lin, Shih-Fu Chang, Qi Zeng, Ying Lin and Nathanael Chambers. Their work appears in journals such as Physics of Fluids, Aerospace Science and Technology, Cell Transplantation, American Journal of Medical Genetics Part B Neuropsychiatric Genetics and IEEE Transactions on Big Data.

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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