A. Wu

699 citations
54 papers · 507 indexed · h-index 12

Impact in

Papers in

A. Wu

49 papers receiving 480 citations

Peers

A. Wu
Comparison fields: 5 of 73
  • Hardware and Architecture 79
  • Artificial Intelligence 196
  • Electrical and Electronic Engineering 223
  • Computer Networks and Communications 87
  • Control and Systems Engineering 86
Replace Ebrahim M. Songhori with:
Ebrahim M. Songhori United States
Luis Parrilla Spain
Tughrul Arslan United Kingdom
Zishen Wan United States
Duncan J. M. Moss Australia
Chang Wu China
M. B. Srinivas India
Mukul Sutaone India
Xiaolong Ma United States
Bertil Svensson Sweden
A. Wu relative to Ebrahim M. Songhori United States Ebrahim M. Songhori's profile →
Citations per field
00.5×3.4×
Ebrahim M. Songhori · 1×
Citations per year

Countries citing papers authored by A. Wu

Since Specialization
Citations

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

Fields of papers citing papers by A. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200164
2 199154
3 201940
4 200028
5 200327
6 201525
7 200322
8 199617
9 200016
10 200815
11 200214
12 200312
13 200510
14 201910
15
GPS Satellite Timing Performance Using the Autonomous Navigation (Autonav)
19989
16 20189
17 20069
18 20028
19 19988
20 19977

About A. Wu

A. Wu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Control and Systems Engineering, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 54 papers that have together received 507 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (10 papers), Evolutionary Algorithms and Applications (7 papers), Neural Networks and Applications (7 papers), Advanced Algorithms and Applications (6 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), VLSI and FPGA Design Techniques (6 papers), Video Coding and Compression Technologies (5 papers) and Low-power high-performance VLSI design (5 papers). The work is most often cited by research in Hardware and Architecture (79 citations), Artificial Intelligence (196 citations), Electrical and Electronic Engineering (223 citations), Computer Networks and Communications (87 citations) and Control and Systems Engineering (86 citations). A. Wu has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Henry Shu-Hung Chung, S.Y.R. Hui, Jack L. Meador, Jun Zhang, Wai‐Lun Lo, Huaqing Min, Derek Pao, Chengguo Liu, Kwan L. Yeung and P.K.S. Tam. Their work appears in journals such as Electronics Letters, Applied Soft Computing, Alexandria Engineering Journal, IEEE Transactions on Consumer Electronics and IEEE Transactions on Industrial Electronics.

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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