Yingjun Wu

1.1k citations
27 papers · 721 · h-index 12

Impact in

Papers in

Yingjun Wu

25 papers receiving 705 citations

Peers

Yingjun Wu
Comparison fields: 5 of 73
  • Computer Networks and Communications 430
  • Information Systems 278
  • Hardware and Architecture 72
  • Signal Processing 89
  • Artificial Intelligence 137
Replace Emanuele Carlini with:
Emanuele Carlini Italy
Yuzhe Tang United States
Ke Chen China
Pan Jun Sun China
Lingjiao Chen China
Sourav Dutta India
Yuedan Chen China
Jun Murai Japan
Yingjun Wu relative to Emanuele Carlini Italy Emanuele Carlini's profile →
Citations per field
00.5×2×4×5.1×
Emanuele Carlini · 1×
Citations per year

Countries citing papers authored by Yingjun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yingjun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Self-Driving Database Management Systems.
2017136
2 2021122
3 2017119
4 201578
5 201244
6 201932
7 201631
8 201229
9 201723
10 200920
11 201418
12 202112
13 202311
14 20239
15
Scalable in-memory transaction processing with HTM
20166
16 20136
17 20145
18 20224
19 20224
20 20154

About Yingjun Wu

Yingjun Wu is a scholar working on Computer Networks and Communications, Information Systems, Signal Processing, Artificial Intelligence and Energy Engineering and Power Technology, having authored 27 papers that have together received 721 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (6 papers), Advanced Data Storage Technologies (5 papers), Distributed systems and fault tolerance (5 papers), Data Management and Algorithms (4 papers), Advanced Database Systems and Queries (4 papers), Blockchain Technology Applications and Security (3 papers), Data Stream Mining Techniques (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Computer Networks and Communications (430 citations), Information Systems (278 citations), Hardware and Architecture (72 citations), Signal Processing (89 citations) and Artificial Intelligence (137 citations). Yingjun Wu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Kian‐Lee Tan, Joy James Prabhu Arulraj, Andrew Pavlo, Chee-Yong Chan, Feng Chen, Zhifeng Hao, Han Pang Huang, Dana Van Aken, Yanqing Ding and Todd C. Mowry. Their work appears in journals such as Ceramics International, IEEE Transactions on Information Forensics and Security, Proceedings of the VLDB Endowment, Frontiers in Oncology and Industrial & Engineering Chemistry Research.

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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