Ching-Hsiang Chu

770 citations
34 papers · 362 indexed · h-index 13

Impact in

Papers in

Ching-Hsiang Chu

34 papers receiving 347 citations

Peers

Ching-Hsiang Chu
Comparison fields: 5 of 40
  • Hardware and Architecture 154
  • Computer Networks and Communications 208
  • Computational Mathematics 4
  • Computer Vision and Pattern Recognition 89
  • Artificial Intelligence 78
Replace Xinxin Mei with:
Xinxin Mei Hong Kong
Denis Foley United States
Maurício Breternitz United States
Mark Gottscho United States
Pitch Patarasuk United States
Gabriel Weisz United States
Fabian Schuiki Switzerland
Ofer Shacham United States
Joonho Song South Korea
Kan Zhong China
Ching-Hsiang Chu relative to Xinxin Mei Hong Kong Xinxin Mei's profile →
Citations per field
00.5×1.6×
Xinxin Mei · 1×
Citations per year

Countries citing papers authored by Ching-Hsiang Chu

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Hsiang Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Hsiang Chu. 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 Ching-Hsiang Chu. The network helps show where Ching-Hsiang Chu may publish in the future.

Co-authorship network

The 23 scholars most cited alongside Ching-Hsiang Chu, 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 Ching-Hsiang Chu Line = papers co-authored together Ching-Hsiang Chu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20244
2 202110
3 202119
4 20207
5 20203
6 202027
7 202043
8 201913
9 201912
10 20191
11 201712
12 20163
13 20166
14 20166
15 201517
16
IVC: Imperceptible Video Communication
201415
17 20144
18 20114
19 201121
20 20101

About Ching-Hsiang Chu

Ching-Hsiang Chu is a scholar working on Hardware and Architecture, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Electrical and Electronic Engineering, having authored 34 papers that have together received 362 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (17 papers), Parallel Computing and Optimization Techniques (16 papers), Distributed and Parallel Computing Systems (8 papers), Caching and Content Delivery (6 papers), Wireless Networks and Protocols (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Advanced Neural Network Applications (4 papers) and Advanced Memory and Neural Computing (3 papers). The work is most often cited by research in Hardware and Architecture (154 citations), Computer Networks and Communications (208 citations), Computational Mathematics (4 citations), Computer Vision and Pattern Recognition (89 citations) and Artificial Intelligence (78 citations). Ching-Hsiang Chu has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Dhabaleswar K. Panda, Hari Subramoni, Ammar Ahmad Awan, Xiaoyi Lu, Khaled Hamidouche, Eric Hsiao‐Kuang Wu, Akshay Venkatesh, Ling‐Jyh Chen, Min-Te Sun and Jahanzeb Maqbool Hashmi. Their work appears in journals such as Parallel Computing, EURASIP Journal on Wireless Communications and Networking, IEEE Transactions on Parallel and Distributed Systems, IEEE Systems Journal and IEEE Sensors 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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