Sheng Di

3.9k citations
126 papers · 2.1k · h-index 23

Impact in

Papers in

Sheng Di

118 papers receiving 2.1k citations

Peers

Sheng Di
Comparison fields: 5 of 84
  • Hardware and Architecture 649
  • Computer Networks and Communications 1.3k
  • Computational Mathematics 15
  • Information Systems 561
  • Artificial Intelligence 783
Replace Timothy G. Mattson with:
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Sheng Di relative to Timothy G. Mattson United States Timothy G. Mattson's profile →
Citations per field
00.5×12×
Timothy G. Mattson · 1×
Citations per year

Countries citing papers authored by Sheng Di

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Di

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 126 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017191
2 2018172
3 201999
4 202198
5 201296
6 201289
7 201885
8 202060
9 201359
10 202052
11 201450
12 201950
13 201847
14 201442
15 201639
16 201737
17 202133
18 201330
19 201928
20 201425

About Sheng Di

Sheng Di is a scholar working on Computer Networks and Communications, Artificial Intelligence, Hardware and Architecture, Information Systems and Computer Vision and Pattern Recognition, having authored 126 papers that have together received 2.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (51 papers), Advanced Data Storage Technologies (46 papers), Algorithms and Data Compression (39 papers), Cloud Computing and Resource Management (25 papers), Distributed and Parallel Computing Systems (21 papers), Advanced Data Compression Techniques (15 papers), IoT and Edge/Fog Computing (11 papers) and Distributed systems and fault tolerance (8 papers). The work is most often cited by research in Hardware and Architecture (649 citations), Computer Networks and Communications (1.3k citations), Computational Mathematics (15 citations), Information Systems (561 citations) and Artificial Intelligence (783 citations). Sheng Di has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Franck Cappello, Zizhong Chen, Dingwen Tao, Xin Liang, Derrick Kondo, Walfredo Cirne, Kai Zhao, Sihuan Li, Cho‐Li Wang and Song Wu. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, The International Journal of High Performance Computing Applications, IEEE Transactions on Cloud Computing, Future Generation Computer Systems and IEEE Transactions on Computers.

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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