Murray Campbell

4.8k citations
112 papers · 2.4k · 1 hit paper · h-index 24

Impact in

Papers in

Murray Campbell

98 papers receiving 2.1k citations

Murray Campbell's Hit Papers

Deep Blue 2002 · 592 citations
5920+8+16Years since publication100200300400500

Peers

Murray Campbell
Comparison fields: 5 of 182
  • Artificial Intelligence 1.2k
  • Health Informatics 43
  • Computer Vision and Pattern Recognition 528
  • Signal Processing 232
  • Music 50
Replace Fabio Petroni with:
Fabio Petroni Italy
Simon Colton United Kingdom
Kang Hao Cheong Singapore
H.J. van den Herik Netherlands
Julian Togelius United States
Luis von Ahn United States
Simon Colton United Kingdom
Yoav Goldberg Israel
Devamanyu Hazarika Singapore
Robert M. French France
Murray Campbell relative to Fabio Petroni Italy Fabio Petroni's profile →
Citations per field
00.5×10×16.7×
Fabio Petroni · 1×
Citations per year

Countries citing papers authored by Murray Campbell

Since Specialization
Citations

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

Fields of papers citing papers by Murray Campbell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Blue
Hit paper breakdown →
2002592
2 2004145
3 2008141
4 198291
5 199090
6
IBM Research TRECVID-2006 Video Retrieval System
200677
7 202072
8 200861
9 198358
10 200057
11 199056
12 201952
13 199050
14
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
201749
15
Learning to Teach in Cooperative Multiagent Reinforcement Learning
201849
16 202044
17 199930
18 201129
19 199429
20 200328

About Murray Campbell

Murray Campbell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Music and Economics and Econometrics, having authored 112 papers that have together received 2.4k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (27 papers), Music and Audio Processing (16 papers), Artificial Intelligence in Games (15 papers), Diverse Musicological Studies (11 papers), Reinforcement Learning in Robotics (10 papers), Topic Modeling (10 papers), Sports Analytics and Performance (9 papers) and Explainable Artificial Intelligence (XAI) (8 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Health Informatics (43 citations), Computer Vision and Pattern Recognition (528 citations), Signal Processing (232 citations) and Music (50 citations). Murray Campbell has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Feng-hsiung Hsu, T.A. Marsland, Clive Greated, Thomas Anantharaman, William R. Hogan, Howard Burkom, Andrew Moore, David L. Buckeridge, Apostol Natsev and Gary S. Pittman. Their work appears in journals such as The Journal of the Acoustical Society of America, Artificial Intelligence, IBM Journal of Research and Development, Applied Acoustics and Human Rights Law Review.

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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