A.W.-C. Fu

2.8k citations
21 papers · 1.7k indexed · 1 hit paper · h-index 14

A.W.-C. Fu

21 papers receiving 1.6k citations

Hit Papers

HOT SAX: Efficiently Finding the Most Unusual Time Series...4592006202620122019100200300400

Peers

A.W.-C. Fu
Comparison fields: 5 of 106
  • Signal Processing 759
  • Artificial Intelligence 1.0k
  • Information Systems 706
  • Computational Theory and Mathematics 476
  • Computer Networks and Communications 359
Replace Vipin Kumar with:
Vipin Kumar United States
Ricard Gavaldà Spain
Stephen D. Bay United States
Dominik Ślȩzak Poland
Youxi Wu China
King-Ip Lin United States
Edwin M. Knorr Canada
Hesam Izakian Canada
Shusaku Tsumoto Japan
Sheng Ma United States
A.W.-C. Fu relative to Vipin Kumar United States Vipin Kumar's profile →
Citations per field
00.5×2.8×
Vipin Kumar · 1×
Citations per year

Countries citing papers authored by A.W.-C. Fu

Since Specialization
Citations

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

Fields of papers citing papers by A.W.-C. Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A.W.-C. Fu. 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.W.-C. Fu. The network helps show where A.W.-C. Fu may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20245
2 20233
3 200919
4 200829
5 200817
6 200648
7
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequencebreakdown →
2006459
8 200615
9 200591
10 20047
11 2003168
12 200331
13 20022
14 2002259
15 20022
16 2002234
17 199970
18 19982
19 1996203
20 198912

About A.W.-C. Fu

A.W.-C. Fu is a scholar working on Signal Processing, Computational Theory and Mathematics, Information Systems, Artificial Intelligence and Computer Networks and Communications, having authored 21 papers that have together received 1.7k indexed citations. Recurring topics across this work include Data Management and Algorithms (7 papers), Data Mining Algorithms and Applications (6 papers), Time Series Analysis and Forecasting (4 papers), Rough Sets and Fuzzy Logic (4 papers), Distributed systems and fault tolerance (3 papers), Advanced Database Systems and Queries (2 papers), Complex Systems and Time Series Analysis (2 papers) and Cryptography and Data Security (2 papers). The work is most often cited by research in Signal Processing (759 citations), Artificial Intelligence (1.0k citations), Information Systems (706 citations), Computational Theory and Mathematics (476 citations) and Computer Networks and Communications (359 citations). A.W.-C. Fu has collaborated with scholars based in Hong Kong, Canada and United States. Frequent co-authors include Jessica Lin, Eamonn Keogh, Vincent Ng, Yongjian Fu, David W. Cheung, Wai-Chuen Kwong, Cheng Chen, C. Yu, Jiawei Han and Helga Van Herle. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Intelligent Vehicles, Computers & Mathematics with Applications, Transportation Research Record Journal of the Transportation Research Board and IEEE Transactions on Neural Networks.

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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