Yanming Shen

4.6k citations
143 papers · 3.3k · 2 hit papers · h-index 31

Impact in

Papers in

Yanming Shen

140 papers receiving 3.2k citations

Yanming Shen's Hit Papers

Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions 2022 · 317 citations
3170+1+3Years since publication100200300

Peers

Yanming Shen
Comparison fields: 5 of 138
  • Transportation 459
  • Building and Construction 664
  • Computer Networks and Communications 651
  • Media Technology 219
  • Signal Processing 258
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Citations per field
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Citations per year

Countries citing papers authored by Yanming Shen

Since Specialization
Citations

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

Fields of papers citing papers by Yanming Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions
Hit paper breakdown →
2022317
2
Do Transformers Really Perform Badly for Graph Representation
Hit paper breakdown →
2021259
3 2020147
4 2005142
5 2019102
6 201397
7 200995
8 201479
9 201874
10 202074
11 200773
12 200862
13 201061
14 201959
15 202258
16 201458
17
Energy Consumption in Cloud Computing Data Centers
201453
18 200749
19 201547
20 201444

About Yanming Shen

Yanming Shen is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Materials Chemistry, Building and Construction and Transportation, having authored 143 papers that have together received 3.3k indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (18 papers), Layered Double Hydroxides Synthesis and Applications (17 papers), Interconnection Networks and Systems (13 papers), Transportation Planning and Optimization (12 papers), Caching and Content Delivery (12 papers), Peer-to-Peer Network Technologies (10 papers), Human Mobility and Location-Based Analysis (9 papers) and Indoor and Outdoor Localization Technologies (9 papers). The work is most often cited by research in Transportation (459 citations), Building and Construction (664 citations), Computer Networks and Communications (651 citations), Media Technology (219 citations) and Signal Processing (258 citations). Yanming Shen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Heng Qi, Keqiu Li, Baocai Yin, Shivendra S. Panwar, Shifeng Li, Xueyan Yin, Wenyu Qu, Zhengye Liu, Keith W. Ross and Lihui Fan. Their work appears in journals such as IEEE Transactions on Communications, Applied Surface Science, Knowledge-Based Systems, Expert Systems with Applications and IEEE Transactions on Intelligent Transportation Systems.

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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