Manghui Tu

588 citations
37 papers · 388 indexed · h-index 9

Manghui Tu

35 papers receiving 356 citations

Peers

Manghui Tu
Comparison fields: 5 of 75
  • Software 37
  • Information Systems 209
  • Signal Processing 81
  • Computer Networks and Communications 156
  • Computer Science Applications 31
Replace Atsuo Hazeyama with:
Atsuo Hazeyama Japan
Jungwoo Ryoo United States
Carsten Kleiner Germany
Susan Mengel United States
Saadiah Yahya Malaysia
Boni García Spain
Stephen Oney United States
Marzieh Ahmadzadeh Iran
David Stotts United States
Fernando Trinta Brazil
Manghui Tu relative to Atsuo Hazeyama Japan Atsuo Hazeyama's profile →
Citations per field
00.5×2.9×
Atsuo Hazeyama · 1×
Citations per year

Countries citing papers authored by Manghui Tu

Since Specialization
Citations

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

Fields of papers citing papers by Manghui Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20181
2 201874
3 201867
4 20171
5 20155
6 20133
7 20133
8 20127
9 201270
10 201018
11
Recruiting Students to Computer Science Program via Online Games.
20081
12
A Scalable Update Protocol for Peer-to-Peer Data Grids.
20080
13 20071
14 20071
15 20077
16
A data management framework for secure and dependable data grid
20068
17 20055
18 200513
19 20045
20 19991

About Manghui Tu

Manghui Tu is a scholar working on Computer Networks and Communications, Software and Computer Science Applications, having authored 37 papers that have together received 388 indexed citations. Recurring topics across this work include Distributed systems and fault tolerance (9 papers), Caching and Content Delivery (7 papers), Distributed and Parallel Computing Systems (6 papers), Advanced Data Storage Technologies (5 papers), Information and Cyber Security (5 papers), Peer-to-Peer Network Technologies (4 papers), Educational Games and Gamification (4 papers) and Smart Grid Security and Resilience (3 papers). The work is most often cited by research in Software (37 citations), Information Systems (209 citations) and Signal Processing (81 citations). Manghui Tu has collaborated with scholars based in United States, Taiwan and Malaysia. Frequent co-authors include Ge Jin, Jonathan White, Tae-Hoon Kim, I‐Ling Yen, Dianxiang Xu, Weifeng Xu, Latifur Khan, B. Thuraisingham, Farokh Bastani and Dianxiang Xu. Their work appears in journals such as IEEE Transactions on Dependable and Secure Computing, Journal of Grid Computing, IEEE Transactions on Reliability, The Lancet and Current Alzheimer 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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