Dongsheng Li

8.1k citations
336 papers · 4.5k indexed · 5 hit papers · h-index 33

Dongsheng Li

293 papers receiving 4.3k citations

Hit Papers

Large Language Mo...742017202620202023100200300

Peers

Dongsheng Li
Comparison fields: 5 of 165
  • Artificial Intelligence 1.7k
  • Computer Vision and Pattern Recognition 995
  • Computer Networks and Communications 830
  • Information Systems 744
  • Hardware and Architecture 135
Replace L.M. Patnaik with:
L.M. Patnaik India
Quan Zhang China
Qi Hao China
Dunwei Gong China
Cesare Alippi Italy
Meiqin Liu China
Minrui Fei China
Suresh Sundaram Singapore
Erik D. Goodman United States
Jianping Wang China
Dongsheng Li relative to L.M. Patnaik India L.M. Patnaik's profile →
Citations per field
00.5×10×15×18×
L.M. Patnaik · 1×
Citations per year

Countries citing papers authored by Dongsheng Li

Since Specialization
Citations

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

Fields of papers citing papers by Dongsheng Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202418
2 20243
3 20246
4 20241
5 20243
6 20240
7 20242
8 20244
9 20248
10 20230
11 202334
12 20230
13 20230
14 202116
15 202027
16
NENN: Incorporate Node and Edge Features in Graph Neural Networks
202012
17 201919
18 20194
19 20130
20
Study on Characteristics of Genetic Algorithms and Its Application to Optimize Reloading Pattern Problem
20031

About Dongsheng Li

Dongsheng Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 336 papers that have together received 4.5k indexed citations. Recurring topics across this work include Topic Modeling (45 papers), Caching and Content Delivery (35 papers), Advanced Neural Network Applications (33 papers), Cloud Computing and Resource Management (33 papers), Natural Language Processing Techniques (31 papers), Stochastic Gradient Optimization Techniques (28 papers), Advanced Graph Neural Networks (27 papers) and Advanced Data Storage Technologies (21 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Computer Vision and Pattern Recognition (995 citations) and Computer Networks and Communications (830 citations). Dongsheng Li has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Tao Sun, Xicheng Lu, Linbo Qiao, Yiming Zhang, Bao Wang, Zhaoning Zhang, Zhigang Kan, Yong Dou, Dawei Feng and Ke Yang. Their work appears in journals such as Nature, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

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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