John Hallam

4.0k citations
130 papers · 2.0k · h-index 24

Impact in

Papers in

John Hallam

125 papers receiving 1.9k citations

Peers

John Hallam
Comparison fields: 5 of 137
  • Developmental Biology 127
  • Artificial Intelligence 880
  • Developmental and Educational Psychology 269
  • Human-Computer Interaction 113
  • Cognitive Neuroscience 317
Replace Juan Carlos Gómez with:
Juan Carlos Gómez Argentina
Barbara Webb United Kingdom
Stephen José Hanson United States
Randall D. Beer United States
Todor Ganchev Greece
Lars Kulik Australia
Jun Tani Japan
Shimon Edelman United States
D. J. K. Mewhort Canada
Stefano Nolfi Italy
John Hallam relative to Juan Carlos Gómez Argentina Juan Carlos Gómez's profile →
Citations per field
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Citations per year

Countries citing papers authored by John Hallam

Since Specialization
Citations

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

Fields of papers citing papers by John Hallam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.

#Work
1
From Animals to Animats
2004163
2 2009128
3 200883
4 200782
5 201479
6 200771
7
European Symposium on Artificial Neural Networks
200662
8 200861
9
From Animals to Animats 10
200858
10 200951
11 200251
12 199849
13 200147
14 200246
15 199844
16 200235
17 199834
18 200132
19 198530
20 200030

About John Hallam

John Hallam is a scholar working on Artificial Intelligence, Ecology, Evolution, Behavior and Systematics, Developmental Biology, Ecology and Computer Vision and Pattern Recognition, having authored 130 papers that have together received 2.0k indexed citations. Recurring topics across this work include Bat Biology and Ecology Studies (21 papers), Animal Vocal Communication and Behavior (18 papers), Reinforcement Learning in Robotics (16 papers), Marine animal studies overview (15 papers), Artificial Intelligence in Games (14 papers), Modular Robots and Swarm Intelligence (10 papers), Educational Games and Gamification (9 papers) and Evolutionary Algorithms and Applications (9 papers). The work is most often cited by research in Developmental Biology (127 citations), Artificial Intelligence (880 citations), Developmental and Educational Psychology (269 citations), Human-Computer Interaction (113 citations) and Cognitive Neuroscience (317 citations). John Hallam has collaborated with scholars based in Denmark, United Kingdom and United States. Frequent co-authors include Georgios N. Yannakakis, Henrik Hautop Lund, Herbert Peremans, Wei‐Po Lee, Auke Jan Ijspeert, Sethu Vijayakumar, Aude Billard, Stefan Schaal, Héctor P. Martínez and Alan T. Murray. Their work appears in journals such as The Journal of the Acoustical Society of America, Adaptive Behavior, International Journal of Neural Systems, Robotics and Autonomous Systems and Ecological Informatics.

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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