David Powers

10.2k citations
167 papers · 2.4k · h-index 26

Impact in

Papers in

David Powers

147 papers receiving 2.2k citations

Peers

David Powers
Comparison fields: 5 of 157
  • Signal Processing 307
  • Artificial Intelligence 849
  • Cognitive Neuroscience 479
  • Computer Vision and Pattern Recognition 500
  • Ocean Engineering 261
Replace Risto Miikkulainen with:
Risto Miikkulainen United States
Charles Rosenberg United States
Nicholas Roy United States
Kevin Warwick United Kingdom
Sridhar Mahadevan United States
Hans Moravec United States
Anthony R. Cassandra United States
Bharath Chandrasekaran United States
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Salvatore Gaglio Italy
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Citations per field
00.5×3.7×
Risto Miikkulainen · 1×
Citations per year

Countries citing papers authored by David Powers

Since Specialization
Citations

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

Fields of papers citing papers by David Powers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 167 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998210
2 2008145
3 1967141
4
Measuring semantic similarity in the taxonomy of WordNet
2005110
5 201790
6 200780
7
Verb similarity on the taxonomy of WordNet
200677
8 201564
9 198961
10 201853
11 201252
12 201546
13 198342
14 200540
15
A unified taxonomic framework for information visualization
200339
16 201239
17 201838
18 201036
19 201535
20 201430

About David Powers

David Powers is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Signal Processing and Experimental and Cognitive Psychology, having authored 167 papers that have together received 2.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (22 papers), Topic Modeling (16 papers), EEG and Brain-Computer Interfaces (15 papers), Robotic Path Planning Algorithms (13 papers), Neural Networks and Applications (13 papers), Blind Source Separation Techniques (13 papers), Evolutionary Algorithms and Applications (12 papers) and Speech and dialogue systems (11 papers). The work is most often cited by research in Signal Processing (307 citations), Artificial Intelligence (849 citations), Cognitive Neuroscience (479 citations), Computer Vision and Pattern Recognition (500 citations) and Ocean Engineering (261 citations). David Powers has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Somaiyeh MahmoudZadeh, Richard Leibbrandt, Adham Atyabi, Trent Lewis, Darius Pfitzner, Sean P. Fitzgibbon, Karl Sammut, Amirmehdi Yazdani, Kenneth J. Pope and Christopher Clark. Their work appears in journals such as Neurocomputing, Forensic Science International Genetics, IBM Journal of Research and Development, Clinical Neurophysiology and Acta veterinaria Scandinavica.

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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