Sai Wu

3.6k citations
123 papers · 2.2k indexed · 1 hit paper · h-index 24

Impact in

Papers in

Sai Wu

111 papers receiving 2.1k citations

Hit Papers

The performance of MapReduce 2010 · 278 citations
2780+5+10Years since publication50100150200250

Peers

Sai Wu
Comparison fields: 5 of 108
  • Signal Processing 578
  • Computer Networks and Communications 1.1k
  • Information Systems 1.1k
  • Computer Science Applications 194
  • Computer Vision and Pattern Recognition 468
Replace Anish Das Sarma with:
Anish Das Sarma United States
Xiaofeng Meng China
Yuanyuan Tian United States
Shuai Ma China
Neoklis Polyzotis United States
Bin Yao China
Wilfred Ng Hong Kong
Cuiping Li China
Emanuele Della Valle Italy
Jun Shao China
Sai Wu relative to Anish Das Sarma United States Anish Das Sarma's profile →
Citations per field
00.5×5.6×
Anish Das Sarma · 1×
Citations per year

Countries citing papers authored by Sai Wu

Since Specialization
Citations

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

Fields of papers citing papers by Sai Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The performance of MapReduce
Hit paper breakdown →
2010278
2 2012183
3 2010118
4 2014110
5 2011105
6 201095
7 201691
8 201176
9 201173
10 201961
11 201160
12 201650
13 201050
14 200947
15 201443
16 201334
17 201431
18 201131
19 202030
20 201330

About Sai Wu

Sai Wu is a scholar working on Computer Networks and Communications, Information Systems, Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 123 papers that have together received 2.2k indexed citations. Recurring topics across this work include Data Management and Algorithms (32 papers), Cloud Computing and Resource Management (23 papers), Advanced Database Systems and Queries (19 papers), Peer-to-Peer Network Technologies (13 papers), Caching and Content Delivery (13 papers), Data Quality and Management (11 papers), Advanced Data Storage Technologies (11 papers) and Advanced Image and Video Retrieval Techniques (11 papers). The work is most often cited by research in Signal Processing (578 citations), Computer Networks and Communications (1.1k citations), Information Systems (1.1k citations), Computer Science Applications (194 citations) and Computer Vision and Pattern Recognition (468 citations). Sai Wu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Beng Chin Ooi, Dawei Jiang, Lei Shi, Kian‐Lee Tan, Dongxiang Zhang, Gang Chen, Feng Li, Chun Chen, Jianzhong Li and Yanyan Shen. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Transactions on Knowledge and Data Engineering, Data Science and Engineering, Information Sciences and ACM Computing Surveys.

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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