Bibo Tu

504 citations
51 papers · 290 · h-index 10

Impact in

Papers in

Bibo Tu

45 papers receiving 280 citations

Peers

Bibo Tu
Comparison fields: 5 of 42
  • Hardware and Architecture 61
  • Computer Networks and Communications 187
  • Information Systems 180
  • Signal Processing 83
  • Artificial Intelligence 66
Replace Hideyuki Kawashima with:
Hideyuki Kawashima Japan
Michael Hobbs Australia
Hameed Hussain Pakistan
Do Le Quoc Germany
Kun Suo United States
Rodrigo Bruno Portugal
Yasuhiko Kanemasa Japan
Sadjad Fouladi United States
Valentina Timčenko Serbia
Rajeev Wankar India
Bibo Tu relative to Hideyuki Kawashima Japan Hideyuki Kawashima's profile →
Citations per field
00.5×1.5×2.4×
Hideyuki Kawashima · 1×
Citations per year

Countries citing papers authored by Bibo Tu

Since Specialization
Citations

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

Fields of papers citing papers by Bibo Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201158
2 201035
3 200923
4 201014
5 200612
6 200812
7 201812
8 202211
9 202310
10 202010
11 20179
12 20178
13 20216
14 20255
15 20185
16 20194
17 20224
18 20064
19 20094
20 20214

About Bibo Tu

Bibo Tu is a scholar working on Information Systems, Computer Networks and Communications, Artificial Intelligence, Signal Processing and Hardware and Architecture, having authored 51 papers that have together received 290 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (16 papers), Distributed and Parallel Computing Systems (14 papers), Security and Verification in Computing (14 papers), Advanced Malware Detection Techniques (13 papers), Cloud Data Security Solutions (12 papers), Parallel Computing and Optimization Techniques (9 papers), Advanced Data Storage Technologies (9 papers) and Network Security and Intrusion Detection (7 papers). The work is most often cited by research in Hardware and Architecture (61 citations), Computer Networks and Communications (187 citations), Information Systems (180 citations), Signal Processing (83 citations) and Artificial Intelligence (66 citations). Bibo Tu has collaborated with scholars based in China and United States. Frequent co-authors include Jianfeng Zhan, Shengzhong Feng, Xiaohong Zhang, Zhiyong Zhong, Jianping Fan, Jizhong Han, Dan Meng, Jianping Fan, Kai Wang and Jiao Dai. Their work appears in journals such as Cybersecurity, IEEE Transactions on Dependable and Secure Computing, Computers & Security, ACM SIGPLAN Notices and IEEE Internet of Things Journal.

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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