Hsin‐Te Wu

894 citations
55 papers · 583 · h-index 13

Impact in

Papers in

Hsin‐Te Wu

49 papers receiving 551 citations

Peers

Hsin‐Te Wu
Comparison fields: 5 of 90
  • Computer Networks and Communications 168
  • Information Systems 160
  • Signal Processing 74
  • Business and International Management 8
  • Automotive Engineering 44
Replace Muhammad Umar Farooq with:
Muhammad Umar Farooq Pakistan
Kamal Gulati India
Amrit Mukherjee India
Syed Bilal Hussain Shah China
Biplob Ray Australia
Amitangshu Pal United States
Ziqian Dong United States
Alfred Daniel India
Van-Hau Nguyen Vietnam
Sheeraz Ahmed Pakistan
Hsin‐Te Wu relative to Muhammad Umar Farooq Pakistan Muhammad Umar Farooq's profile →
Citations per field
00.5×2.6×
Muhammad Umar Farooq · 1×
Citations per year

Countries citing papers authored by Hsin‐Te Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hsin‐Te Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201989
2 201970
3 201748
4 200445
5 201839
6 202030
7 202026
8
Optimal Route Planning System for Logistics Vehicles Based on Artificial Intelligence
202018
9 201918
10 200317
11 201116
12 200714
13 202012
14 202111
15 201811
16 20229
17 20199
18 20198
19 20218
20 20147

About Hsin‐Te Wu

Hsin‐Te Wu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 583 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (7 papers), Vehicular Ad Hoc Networks (VANETs) (7 papers), Blockchain Technology Applications and Security (6 papers), Cryptography and Data Security (4 papers), IoT and Edge/Fog Computing (4 papers), Smart Agriculture and AI (4 papers), Water Quality Monitoring Technologies (4 papers) and Advanced Authentication Protocols Security (3 papers). The work is most often cited by research in Computer Networks and Communications (168 citations), Information Systems (160 citations), Signal Processing (74 citations), Business and International Management (8 citations) and Automotive Engineering (44 citations). Hsin‐Te Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chun‐Wei Tsai, Fan‐Hsun Tseng, Hsin‐Hung Cho, Gwo-Jiun Horng, Mu‐Yen Chen, Wu-Chih Hu, Fu‐Kun Chen, Wen‐Shyong Hsieh, S.M. Kuo and Gautam Srivastava. Their work appears in journals such as Journal of Organizational and End User Computing, Enterprise Information Systems, Frontiers in Psychology, IEEE Access and IEEE Consumer Electronics Magazine.

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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